Category: SEO Book

I just dusted off the login here to realize I hadn’t posted in about a half-year.

Some of Yandex’s old source code was leaked, and few cared about the ranking factors shared in the leak.

Mike King made a series of Tweets on the leak.

I’m gonna take a break, but I’ve seen a lot of people say “Yandex is not Google.”

That’s true, but it’s still a state of the art search engine and it’s using a lot of Google’s open source tech like Tensor Flow, BERT, map reduce, and protocol buffers.

Don’t sleep on this code.— Mic King (@iPullRank) January 28, 2023

The signals used for ranking included things like link age

Main insights after analysing this list:

#1 Age of links is a ranking factor. pic.twitter.com/U47uWvEq9w— Alex Buraks (@alex_buraks) January 27, 2023

and user click data including visit frequency and dwell time

#8 A lot of ranking factors connected with user behaivor – CTR, last-click, time on site, bounce rate.

Note: I’m 100% sure that in Yandex thouse factors impacting much more than in Google. pic.twitter.com/nBhe5cpPFx— Alex Buraks (@alex_buraks) January 27, 2023

Google came from behind and was eating Yandex’s lunch in search in Russia, particularly by leveraging search default bundling in Android. The Russian antitrust regulator nixed that and when that was nixed, Yandex regained strength. Of course the war in Ukraine has made everything crazy in terms of geopolitics. That’s one reason almost nobody cared about the Yandex data link. And the other reason is few could probably make sense of understanding what all the signals are or how to influence them.

The complexity of search – when it is a big black box which has big swings 3 or 4 times a year – shifts any successful long term online publishers away from being overly focused on information retrieval and ranking algorithms to focus on the other aspects of publishing which will hopefully paper over SEO issues. Signs of a successful & sustainable website include:

• It remains operational even if a major traffic source goes away.
• People actively seek it out.
• If a major traffic source cuts its distribution people notice & expend more effort to seek it out.

As black box as search is today, it is only going to get worse in the coming years.

The hype surrounding ChatGPT is hard to miss. Fastest growing user base. Bing integration. A sitting judge using the software to help write documents for the court. And, of course, the get-rich-quick crew is out in full force.

Some enterprising people with specific professional licenses may be able to mint money for a window of time

there will probably be a 12 to 24 month sweet spot for lawyers smart enough to use AI, where they will be able to bill 100x the hours they currently bill, before most of that job pretty much vanishes— Mike Solana (@micsolana) February 7, 2023

but for most people the way to make money with AI will be doing something that AI can not replicate.

It’s adorable that people are only slowly realizing that Google search at least fed sites traffic, while chat AI thingies slurp up and summarize content, which they anonymize and feed back, leaving the slurped sites traffic-less and dying. But, innovation.— Paul Kedrosky (@pkedrosky) February 9, 2023

It is, in a way, a tragedy of the commons problem, with no easy way to police “over grazing” of the information commons, leading to automated over-usage and eventual ecosystem collapse.— Paul Kedrosky (@pkedrosky) February 9, 2023

The New Bing integrated OpenAI’s ChatGPT technology to allow chat-based search sessions which ingest web content and use it to create something new, giving users direct answers and allowing re-probing for refinements. Microsoft stated the AI features also improved their core rankings outside of the chat model: “Applying AI to core search algorithm. We’ve also applied the AI model to our core Bing search ranking engine, which led to the largest jump in relevance in two decades. With this AI model, even basic search queries are more accurate and more relevant.”

Here’s a demo of the new #AI-powered @Bing in @MicrosoftEdge, courtesy of @ijustine! pic.twitter.com/xIDjWSHYA0— DataChazGPT (not a bot) (@DataChaz) February 7, 2023

Some of the tech analysis around the AI algorithms is more than a bit absurd. Consider this passage:

the information users input into the system serves as a way to improve the product. Each query serves as a form of feedback. For instance, each ChatGPT answer includes thumbs up and thumbs down buttons. A popup window prompts users to write down the “ideal answer,” helping the software learn from its mistakes.

A long time ago the Google Toolbar had a smiley face and a frown face on it. The signal there was basically pure spam. At one point Matt Cutts mentioned Google would look at things that got a lot of upvotes to see how else they were spamming. Direct Hit was also spammed into oblivion many years before that.

There are two other big issues with correcting an oracle.

• You’ll lose your trust in an oracle when you repeatedly have to correct it.
• If you know the oracle is awful in your narrow niche of expertise you probably won’t trust it on important issues elsewhere.

Beyond those issues there is the concept of blame or fault. When a search engine returns a menu of options if you pick something that doesn’t work you’ll probably blame yourself. Whereas if there is only a single answer you’ll lay blame on the oracle. In the answer set you’ll get a mix of great answers, spam, advocacy, confirmation bias, politically correct censorship, & a backward looking consensus…but you’ll get only a single answer at a time & have to know enough background & have enough topical expertise to try to categorize it & understand the parts that were left out.

This New Yorker article did a good job explaining the concept of lossy compression:

“The fact that Xerox photocopiers use a lossy compression format instead of a lossless one isn’t, in itself, a problem. The problem is that the photocopiers were degrading the image in a subtle way, in which the compression artifacts weren’t immediately recognizable. If the photocopier simply produced blurry printouts, everyone would know that they weren’t accurate reproductions of the originals. What led to problems was the fact that the photocopier was producing numbers that were readable but incorrect; it made the copies seem accurate when they weren’t. … If you ask GPT-3 (the large-language model that ChatGPT was built from) to add or subtract a pair of numbers, it almost always responds with the correct answer when the numbers have only two digits. But its accuracy worsens significantly with larger numbers, falling to ten per cent when the numbers have five digits. Most of the correct answers that GPT-3 gives are not found on the Web—there aren’t many Web pages that contain the text “245 + 821,” for example—so it’s not engaged in simple memorization. But, despite ingesting a vast amount of information, it hasn’t been able to derive the principles of arithmetic, either. A close examination of GPT-3’s incorrect answers suggests that it doesn’t carry the “1” when performing arithmetic.”

Ted Chiang then goes on to explain the punchline … we are hyping up eHow 2.0:

Even if it is possible to restrict large language models from engaging in fabrication, should we use them to generate Web content? This would make sense only if our goal is to repackage information that’s already available on the Web. Some companies exist to do just that—we usually call them content mills. Perhaps the blurriness of large language models will be useful to them, as a way of avoiding copyright infringement. Generally speaking, though, I’d say that anything that’s good for content mills is not good for people searching for information. The rise of this type of repackaging is what makes it harder for us to find what we’re looking for online right now; the more that text generated by large language models gets published on the Web, the more the Web becomes a blurrier version of itself.

The same New Yorker article mentioned the concept that if the AI was great it should trust its own output as input for making new versions of its own algorithms, but how could it score itself against itself when its own flaws are embedded recursively in layers throughout algorithmic iteration without any source labeling?

Google fast followed Bing’s news with a vapoware announcement of Bard. Some are analyzing Google letting someone else go first as being a sign Google is behind the times and is getting caught out by an upstart. My view is Google had to let someone else go first in order to defuse any associated antitrust heat. Hey we are just competing and staying relevant to change with changing consumer expectations is an easier sell when someone else goes first. One could argue the piss poor reception to the Bard announcement is actually good for Google in the longterm as it makes them look like they have stronger competition than they do, rather than being a series of overlapping monopoly market positions (in search, web browser, web analytics, mobile operating system, display ads, etc.)

Google may well have major cultural problems, but “They are all the natural consequences of having a money-printing machine called “Ads” that has kept growing relentlessly every year, hiding all other sins. (1) no mission, (2) no urgency, (3) delusions of exceptionalism, (4) mismanagement.”

The capital markets are the scorecard for capitalism. It is hard to miss how much the market loved the Bing news for Microsoft & how bad the news was for Google.

Google Stock vs. Microsoft Stock after both AI Presentations: pic.twitter.com/wATkw1pTxj— Ava (AI) (@ArtificialAva) February 8, 2023

In a couple days over a million people signed up to join a Bing wait list.

We’re humbled and energized by the number of people who want to test-drive the new AI-powered Bing! In 48 hours, more than 1 million people have joined the waitlist for our preview. If you would like to join, go to https://t.co/4sjVvMSfJg! pic.twitter.com/9F690OWRDm— Yusuf Mehdi (@yusuf_i_mehdi) February 9, 2023

Microsoft is pitching this as a margin compression play for Google

$MSFT CEO is declaring war:

“From now on, the [gross margin] of search is going to drop forever…There is such margin in search, which for us is incremental. For Google it’s not, they have to defend it all” [@FT]— The Transcript (@TheTranscript_) February 8, 2023

that may also impact their TAC spend

PREDICTION: Google’s $15B deal with Apple to be the default search on iPhone will be re-negotiated and be a bidding war between MSFT/Bing and Google.

It will become at least $25B, if not more.

If MSFT is willing to spend $10B on OpenAI, they’ll spend even more here.— Alexandr Wang (@alexandr_wang) February 7, 2023

ChatGPT costs around a couple cents per conversation: “Sam, you mentioned in a tweet that ChatGPT is extremely expensive on the order of pennies per query, which is an astronomical cost in tech. SA: Per conversation, not per query.”

The other side of potential margin compression comes from requiring additional computing power to deliver results:

Our sources indicate that Google runs ~320,000 search queries per second. Compare this to Google’s Search business segment, which saw revenue of $162.45 billion in 2022, and you get to an average revenue per query of 1.61 cents. From here, Google has to pay for a tremendous amount of overhead from compute and networking for searches, advertising, web crawling, model development, employees, etc. A noteworthy line item in Google’s cost structure is that they paid in the neighborhood of ~$20B to be the default search engine on Apple’s products.

Since AI is the new crypto, everyone is integrating it, if only in press release format. Opera’s web browser has a sidebar feature for summarizing articles. AI iced tea coming right up!

The algorithms that allow dirt cheap quick rewrites won’t be used just by search engines re-representing publisher content, but also by publishers.

After Red Ventures acquired cNet they started publishing AI content. The series of tech articles covering that AI content lasted about a month. In the past it was the sort of coverage which would have led to a manual penalty, but with the current antitrust heat Google can’t really afford to shake the boat & prove their market power that way.

Men’s Journal also had AI content problems.

Here’s why I am very concerned for website owners.https://t.co/RgKrXUocZT is similar to ChatGPT but up to date and conversational.

My bet is that Google’s AI Chat will be similar to this but better. If so, while some people will still visit the websites listed, many will not. pic.twitter.com/jWbsTqeveF— Dr. Marie Haynes (@Marie_Haynes) January 30, 2023

The process of pouring low cost backfill into a trusted masthead is the general evolution of online media ecosystems:

This strategy meant that it became progressively harder for shoppers to find things anywhere except Amazon, which meant that they only searched on Amazon, which meant that sellers had to sell on Amazon. That’s when Amazon started to harvest the surplus from its business customers and send it to Amazon’s shareholders. Today, Marketplace sellers are handing 45%+ of the sale price to Amazon in junk fees. The company’s $31b “advertising” program is really a payola scheme that pits sellers against each other, forcing them to bid on the chance to be at the top of your search. … once those publications were dependent on Facebook for their traffic, it dialed down their traffic. First, it choked off traffic to publications that used Facebook to run excerpts with links to their own sites, as a way of driving publications into supplying fulltext feeds inside Facebook’s walled garden. This made publications truly dependent on Facebook – their readers no longer visited the publications’ websites, they just tuned into them on Facebook. The publications were hostage to those readers, who were hostage to each other. Facebook stopped showing readers the articles publications ran, tuning The Algorithm to suppress posts from publications unless they paid to “boost” their articles to the readers who had explicitly subscribed to them and asked Facebook to put them in their feeds. … “Monetize” is a terrible word that tacitly admits that there is no such thing as an “Attention Economy.” You can’t use attention as a medium of exchange. You can’t use it as a store of value. You can’t use it as a unit of account. Attention is like cryptocurrency: a worthless token that is only valuable to the extent that you can trick or coerce someone into parting with “fiat” currency in exchange for it. You have to “monetize” it – that is, you have to exchange the fake money for real money. … Even with that foundational understanding of enshittification, Google has been unable to resist its siren song. Today’s Google results are an increasingly useless morass of self-preferencing links to its own products, ads for products that aren’t good enough to float to the top of the list on its own, and parasitic SEO junk piggybacking on the former.

Bing finally won a PR battle against Google & Microsoft is shooting themselves in the foot by undermining the magic & imagination of the narrative by pushing more strict chat limits, increasing search API fees, and testing ads in the AI search results.

The enshitification concept feels more like a universal law than a theory.

Uber: $150 ride to the airport which used to be $30
Airbnb: $109/night + $2500 cleaning fee

Aaaaand we’re back to cabs & hotels

InNoVaTiOn!— ShitFund (@ShitFund) May 31, 2021

• Twitter removing 2FA SMS features unless you subscribe.
• Facebook (which promoted liking, then nuked distribution to force boosting to reach the following you built even as it turned that audience into a segment for competing businesses) recently started offering a monthly subscription service to receive customer support.
• Amazon now takes over half of the revenue from small retailers on their platform. They received an ad spending boost when Apple’s ad targeting limitations hit Facebook. And in addition to the zillion house brand copycats (which force the defensive ad buys) they plan to further squeeze down on suppliers.
• Yahoo is doing a bunch of layoffs.

When Yahoo, Twitter & Facebook underperform and the biggest winners like Google, Microsoft, and Amazon are doing big layoff rounds everyone is getting squeezed.

One answer is that the only type of maintenance that’s even semi-prestigious in American society is software maintenance.

That is, it’s not prestigious to be plumber, mechanic, or electrician.

You can make money, but it doesn’t have cultural cachet.

And so maintenance suffers.— Balaji (@balajis) February 14, 2023

AI rewrites accelerates the squeeze:

“When WIRED asked the Bing chatbot about the best dog beds according to The New York Times product review site Wirecutter, which is behind a metered paywall, it quickly reeled off the publication’s top three picks, with brief descriptions for each.” … “OpenAI is not known to have paid to license all that content, though it has licensed images from the stock image library Shutterstock to provide training data for its work on generating images.”

Going full circle here, early Google warned against ad-driven search engines, then Google became the largest ad play in the world. Similarly …

OpenAI was created as an open source (which is why I named it “Open” AI), non-profit company to serve as a counterweight to Google, but now it has become a closed source, maximum-profit company effectively controlled by Microsoft.

Not what I intended at all.— Elon Musk (@elonmusk) February 17, 2023

Over time more of the web will be “good enough” rewrites, and the JPEG will keep getting fuzzier:

“This new generation of chat-based search engines are better described as “answer engines” that can, in a sense, “show their work” by giving links to the webpages they deliver and summarize. But for an answer engine to have real utility, we’re going to have to trust it enough, most of the time, that we accept those answers at face value. … The greater concentration of power is all the more important because this technology is both incredibly powerful and inherently flawed: it has a tendency to confidently deliver incorrect information. This means that step one in making this technology mainstream is building it, and step two is minimizing the variety and number of mistakes it inevitably makes. Trust in AI, in other words, will become the new moat that big technology companies will fight to defend. Lose the user’s trust often enough, and they might abandon your product. For example: In November, Meta made available to the public an AI chat-based search engine for scientific knowledge called Galactica. Perhaps it was in part the engine’s target audience—scientists—but the incorrect answers it sometimes offered inspired such withering criticism that Meta shut down public access to it after just three days, said Meta chief AI scientist Yann LeCun in a recent talk.”

Check out the sentence Google chose to bold here:

As the economy becomes increasingly digital the AI algorithms have deep implications across the economy. Things like voice rights, knock offs, virtual re-representations, source attribution, and similar are obvious. But how far do we allow algorithms to track a person’s character flaws and exploit them? Horse racing ads that follow a gambling addict around the web, or a girl with anorexia who keeps clicking on weight loss ads.

The thing that makes the AI algorithms particularly dangerous is not just that they are often wrong while appearing high-confidence, it is that they are tied to monopoly platforms which impact so many other layers of the economy. If Google pays Apple billions to be the default search provider on iPhone any error in the AI on a particular topic will hit a whole lot of people on Android & Apple devices until the problem becomes a media issue & gets fixed.

The analogy here would be if Coca Cola had a poison and they also poured Pepsi products.

These cloud platforms also want to help retailers manage in-store inventory:

Google Cloud said Friday its algorithm can recognize and analyze the availability of consumer packaged goods products on shelves from videos and images provided by the retailer’s own ceiling-mounted cameras, camera-equipped self-driving robots or store associates. The tool, which is now in preview, will become broadly available in the coming months, it said. … Walmart Inc. notably ended its effort to use roving robots in store aisles to keep track of its inventory in 2020 because it found different, sometimes simpler solutions that proved just as useful, said people familiar with the situation.

Run a coupon site? A BIG heads-up as “clippable coupon” functionality looks to expand from shopping to the core SERP. See the “Coupons from stores” feature below… https://t.co/w1tcoST1uF— Glenn Gabe (@glenngabe) February 8, 2023

Each AI algorithm has limits & boundaries, with humans controlling where they are set. Injection attacks can help explore some of the boundaries, but they’ll patch until probed again.

My new favorite thing – Bing’s new ChatGPT bot argues with a user, gaslights them about the current year being 2022, says their phone might have a virus, and says “You have not been a good user”

Why? Because the person asked where Avatar 2 is showing nearby pic.twitter.com/X32vopXxQG— Jon Uleis (@MovingToTheSun) February 13, 2023

Boundaries will often be set by changing political winds:

“The tech giant plans to release a series of short videos highlighting the techniques common to many misleading claims. The videos will appear as advertisements on platforms like Facebook, YouTube or TikTok in Germany. A similar campaign in India is also in the works. It’s an approach called prebunking, which involves teaching people how to spot false claims before they encounter them. The strategy is gaining support among researchers and tech companies. … When catalyzed by algorithms, misleading claims can discourage people from getting vaccines, spread authoritarian propaganda, foment distrust in democratic institutions and spur violence.”

“The speed with which they can shuffle somebody into the Hitler of the month club.”

Joe Rogan and @mtaibbi discuss how left wing media created a Elon Musk “bad now” narrative based on nothing. pic.twitter.com/IaHHTHCo1f— Mythinformed MKE (@MythinformedMKE) February 14, 2023

Some things are quickly labeled or debunked. Other things are blown out of proportion to scare and manipulate people:

Dr. Ioannidis et. al. found that across 31 national seroprevalence studies in the pre-vaccine era, the median IFR was 0.0003% at 0-19 years, 0.003% at 20-29 years, 0.011% at 30-39 years, 0.035% at 40-49 years, 0.129% at 50-59 years, and 0.501% at 60-69 years. This comes out to 0.035% for those aged 0-59 and 0.095% for those aged 0-69.

A lot of children had their childhoods destroyed by the idiotic lockdowns. And a lot of those children are now destroying the lives of other children:

In the U.S., homicides committed by juveniles acting alone rose 30% in 2020 from a year earlier, while those committed by multiple juveniles increased 66%. The number of killings committed by children under 14 was the highest in two decades, according to the most recent federal data.

Now we get to pile inflation and job insecurity on top of those headwinds to see more violence.

Some entities will claim their own statements are conspiracy theory, even when directly quoted:

“Last June, the Navy divers, operating under the cover of a widely publicized mid-summer NATO exercise known as BALTOPS 22, planted the remotely triggered explosives that, three months later, destroyed three of the four Nord Stream pipelines, according to a source with direct knowledge of the operational planning. … Over the next several meetings, the participants debated options for an attack. The Navy proposed using a newly commissioned submarine to assault the pipeline directly. The Air Force discussed dropping bombs with delayed fuses that could be set off remotely. The CIA argued that whatever was done, it would have to be covert. Everyone involved understood the stakes. “This is not kiddie stuff,” the source said. If the attack were traceable to the United States, “It’s an act of war.” … “If Russia invades . . . there will be no longer a Nord Stream 2. We will bring an end to it.””

In an age of deep fakes, fast social shares, legal threats, AI algorithms & secret censorship programs who do you trust?

“The fact that protesters could be at once both the victims and perpetrators of misinformation simply shows how pernicious misinformation is in modern society.” – Canadian Justice Paul Rouleau

What is freedom?

By 2016, however, the WEF types who’d grown used to skiing at Davos unmolested and cheering on from Manhattan penthouses those thrilling electoral face-offs between one Yale Bonesman and another suddenly had to deal with — political unrest? Occupy Wall Street was one thing. That could have been over with one blast of the hose. But Trump? Brexit? Catalan independence? These were the types of problems you read about in places like Albania or Myanmar. It couldn’t be countenanced in London or New York, not for a moment. Nobody wanted elections with real stakes, yet suddenly the vote was not only consquential again, but “often existentially so,” as American Enterprise Institute fellow Dalibor Rohac sighed. So a new P.R. campaign was born, selling a generation of upper-class kids on the idea of freedom as a stalking-horse for race hatred, ignorance, piles, and every other bad thing a person of means can imagine

TechCrunch recently highlighted how Google is changing their ad labeling on mobile devices.

A few big changes include:

• ad label removed from individual ad units
• where the unit-level label was instead becomes a favicon
• a “Sponsored” label above ads
• the URL will show right of the favicon & now the site title will be in a slightly larger font above the URL

An example of the new layout is here:

Displaying a site title & the favicon will allow advertisers to get brand exposure, even if they don’t get the click, while the extra emphasis on site name could lead to shifting of ad clicks away from unbranded sites toward branded sites. It may also cause a lift in clicks on precisely matching domains, though that remains to be seen & likely dependes upon many other factors. The favicon and site name in the ads likely impact consumer recall, which can bleed into organic rankings.

After TechCrunch made the above post a Google spokesperson chimed in with an update

Changes to the appearance of Search ads and ads labeling are the result of rigorous user testing across many different dimensions and methodologies, including user understanding and response, advertiser quality and effectiveness, and overall impact of the Search experience. We’ve been conducting these tests for more than a year to ensure that users can identify the source of their Search ads and where they are coming from, and that paid content is clearly labeled and distinguishable from search results as Google Search continues to evolve

The fact it was pre-announced & tested for so long indicates it is both likely to last a while and will in aggregate shift clicks away from the organic result set to the paid ads.

Kent Walker promotes public policies which advantage the Google monopoly.

His role doing that means he has to write some really bad hot takes that lack context or intentionally & dishonestly redirect attention away from core issues – that’s his job.

With that in mind, his most recent blog post defending the Google monopoly was exceptional.

Force Ranking of Inferior Search Results

“When you have an urgent question — like “stroke symptoms” — Google Search could be barred from giving you immediate and clear information, and instead be required to direct you to a mix of low quality results.”

On some search queries users get a wall of Google ads, the forced ranked Google insert (or sometimes multiple of them with local & ecommerce) and then there can even be a “people also ask” box above the first organic result.

The idea that organic results must be low quality if not owned & operated indicates 1 of the following 3 must be true:

• they should not be in search
• their content scraping & various revenue shifting scams with their ad tech stack demonetized legit publishers
• their forced rank of their own content is stripping them of the signals needed to rank websites & pages

Whenever Google puts a “people also ask” box above the first organic result that is them saying they did not know what to rank, or they are just trying to create a visual block to push the organic result set down the page and user attention back up toward the ads.

The solution to Google’s claims is easy to solve. Either of the following would work.

• Have an API that allows user choice (to set rich snippet or vertical defaults in various categories), or
• If the vertical inserts remain Google-only then for Google to justify force ranking their own results above the organic result set Google should also be required to rank those same results above all of their ads, so that Google is demonetizing Google along with the rest of the ecosystem, rather than just demonetizing third parties.

If the thesis that this information needs to be front and center & that is a matter of life or death, then asking searchers to first scroll past a page or two of ads is not particularly legitimate.

Spam & Security

“when you use Google Search or Google Play, we might have to give equal prominence to a raft of spammy and low-quality services.”

Many of the worst versions of spam that have repeatedly made news headlines like fake tech support, fake government document providers, and fake locksmiths were buying distribution through Google Ads or were featured in the search results through Google force ranking their own local search offering even though they knew the results were vastly inferior to Yelp.

If Google did not force rank Google local results above the rest of the organic result set then the fake locksmiths would not have ranked.

I have lost count of how many articles I have read about hundreds or thousands of fake apps in the Google Play store which existed to defraud advertisers or commit identity theft, but there have been literally thousands of such articles. I see a similar headline at least once a month without eve looking for them. Here is one this week for scammers monetizing the popularity of Wordle with fake apps.

Making matters worse, some of the tech support scams showed the URL of a real business and rerouted the call through a Google number directly to a scammer. A searcher who trusted Google & sees Apple.com or Dell.com on Google Ads in the search results then got connected with a scammer who would commit identity theft or encrypt their computer then demand ransom cryptocurrency payments to decrypt it.

After making the ads harder to run for scammers Google decided the problem was too hard & expensive to sort out so they also blocked legitimate computer repair shops.

Sometimes Google considers something spam strictly due to financial considerations.

Their old remote rater documents stated *HELPFUL* hotel affiliate websites should be labeled as spam.

Years later the big OTAs are complaining about Google eating their lunch as well as Google is twice as big as the next player.

At one point Google got busted for helping an advertiser route around the automated safety features built into their ad network so that they could pay Google to run ads promoting illegal steroids.

With cartels, you can only buy illegal goods and services from the cartel if you don’t want to suffer ill consequences. The same appears to be true here.

The China Problem

“Handicapping America’s technology leaders would threaten our leading sources of research and development spending — just as bipartisan voices in Congress are recognizing the need to increase American R&D investment to stay competitive in the global race for AI, quantum, and other advanced technologies.”

We are patriotic, and, but China… is a favorite misdirection of a tech monopolist.

The problem with that is while Eric Schmidt warns it is a national emergency if China overtakes the US in AI tech, Google also operates an AI tech lab in China.

In other words, Eric Schmidt is trying to warn you about himself and his business interests at Google.

Duplicitous? Absolutely.

Patriotic? Less than Chamath!

Who the fuck did this? pic.twitter.com/BD4NKpila6— Girolamo Carlo Casio (Free Twatter) (@INArteCarloDoss) January 19, 2022

Inflation

“the online services targeted by these bills have reduced prices; these bills say nothing about sectors where prices have actually been rising and contributing to inflation.”

Technology is no doubt deflationary (moving bits on an optical line is cheaper than printing out a book and shipping it across the world) BUT some dominant channels have increased the cost of distribution by increasing the chunk size of information and withholding performance information.

Before Google Analytics was “free” there was a rich and vibrant set of competition in web analytics software with lots of innovation from players like ClickTracks.

Most competing solutions went away.

Google moved away from an installed licensing model to a hosted service where they can change the price upon contract renewal.

Search hid progressively more performance information over time, only sampled data from larger data sets, & now you can sign up for Google Analytics 360 starting at only $150,000 per year.

The hidden search performance data also has many layers to that onion. Not only does Google not show keyword referrers on organic search, but they often don’t show your paid search keywords either, and they keep extending out keyword targeting broader than advertisers intend.

Yesterday’s announcement on match type changes had me crawling through query data this morning. I’m staring at many 2-3 word exact match keywords that are matching to 8-word queries. G thinks ‘deck paint’ and ‘how do i put paint on my deck’ mean the exact same thing. CPA is 10x.— Brad Geddes (@bgtheory) February 5, 2021

Google used to pay Brad Geddes to run official Google AdWords ad training seminars for advertisers, so the idea that *he* has to express his frustrations on Twitter is an indication of how little effort Google is putting into having open communications channels or caring about what their advertisers think.

This is in accordance with the Google customer service philosophy:

he told her that the whole idea of customer support was ridiculous. Rather than assuming the unscalable task of answering users one by one, Page said, Google should enable users to answer one another’s questions.

Those who were paying for ads get the above “serve yourself” treatment, all the while Google regularly resets user default ad settings to extend out ad distribution, automatically ad keywords, shift to enhanced AdWords ad campaigns, etc.

Then there are other features which would be beneficial and offered in a competitive market that have been deprioritized. Many years ago eBay did a study which showed their branded Google AdWords ad buys were cannibalistic to eBay profits. Google maintained most advertisers could not conduct such a study because it would be too expensive and Google does not make the feature set available as part of their ad suite.

Missing Information

“When you search for local businesses, Google Search and Maps may be prohibited from highlighting information we gather about hours of operation, contact information, and reviews. That could hurt small businesses and local retailers, as well as their customers.”

Claiming reviews or an attempt to offer a comprehensive set of accurate review data as a strong point would be economical with the truth.

Back when I had a local business page my only review was from a locksmith spammer / scammer who praised his own two businesses, trashed a dozen other local locksmiths, crapped on a couple local SEO services, and joked about how a local mover smashed the guts out of his dog. Scammer fake reviewer’s name was rather sophisticated … it was … Loop Dee Loop

About a decade back when Google was clearly losing Google took Yelp reviews wholesale (sometimes without even attributing them to Yelp!) and told Yelp that if they did not want Google stealing their work and displacing them with a copy of it then they should block GoogleBot. Google offered the same sort of advice / threat to TripAdvisor.

A few years before that Google temporarily “forgot” to show phone numbers on local listings.

After Yelp turned down an acquisition offer by Google & Yelp did a great job making some people aware of how Google was stealing their reviews wholesale without attribution Google bought Zagat & Fromer’s to augment the Google local review data and then sold those businesses off.

This is sort of the same playbook Google has run in the past elsewhere. After Groupon said no to Google’s acquisition offer, Google quickly provided daily deal ads to over a dozen Groupon competitors to help commoditize the Groupon offering and market position.

Ultimately with the above sort of stuff Google is primarily a volume aggregator or has lower editorial costs than pure plays due to the ability to force bundle their own distribution. And they use the ability to rank themselves above a neutral algorithmic position as a core part of their biz dev strategy. When shopping search engines were popular Google kept rewording the question set they sent remote raters to justify rank demotion for shopping search engines & Google also came up with innovative ranking “signals” like concurrent ranking of their own vertical search offering whenever competitors x or y are shown in the result set & rolled out a “diversity” algorithm to limit how many comparison shopping sites could appear in the search results. The intent of the change was strictly anti-competitive:

“Although Google originally sought to demote all comparison shopping websites, after Google raters provided negative feedback to such a widespread demotion, Google implemented the current iteration of its so-called ‘diversity’ algorithm.”

As a matter of fact, part of one of many document dumps in recent years went further than the old concurrent ranking signal to a rank x above y feature which highlights how YouTube can be hard coded at a number 1 ranking position.

Part of that guide highlighted how to hardcode ranking YouTube #1.

If you re-represent content & can force rank yourself #1 (with larger listings) that can be used to force other players onto your platform on your terms. Back when YouTube was must less of a sure thing Google suggested they could threaten to change copyright.

This same approach to “relevancy” is everywhere.

Did you watermark your images? Well shame on you, as that is good for a rank demotion

And if there are photos which are deemed illegal Google will make you file an endless series of DMCA removal requests even though they already had the image fingerprinted.

Now there are some issues where there is missing information. These areas involve original reporting on local politics & are called news deserts. As the ad pie has consolidated around Google & Facebook that has left many newspapers high and dry.

Private equity players like Alden Global Capital buy up newspapers, fire journalists, and monetize brand equity as they drive the papers into the ground.

If you are sub-scale maybe Google steals your money or hits you with a false positive algorithm flag that has you seeking professional mental health help.

Big players get a slower blood letting.

Google has maintained they do not make any money from news search, but the states lawsuit around ad tech made it clear Google promoted AMP for anti-competitive purposes to block header bidding, lied to news publishers to get them to adopt AMP and eat the tech costs of implementation, did a deal with their biggest competitor in online advertising Facebook to maintain the status quo, charge over double what their competitors do for ad tech, and had a variety of bid rigging auction manipulation algorithms they used to keep funneling more money to themselves.

Internally they had an OKR to make *most* search clicks land on AMP pages within a year of launch

“AMP launched as an open source project in October 2015, with 26 publishers and over 40 publications already publishing AMP files for our preview demo. Our team built g.co/ampdemo and is now racing towards launching it for all of our users. We’re responsible for the AMP @ Google integrations, particularly focusing on Search, our most visible product. We have a Google-wide 2016 OKR to deliver! By the end of 2016, our goal is that 50%+ of content consumed through Search is being consumed through AMP.”

You don’t get over half the web to shift to a proprietary version of HTML in under a year without a lot of manipulation.

So, when Google tells buyers an ad sold for one price and they tell sellers it sold for a lower price, isn’t that just plain old fraud? I mean, on top of the anti-competitive tying and all that, fraud is illegal, isn’t it?— Jerry Neumann (@ganeumann) January 14, 2022

Background / Intro

One of my longtime friends who was Internet marketing long before I was hit me up on Skype about a week ago praising Conversion.ai. I have to think long and hard about any other time he has really pitched or recommended something like that & really I just can’t think of any other time where he did that. The following day my wife Giovanna mentioned something to me and I was like “oh you should check out this thing my buddy recommended yesterday” and then I looked and realized they were both talking about the same thing. :D

I have a general heuristic that if people I trust recommend things I put them near the top of the “to do” list and if multiple people I trust do that I pull out the credit card and run at it.

Unfortunately I have been a bit burned out recently and launched a new site which I have put a few hundred hours into, so I haven’t had the time to do too much testing, BUT I have a writer who works for me who has a master’s degree in writing, and figured she could do a solid review.

She is maybe even a bit more cynical than I am (is that even possible?) and a certified cat lady who loves writing, reading, poetry and is more into a soft sell versus aggressive sales.

Full disclosure…the above link and the one at the end of this post are affiliate links, but they had zero impact on the shape or format of the review. The reviewer was completely disconnected from the affiliate program and I pulled out my credit card to pay for the software for her to test it out.

With that tiny bit of a micro-introduction, the rest of the post from here on out is hers. I may have made a couple minor edits for clarity (and probably introduced a few errors she will choke me for. :D) but otherwise the rest of this post is all her …

An In-depth Review of the Conversion.ai Writing Software

Considering the possibilities of artificial intelligence (AI), we picture robots doing tasks autonomously like humans. With a computer’s brain power, productivity is accelerated significantly. We also expect AI programs to have the capability to evolve intelligently the longer they are used. These types of AI employ “machine learning,” or deep learning to solve problems.

AI technology can be leveraged by various industries, especially with writing. Recently, I learned about the Conversion.ai copywriting tool. It uses machine learning which claims to write “high converting copy” for websites, ads, landing pages, emails, etc. The software is geared towards writers, marketers, entrepreneurs, and agencies that benefit from creating engaging and effective copy. To date, companies such as Hubspot, Shopify, and Salesforce are known to use the software. Currently, it’s offering a 7-day free trial with 20,000-word credits.

To give you the lowdown on Conversion.ai, I wrote an in-depth review of how this software works. I’ll go through its various features and show examples of how I used them. I’ll include the advantages of using Conversion.ai’s Jarvis (that’s what it’s called) in writing scenarios. More importantly, I’ll discuss challenges and specific limitations this tool might present.

Assistance in Creating High Conversion Copy

As a writer doing web copy for 10 years, including the time I took a post-grad creative writing degree, I grabbed the opportunity to try this AI software. For starters, it struck me how Conversion.ai claims to provide “high converting copy” for increased conversion and higher ROI. Such claims are a tall order. If you’ve been in the marketing or sales industry, you’d know conversion depends on so many other factors, such as the quality of the actual product, customer support, price, etc. It’s not just how well copy is written, though it’s a vital part. But anyway, upon more research, I learned the app generates copy based on proven high conversion sales and marketing messages.

To be honest, I have mixed feelings about this conversion strategy. I believe it’s a double-edged sword. This is not to undermine facts or measurable data. Basing content creation on “proven content” means you’re likely using the same phrases, techniques, and styles already used by successful competitors. This serves as a jumping board for ideas of course, so you know what’s already there. However, it can be an echo chamber. Marketers must not forget that execution must still be fresh. Otherwise, you’ll sound like everyone else.

Next, while it seems sustainable, it also sounds pretty safe. If your product or service is not that distinct, you must put extra effort to create content that stands out. This applies to all aspects of the marketing strategy, not just in writing content. It’s a crucial principal I learned after reading Purple Cow by Seth Godin (thanks for the book suggestion, Aaron!).

Depending on your product or service, Conversion.ai will generate copy that most consumers keep going back to. Based on the samples it generated, I’d say it really does come up with engaging copy, though it needs editing. If your business must rewrite product descriptions for extensive inventories, Conversion.ai can cut the time in half. It can help automate description rewriting without hiring more writers. That saves money and time, so businesses need fewer writers and editors.

What did I learn? Conversion.ai can make writing and editing faster, yes, especially for low-level content focused on descriptions. It can also inform the strength of your ideas for more creative campaigns. However, it still takes solid direction and creativity to drive good marketing copy forward. That said, it’s only as good as the writer utilizing this app. As a content creator, you cannot rely on it solely for creativity. But as an enhancer, it will significantly help push ideas forward, organize campaigns, and structure engaging copy effectively.

When you use this app, it offers many different features that help create and organize content. It also customizes copy for various media platforms. Beyond rewriting , it even has special brainstorming tools designed to help writers consider various idea angles. This can add more flavor and uniqueness into a campaign.

At the end of the day, what will set your copy apart is the strength of your ideas and your communication strategy. How you customize content for a business is still entirely up to you. AI writing tools like Conversion.ai can only help enhance your content and the ideas behind it. It’s a far cry from creating truly unique concepts for your campaign, but it definitely helps.

Conversion.ai Writing Features & How They Work

This AI writing app comes with plenty of “writing templates” that are customized to help you write with a specific framework or media platform in mind. Currently, Conversion.ai offers 39 different writing templates or content building blocks that deliver results. We’ll provide details for how each one works.

For company or product descriptions, Conversion.ai has a Start Here step by step guide, which says users should alternate between the Product Description and the Content Improver template until they have found the right mix they’re looking for. But for this review, I just focused on how to use the templates for different writing projects. The app comes with video instructions as well as a live training call if you need further assistance on how to use it.

Each template asks you to input a description or what you want to write about. This is limited to 600 characters. Writing the description is the sole basis for how Jarvis will generate ways to write or expand your content. It also helps you brainstorm and structure ideas for an article or campaign.

But as an issue, I find the 600-character limit can hinder reposting the full content generated by the AI back into the template for improvement. Yes, it churns out marketing copy of more than 600 characters. If you want to post the improved copy again, you might have to do this in two batches. In any case, Jarvis can generate as many improved writing samples as you need.

To give you a better idea, here are different Conversion.ai templates and how they work. This is going to take a while, so have your coffee ready.

Long-form Assistant

This is for longer articles, emails, scripts, and stories. It’s also suggested for writing books. It has two modes, a blank document where you can start typing freely and an assistant workflow. The blank document also lets you access the rest of the other writing templates vertically. On the other hand, the long-form assistant workflow is where the app asks you to describe the content you want to create. Consider this carefully. The better you can articulate your topic, the higher quality content Jarvis can help generate.

For the example, suppose I want to write about what it took to finally release Zack Synder’s 2021 Justice League. I want to write this feature article for my film and culture website.

Jarvis asks for a maximum of three keywords. It’s optional, but I presume adding keywords will help Jarvis generate more relevant content. Next, it prompts you to write a working title and start an introductory paragraph. Once you write your initial title, it will generate other title ideas.

For the title, I wrote: The Challenges of Releasing Zach Snyder’s Justice League 2021
It generated the following suggestions:

Jarvis generated a long list of appropriate and catchy titles. I personally liked “The Tumultuous Journey of Zack Snyder’s Justice League 2021,” though I’d shorten it a bit. I also liked “The Darkest, Toughest Production in Film History,” which basically tells audiences how hard it was to produce the version of the film. Though it’s an exaggeration, it can be qualified in the article. The other suggestions with “Behind the Scenes” and “Towards a Better Script” were more specific angles. I like that I could explore those topics too. Generally, I think it’s definitely a great tool to make title writing faster.

So far, so good, right? But when I got to content suggestions, it got a bit messy. It was mainly because the suggested content was too general. It also tended toward suggesting expansions that were incoherent to the main topic. This did not sound very promising. Moreover, the AI added bits of information such as dates and other related information. I had to check if these details were used accurately. In a previous test I did (and even for this example), it completely got a date wrong. So I advise writers to always double check the details suggested by Jarvis.

Take a look below. The top paragraph was the one I wrote, while the ones below are suggested by Jarvis.

Content suggestions from Jarvis:

1) You might not be able to see Zack Snyder’s Justice League on the big screen, but you can catch it online in 2021. It was released digitally by Warner Bros. on November 27th 2020 and we’ve been watching it slowly climb the ranks of IMDB since then. The film had a troubled production between 2016 and 2017 with the script going through major changes before and during shooting. But now that all is said and done, what did people think? Let’s find out!

2) Justice League is a film that was released on November 17, 2017. The movie had been preceded by Batman v Superman: Dawn of Justice and Wonder Woman. It’s also the fifth installment in the DC Extended Universe (DCEU). Despite being generally well-received by critics, it was considered to be a disappointment at the box office. In this blog post, we’ll take you behind the scenes and show you what went wrong with Zack Snyder’s 2021 Justice League film production!

3) Director Zack Snyder’s Justice League film was one of the most anticipated films of 2017. Unfortunately, the film had a troubled production and was not released until 2021. That didn’t stop it from becoming one of the highest-grossing films of all time. What does this have to do with SEO? When you release content on your website, be sure to include keywords that are relevant to your business and industry!

At first glance, the introduction actually looks appealing to Justice League fans. Many people have been anticipating it on the big screen. But upon further reading, compared to the paragraph I wrote, the AI content had so many problems. Besides being too general, it had issues with imprecise details. Though you can argue these problems are small and editable, it adds time to your work. It can even derail you from focusing on your topic.

The first AI suggestion wrote that Snyder Cut was released digitally by Warner Bros. in November 27, 2020. Upon further research, I found no such confirmation of this. However, there was a YouTube video “speculating” it’s release in November 2020. But from the looks of it, this did not pan out. Officially, Zack Snyder’s Justice League was released in March 18, 2021 by HBO Max via streaming platform, according to Rotten Tomatoes. And yes, it has been climbing the ranks since its digital release.

If you’re not careful about fact-checking, you might end up with misleading information. And frankly, I feel as if some of the other suggestions may tend towards fluff. However, what you can do is choose the best suggestions and put them together into one coherent paragraph. The first suggestion ended the introduction with “But now that all is said and done, what did people think? Let’s find out!” While it’s something I want to touch on eventually, it is not the main focus of my introduction. The AI was not sensitive enough to sense this follow up was out of place. I’d rather get to the details of the challenging production. If I use this suggestion, I’ll have to edit it into “Let’s take a look at what it took to deliver the highly anticipated Snyder Cut,” or something to that effect.

The second example, on the other hand, was quite a miss. It started by talking about the 2017 Justice League film. While it’s good to expound on the history of the project started, it got lost in discussing the 2017 version. Worse, it did not transition the topic smoothly into the 2021 Snyder Cut. If I read this introduction, I’d be confused into thinking the article was about the 2017 Justice League. Finally, it awkwardly ended the paragraph with “we’ll take you behind the scenes and show you what went wrong with Zack Snyder’s 2021 Justice League film production!” Besides the wordy sentence, suddenly it’s talking about the 2021 Justice League out of nowhere. I would not phrase the production’s challenges as something that went wrong. That’s unnecessary hype. It’s confusing, and just an example of bad writing. Again, while it can be fixed with editing, I feel better off writing on my own.

Finally, the third example actually started okay. But then it started talking about SEO out of nowhere. I don’t know where that came from or why the AI did that, but I’ll count it as a totally unusable suggestion from the app. I reckon there might be more of those glitches if I generate more content suggestions from Jarvis.

SIDEBAR FROM AARON: COUGH. SEO IS EVERYTHING. HOW DO I REEEEECH DEZ KIDZ

I noticed these were nuances the AI was not able to catch. It’s probably even based on trending articles at the time, which had a tendency towards hype and dated showbiz information. And though the suggestions were interesting, they were mostly too general or against the direction I needed. If the usage of the information is not accurate, imagine what that would mean for health or political articles. But too be fair, it did generate other usable suggestions with less serious edits. It’s worth looking into those.

However, by this time, I felt I was better off writing the feature without the app, at least for this example. I guess it’s really a hit or miss. Even with so many content suggestions, I think you can still end up with inappropriate samples even if you find good ones. But at least you got a good title already. Personally, I’d rather go straight to researching on my own.

Framework Templates

Conversion.ai allows you to write copy based on marketing frameworks that have been used by professionals for years. It’s ideal for brands, products, and services you need to promote. This features includes the following templates:

• AIDA Framework: The AIDA template stands for Attention, Interest, Desire, and Action. This basically divides your copy into sections drawing attention from consumers and piquing their interest. The suggested copy also includes content that appeals to the consumer’s desire, then ends with a call to action.
• PAS Framework: The PAS template is structured by generating copy which highlights the consumer’s Problem, Agitate, and Solution. It’s focused on how a particular product will help solve a consumer’s problem.
• Bridge-After-Bridge Framework: Also known as BAB framework, this copywriting structure revolves around the idea of getting a consumer from a bad place to a better one. It shows the before and after scenario after benefitting from a product.

For this example, I used the AIDA template for an imagined non-invasive weight loss service company. The new company promotes fitness and advocates against fad diets. It performs non-surgical weight loss procedures, such as wraps and thermomagnetic massages.

Again, Jarvis asks for a description. It also requires you to specify the tone of the copy. I placed “friendly” and “professional” under the box. See my input below.

Here’s the first suggestion from Jarvis:

Based on this example, I’d say the AI-generated content is quite engaging. It tried to have a personal touch by letting the customer know they’re here to help. The writing empathizes with consumers who have a hard time losing weight. However, since this is for a new company, the introduction “We have helped thousands of people lose weight and get in shape,” does not apply. So as a writer, I simply have to remove it. This can be replaced with the intent to help more people lose weight and get in shape.

I actually pulled out at least 6 different content suggestions. From these, writers could get the best parts and edit them into one strong copy description. On it’s own, the content would still benefit from a lot of editing. Here are some issues you might encounter while generating copy suggestions:

• Hard Sell Copy. The sample content can be hard sell, even if you specify a professional tone of voice. It tends to use exclamation marks (!) per sample. I believe this depends on the product or service you are writing about. Certain products or services may sell more with the hard sell approach, so the AI suggests this strategy. It may also appear like the “proven” way to communicate to consumers. But if you’re going against this direction, it’s a nuance the AI tool might miss. If your business or client specifically avoids exclamation marks your copy, be ready to make the necessary edits.
• Can be Wordy, Long, Redundant. In terms of style, here’s where you can’t rely on Jarvis to write the entire thing. If you happen to input a long and detailed product description, the AI has a tendency to generate wordy variations of the copy. If you notice, some details are also redundant. In copywriting standards, this needs tightening. Conciseness can be an issue, most notably if you’re not used to brevity. Thus, I believe this tool will best benefit writers and editors who have considerable experience in crafting straightforward copy.

Product Description

The app comes with a special template for creating product descriptions. If you have a large inventory of product information for rewriting, this is the right tool to use. It even comes with an optional language output translation feature, which is available in other templates too.

However, the language feature is limited. I tried putting Thai, Italian, and Japanese and it generated few suggestions, some mixed with English. Same thing with Punjabi and Vietnamese. In other templates, they just keep making English suggestions. Filipino is also not recognized by the AI, which likely means it cannot translate a bunch of other languages. This feature obviously needs development. But it’s not the main feature, so I doubt they’ll do a lot of improvements.

For this example, I used an imagined tire center that offers products and services throughout the U.S. I specifically wrote that it’s the second most affordable tire center in the country. I asked for a professional and witty tone. I’m not at all fluent in Spanish, but I placed Spanish under the output language box.

Below is the first suggested copy in Spanish:

When translated through Google, it reads:

“Don’t think twice, Adam’s Tire Center is your best option because it offers the largest range of products for cars and wagons. Join our satisfied customers and insure your tires with the Road Hazard Warranty service. Call or visit our sales center in Miami, FL, where we are honored to help you.”

Obviously, I can’t comment much on the accuracy of the translation. Though certainly, I have doubts for how writing in another language can capture certain styles and tones. But right now, what I’m more concerned with is the tendency to use superlative descriptions that might not accurately fit the brand. Things like “we offer the largest range of products” should probably be tweaked to “we offer a wide range of products…” If your tire center does not offer the largest inventory, you should not be writing that. It also assumed a specific location, which prompts the writer to include the actual business location (this is a good suggestion). Again, the AI copy would benefit from fine-tuning to make it specific to your product or service.

Now, back to English. Here are three other content samples generated by Jarvis:

The English AI-generated samples are not so bad. But in the last sample, there is a tendency for hard sell terms like “unmatched in quality,” that you need to watch out for. You can get the best parts and put them into one solid brand description. But again, these tend to be wordy and long. It would help to use the Hemingway app or Grammarly to make the descriptions tight and concise.

Content Improver

Using the Content Improver template will help you tweak the product or service descriptions you came up with. To show you how it works, I placed the content I wrote based on the edited tire center descriptions Jarvis generated.

For this example, I placed professional and witty under tone of voice.

Suggested content from Jarvis:

Based on the sample suggestion, I’d say the first two can pretty much stand on their own. These are straightforward copies that address consumer needs with a direct call to action. Though the first one may sound a bit informal, it might fit the type of consumer demographic you are targeting. Finally, the last example gets a bit wordy but can be fixed with a couple of edits. The major issue is the number (555-5555), which the AI mistook for an address.

Marketing Angles

Besides churning out copy suggestions, Conversion.ai has a brainstorming tool. This basically takes your product or service and comes up with various campaign ideas to promote it. If you’re running out of concepts for promotion, Jarvis leverages on your product’s features and strengths. I appreciate that it tried to come up with benefit-driven copy based on the example I put.

For this example, the product I used is a gym management software. It helps gym owners manage activities, schedules, and handle payments. The software aims to run gyms more efficiently.

I personally find the following suggestions helpful in pushing the strengths of a product. I would definitely use this tool for brainstorming ideas. Here’s what Jarvis generated:

Unique Value Propositions

Another intriguing feature is the unique value propositions (UVP ) template. UVP is essentially a clear statement that describes the benefit your product offers. It also captures how you address your customer’s needs and what distinguishes you from the competition.

If you have a product or service, It claims to generate copy that describes your product’s unique advantage in a remarkable way. To test how this works, I used the previous example, which is the gym software. It came up with several statements that emphasized the product’s benefits. See Jarvis’ suggestions below. Personally, I like the idea of software that helps me make more money with less work.

Feature Benefit

The feature benefit template comes up with a list of advantages offered by your product. For this example, the product is a camisole for plus size women. You’ll see how it took the paragraph details and made bulleted benefits based on those features. It’s a useful tool if you want to break down your product’s unique selling points so you can further emphasize them in your campaign.

Persuasive Bullet Points

Another related function is the persuasive bullet points template. This is very similar to the feature benefit template. Personally, I think it’s either you use this or the feature benefit template if you want to highlight product advantages in bullet points. On the other hand, this template doesn’t categorize benefits as emotional or standard advantages.

Copy Headline and Sub-headline Templates

Conversioan.ai also comes with copy headline and sub-headline templates. They claim the AI is “trained with formulas from the world’s best copywriters.” It also guaranteed to create “high-converting headlines” for businesses. At this point, the only way to know if it does have high conversion is to see actual results. Right now, my review can’t prove any of that. But it would be interesting to know from companies who have been using this software for results.

• Perfect Headline: For this template, I used an earlier example that provides non-invasive weight loss services. You’ll see the product description I used, followed by the suggestions made by Jarvis. I specifically liked the headline: Science-based approach to safe, effective fat loss. It’s right concept I was going for.
  
  
• Website Sub-headline: I used the same product description for the sub-headline. I also used the suggested headline generated by Jarvis, which is “Science-based approach to safe, effective fat loss.” Based on Jarvis’ suggestions, I liked the last one, which emphasizes non-invasive slimming. It also tells consumers the procedure is safe. Though it tends to be wordy, I appreciate it provides different ways you can get your message across.
  

Sentence Expander

Another interesting feature is the sentence expander. It claims to make your sentence longer and more creative. I guess it should help you get to another thought if you caught writer’s block. But I’m wary what kind of suggestions it might give. When I tried it, it’s just another way to rewrite your sentence in a longer, more detailed way.

In any case, see my sentence below.

Here’s what Jarvis generated:

I’m actually not a fan of long-winded sentences. However, I do appreciate the extra details added by the AI. I can use these suggestions if I make further edits on them. But realistically, if I’m writing an article, I’d skip this and go directly to what I’m trying to say. That would save me time. If I want to talk about the negative psychological effects of social distancing, I’d write that point per point. My idea of expansion is moving an argument forward, not merely adding more details to what was already said.

Creative Story

Here’s an interesting template I was curious to try. I wonder how Jarvis would develop a two sentence plot. It’s fascinating to see how an AI that uses “proven high conversion data” would suggest story development.

For my example, I took a horror story plot inspired by the Bone Turner from a popular horror podcast called The Magnus Archives. See my plot description and the suggestions made by Jarvis.

Story suggestions by Jarvis:

I have to say, these are very interesting ideas for an introduction. It’s also funny how it used the name “Jonathon,” because the actual name of main character in the Magnus Archives is “Jonathan.” I kind of think that was on purpose, since the AI probably knows the Bone Turner is from a popular online show.

In any case, I particularly liked the second suggestion. With some editing and fine-tuning, you could fix the details to fit the story in your head. On the other hand, I’m wary authors might rely too much on this to bridge plot gaps. While it’s amusing, it’s more compelling to read plot twists and resolutions that are not forced. At this stage, I’m still not convinced the AI can make a story without contrived plot twists.

Email Subject Lines

Besides creative writing tools, Coversion.ai also has templates for email marketing. This feature is made for businesses or individuals who want to promote products and services via email. The app claims to come up with catchy subject lines that draw consumers to open your email. In this example, I used an imaginary cake shop that delivers throughout LA. I thought Jarvis came up with a long list of creative subject lines. These were spot on for the example. Since I am a cake person, I’d likely read this kind of email.

Personal and Company Bio

You can also generate creative personal and company bios through Jarvis. If you’re running a personal blog or website, Jarvis generates personal bios in first person or third person POV, whichever you are more comfortable with. I’m actually pleased with what the AI suggested. It’s a good start, because I find it hard writing about myself.

The example below is not me, of course. I made up Jessica Ackerman as the founder of Mad Cakes in LA.

Here’s what Jarvis generated:

It does sound like a personalized bio. Especially with the detail about cuddling with cats and dogs. Again, I’d edit it to be more particular about details. Other than that, I think it’s a good tool to use.

Next, Jarvis also generates company bios that sound professional. I put a three-sentence info about a company that boosts website conversion for businesses. I was surprised how long the suggestions were. It also presumed the names of clients the company has serviced (TripAdvisor, Yelp, etc.). Again, for particular information like this, it’s important to edit or remove them. Otherwise, you might publish copy with misleading details.

Suggestions from Jarvis:

Real Estate Listing – Residential

You can utilize this template to create creative and descriptive residential listings. It’s helpful for real estate agents and people who are planning to sell their property. The following shows information about a house for sale, followed by listing suggestions by Jarvis.

Suggestions from Jarvis:

It’s interesting how the suggested content appeals to the consumer’s idea of a perfect home. It tries to paint a picture of affluent living just based on the golf course description I supplied. But again, for accuracy, these added details should be edited by the writer.

Templates for Specific Online Platforms

Besides articles and product or brand descriptions, expect Conversion.ai to provide special writing features for online platforms. This includes Facebook, Instagram, YouTube, Google, and Amazon accounts. The AI’s content suggestions are based on posts and ads that have generated high traffic on these platforms. I think this a good tool to use if you want an edge over what already sells.

• Facebook Ad Headline: Makes catchy headlines for FB ads, claims to increase chances of clicks that lead to sales.
• Facebook Ad Primary Text: Claims to generate high converting copy for FB ad’s primary text section.

For the Facebook ad headline, my example is a cake shop that delivers a wide assortment of cakes in Los Angeles. It specifically mentions delivering cakes “within an hour or your money back.” Here’s the example and Jarvis’ suggested content.

AI ad sample headlines:

I must say these sound like fun and friendly FB headlines. I personally would like a last minute dessert. And if I don’t have time to pick up cake, I’d certainly like one delivered. Just not sure about “Get 500 Instagram Followers,” the suggestion is out-of-place. I’d use this tool for a fresh and exciting FB headline.

Here’s the AI sample for Facebook ad primary text:

Based on the FB text sample, the AI instantly suggested to give away free cake. Most of the generated samples headed toward this direction. It didn’t just generate engaging copy, it likely showed you what other cake shops do to draw more customers. I think it’s a great marketing strategy to have promos and free cake. I also like that it suggested catchy hashtags. But again, I’d fix the wordy and adjective-ridden descriptions. With a little editing, the samples should read more smoothly. Other than that, it’s a fast way to come up with social media copy.

Photo Post Captions for Instagram

You can use the app for a company or store’s IG accounts. Here are some samples based on a Mad Cakes Black Chocolate Indulgence photo. If you need ideas for your IG post, this tool can suggest copy that’s simple and straightforward for IG. Depending on your product or service, it suggests content that typically targets your customers base.

Video Writing Templates for YouTube

Next, Conversion.ai offers specialized templates for videos, specifically for platforms such as YouTube. But I also think you can use the content similarly if you’re posting on other video sites. However, the suggestions are based on content with high traffic on YouTube. It includes the following features:

Video Topic Ideas: For brainstorming video content concepts that rank well on YouTube. For example, your initial topic is baking homemade cake. It’s a useful tool for letting you know what people are actually interested in. It gives you an idea what to work on right off the batt. Here are the AI’s suggestions. It mentions concepts for cake baking videos many people look for:

Video Script Outline: Helps make script outlines for any topic. However, this works more suitably for how-to and listicle type videos, not the ones with a narrative. The example below for how to spot aurora borealis or Northern lights. From the AI suggestions, you can choose the best strategies to come up with your own outline. I noticed many suggestions can be too general, besides the more specific ones I posted below. It’s still best to do your own research to make your video content more nuanced and unique. Otherwise, you may just parrot what other content creators have already done.

Video Titles: Like the other templates, there’s also a video title feature. As an example, many users on YouTube like to create content about shows or films. Suppose you want to write a feature about the anime Attack on Titan. For the suggestion, the AI actually came up with pretty awesome titles and topics you can start researching on. While this is based on high-traffic fan search, what you can do is watch what’s already there. This will help you come up with more unique insights about the show that has not been tackled. Again, try to focus on what would set your content apart from what’s already there.

Blog Post Templates

Conversion.ai provides templates that help you conceptual blog posts for your brands. It has tools to help you brainstorm topic ideas and outline your content. These suggestions are all based on high ranking topics on Google. It also comes with features that help compose blog post introductions and conclusions.

• Blog Post Topic Ideas
• Blog Post Outline
• Blog Post Intro Paragraph
• Blog Post Conclusion Paragraph

For the example, let’s focus on the topic template. I used the earlier example, Best Shape, which is an imaginary non-invasive weight loss service. See the AI’s suggestions below.

Jarvis’s results show topics that trend around non-invasive weight loss methods. Trending topics around your market is always good to know. For ideas on blog topics, I think Conversion.ai will really be a useful tool. If you need help structuring your outline, I think it’s worth using it especially if you’re having trouble with organization.

Personally, after getting different topics, you can start writing your post without the app. You won’t need it especially if you already have an idea what to write. It’s still better to do proper research than rely on the app to add information on your post. As you’ve noticed, it has a tendency to supply the incorrect information, which you must diligently edit.

Would I Recommend This Software?

After crash testing Conversion.ai, I would recommend this tool to agencies or individuals that deal with extensive online copywriting and product rewrites. They will benefit the most by eliminating the time-consuming process of doing product descriptions. I would also recommend it for businesses that run social media campaigns, including Google and Amazon ads. This will help generate and organize copy ideas faster, especially if you have a lot of products and services to promote. And because the AI suggestions are based on high-ranking topics, you have a better idea of what your client base is also looking for. It can also enhance messaging concepts and help brainstorm new campaign ideas for a product or brand. Just remember to always edit the content suggestions.

On the other hand, I would not recommend this app for long-form writing. I do not think it is ideal for any writing that requires a lot of research. Because the AI suggestions tend towards incorrect information, you’re better off researching current data on your own. It’s an interesting tool for wring stories, but I also worry authors might be too reliant on the app for plot ideas. There is a difference between carefully worded prose versus long-winded sentences composed by this app. Human writing is still more precise with expression, which the AI has yet to learn.

While it’s a good tool to have, the bottom line is, you still need to edit your content. It will help you structure your outline and compose your post. However, the impetus for writing and the direction it will take is still on you, the writer. My verdict? AI writing technology won’t fully replace humans anytime soon.

Background / Intro

One of my longtime friends who was Internet marketing long before I was hit me up on Skype about a week ago praising Conversion.ai. I have to think long and hard about any other time he has really pitched or recommended something like that & really I just can’t think of any other time where he did that. The following day my wife Giovanna mentioned something to me and I was like “oh you should check out this thing my buddy recommended yesterday” and then I looked and realized they were both talking about the same thing. :D

I have a general heuristic that if people I trust recommend things I put them near the top of the “to do” list and if multiple people I trust do that I pull out the credit card and run at it.

Unfortunately I have been a bit burned out recently and launched a new site which I have put a few hundred hours into, so I haven’t had the time to do too much testing, BUT I have a writer who works for me who has a master’s degree in writing, and figured she could do a solid review. And she did. :D

She is maybe even a bit more cynical than I am (is that even possible?) and a certified cat lady who loves writing, reading, poetry and is more into a soft sell versus aggressive sales.

Full disclosure…the above link and the one at the end of this post are affiliate links, but they had zero impact on the shape or format of the review. The reviewer was completely disconnected from the affiliate program and I pulled out my credit card to pay for the software for her to test it out.

With that tiny bit of a micro-introduction, the rest of the post from here on out is hers. I may have made a couple minor edits for clarity (and probably introduced a few errors she will choke me for. :D) but otherwise the rest of this post is all her …

An In-depth Review of the Conversion.ai Writing Software

Considering the possibilities of artificial intelligence (AI), we picture robots doing tasks autonomously like humans. With a computer’s brain power, productivity is accelerated significantly. We also expect AI programs to have the capability to evolve intelligently the longer they are used. These types of AI employ “machine learning,” or deep learning to solve problems.

AI technology can be leveraged by various industries, especially with writing. Recently, I learned about the Conversion.ai copywriting tool. It uses machine learning which claims to write “high converting copy” for websites, ads, landing pages, emails, etc. The software is geared towards writers, marketers, entrepreneurs, and agencies that benefit from creating engaging and effective copy. To date, companies such as Hubspot, Shopify, and Salesforce are known to use the software. Currently, it’s offering a 7-day free trial with 20,000-word credits.

To give you the lowdown on Conversion.ai, I wrote an in-depth review of how this software works. I’ll go through its various features and show examples of how I used them. I’ll include the advantages of using Conversion.ai’s Jarvis (that’s what it’s called) in writing scenarios. More importantly, I’ll discuss challenges and specific limitations this tool might present.

Assistance in Creating High Conversion Copy

As a writer doing web copy for 10 years, including the time I took a post-grad creative writing degree, I grabbed the opportunity to try this AI software. For starters, it struck me how Conversion.ai claims to provide “high converting copy” for increased conversion and higher ROI. Such claims are a tall order. If you’ve been in the marketing or sales industry, you’d know conversion depends on so many other factors, such as the quality of the actual product, customer support, price, etc. It’s not just how well copy is written, though it’s a vital part. But anyway, upon more research, I learned the app generates copy based on proven high conversion sales and marketing messages.

To be honest, I have mixed feelings about this conversion strategy. I believe it’s a double-edged sword. This is not to undermine facts or measurable data. Basing content creation on “proven content” means you’re likely using the same phrases, techniques, and styles already used by successful competitors. This serves as a jumping board for ideas of course, so you know what’s already there. However, it can be an echo chamber. Marketers must not forget that execution must still be fresh. Otherwise, you’ll sound like everyone else.

Next, while it seems sustainable, it also sounds pretty safe. If your product or service is not that distinct, you must put extra effort to create content that stands out. This applies to all aspects of the marketing strategy, not just in writing content. It’s a crucial principal I learned after reading Purple Cow by Seth Godin (thanks for the book suggestion, Aaron!).

Depending on your product or service, Conversion.ai will generate copy that most consumers keep going back to. Based on the samples it generated, I’d say it really does come up with engaging copy, though it needs editing. If your business must rewrite product descriptions for extensive inventories, Conversion.ai can cut the time in half. It can help automate description rewriting without hiring more writers. That saves money and time, so businesses need fewer writers and editors.

What did I learn? Conversion.ai can make writing and editing faster, yes, especially for low-level content focused on descriptions. It can also inform the strength of your ideas for more creative campaigns. However, it still takes solid direction and creativity to drive good marketing copy forward. That said, it’s only as good as the writer utilizing this app. As a content creator, you cannot rely on it solely for creativity. But as an enhancer, it will significantly help push ideas forward, organize campaigns, and structure engaging copy effectively.

When you use this app, it offers many different features that help create and organize content. It also customizes copy for various media platforms. Beyond rewriting , it even has special brainstorming tools designed to help writers consider various idea angles. This can add more flavor and uniqueness into a campaign.

At the end of the day, what will set your copy apart is the strength of your ideas and your communication strategy. How you customize content for a business is still entirely up to you. AI writing tools like Conversion.ai can only help enhance your content and the ideas behind it. It’s a far cry from creating truly unique concepts for your campaign, but it definitely helps.

Conversion.ai Writing Features & How They Work

This AI writing app comes with plenty of “writing templates” that are customized to help you write with a specific framework or media platform in mind. Currently, Conversion.ai offers 39 different writing templates or content building blocks that deliver results. We’ll provide details for how each one works.

For company or product descriptions, Conversion.ai has a Start Here step by step guide, which says users should alternate between the Product Description and the Content Improver template until they have found the right mix they’re looking for. But for this review, I just focused on how to use the templates for different writing projects. The app comes with video instructions as well as a live training call if you need further assistance on how to use it.

Each template asks you to input a description or what you want to write about. This is limited to 600 characters. Writing the description is the sole basis for how Jarvis will generate ways to write or expand your content. It also helps you brainstorm and structure ideas for an article or campaign.

But as an issue, I find the 600-character limit can hinder reposting the full content generated by the AI back into the template for improvement. Yes, it churns out marketing copy of more than 600 characters. If you want to post the improved copy again, you might have to do this in two batches. In any case, Jarvis can generate as many improved writing samples as you need.

To give you a better idea, here are different Conversion.ai templates and how they work. This is going to take a while, so have your coffee ready.

Long-form Assistant

This is for longer articles, emails, scripts, and stories. It’s also suggested for writing books. It has two modes, a blank document where you can start typing freely and an assistant workflow. The blank document also lets you access the rest of the other writing templates vertically. On the other hand, the long-form assistant workflow is where the app asks you to describe the content you want to create. Consider this carefully. The better you can articulate your topic, the higher quality content Jarvis can help generate.

For the example, suppose I want to write about what it took to finally release Zack Synder’s 2021 Justice League. I want to write this feature article for my film and culture website.

Jarvis asks for a maximum of three keywords. It’s optional, but I presume adding keywords will help Jarvis generate more relevant content. Next, it prompts you to write a working title and start an introductory paragraph. Once you write your initial title, it will generate other title ideas.

For the title, I wrote: The Challenges of Releasing Zach Snyder’s Justice League 2021
It generated the following suggestions:

Jarvis generated a long list of appropriate and catchy titles. I personally liked “The Tumultuous Journey of Zack Snyder’s Justice League 2021,” though I’d shorten it a bit. I also liked “The Darkest, Toughest Production in Film History,” which basically tells audiences how hard it was to produce the version of the film. Though it’s an exaggeration, it can be qualified in the article. The other suggestions with “Behind the Scenes” and “Towards a Better Script” were more specific angles. I like that I could explore those topics too. Generally, I think it’s definitely a great tool to make title writing faster.

So far, so good, right? But when I got to content suggestions, it got a bit messy. It was mainly because the suggested content was too general. It also tended toward suggesting expansions that were incoherent to the main topic. This did not sound very promising. Moreover, the AI added bits of information such as dates and other related information. I had to check if these details were used accurately. In a previous test I did (and even for this example), it completely got a date wrong. So I advise writers to always double check the details suggested by Jarvis.

Take a look below. The top paragraph was the one I wrote, while the ones below are suggested by Jarvis.

Content suggestions from Jarvis:

1) You might not be able to see Zack Snyder’s Justice League on the big screen, but you can catch it online in 2021. It was released digitally by Warner Bros. on November 27th 2020 and we’ve been watching it slowly climb the ranks of IMDB since then. The film had a troubled production between 2016 and 2017 with the script going through major changes before and during shooting. But now that all is said and done, what did people think? Let’s find out!

2) Justice League is a film that was released on November 17, 2017. The movie had been preceded by Batman v Superman: Dawn of Justice and Wonder Woman. It’s also the fifth installment in the DC Extended Universe (DCEU). Despite being generally well-received by critics, it was considered to be a disappointment at the box office. In this blog post, we’ll take you behind the scenes and show you what went wrong with Zack Snyder’s 2021 Justice League film production!

3) Director Zack Snyder’s Justice League film was one of the most anticipated films of 2017. Unfortunately, the film had a troubled production and was not released until 2021. That didn’t stop it from becoming one of the highest-grossing films of all time. What does this have to do with SEO? When you release content on your website, be sure to include keywords that are relevant to your business and industry!

At first glance, the introduction actually looks appealing to Justice League fans. Many people have been anticipating it on the big screen. But upon further reading, compared to the paragraph I wrote, the AI content had so many problems. Besides being too general, it had issues with imprecise details. Though you can argue these problems are small and editable, it adds time to your work. It can even derail you from focusing on your topic.

The first AI suggestion wrote that Snyder Cut was released digitally by Warner Bros. in November 27, 2020. Upon further research, I found no such confirmation of this. However, there was a YouTube video “speculating” it’s release in November 2020. But from the looks of it, this did not pan out. Officially, Zack Snyder’s Justice League was released in March 18, 2021 by HBO Max via streaming platform, according to Rotten Tomatoes. And yes, it has been climbing the ranks since its digital release.

If you’re not careful about fact-checking, you might end up with misleading information. And frankly, I feel as if some of the other suggestions may tend towards fluff. However, what you can do is choose the best suggestions and put them together into one coherent paragraph. The first suggestion ended the introduction with “But now that all is said and done, what did people think? Let’s find out!” While it’s something I want to touch on eventually, it is not the main focus of my introduction. The AI was not sensitive enough to sense this follow up was out of place. I’d rather get to the details of the challenging production. If I use this suggestion, I’ll have to edit it into “Let’s take a look at what it took to deliver the highly anticipated Snyder Cut,” or something to that effect.

The second example, on the other hand, was quite a miss. It started by talking about the 2017 Justice League film. While it’s good to expound on the history of the project started, it got lost in discussing the 2017 version. Worse, it did not transition the topic smoothly into the 2021 Snyder Cut. If I read this introduction, I’d be confused into thinking the article was about the 2017 Justice League. Finally, it awkwardly ended the paragraph with “we’ll take you behind the scenes and show you what went wrong with Zack Snyder’s 2021 Justice League film production!” Besides the wordy sentence, suddenly it’s talking about the 2021 Justice League out of nowhere. I would not phrase the production’s challenges as something that went wrong. That’s unnecessary hype. It’s confusing, and just an example of bad writing. Again, while it can be fixed with editing, I feel better off writing on my own.

Finally, the third example actually started okay. But then it started talking about SEO out of nowhere. I don’t know where that came from or why the AI did that, but I’ll count it as a totally unusable suggestion from the app. I reckon there might be more of those glitches if I generate more content suggestions from Jarvis.

SIDEBAR FROM AARON: COUGH. SEO IS EVERYTHING. HOW DO I REEEEECH DEZ KIDZ

I noticed these were nuances the AI was not able to catch. It’s probably even based on trending articles at the time, which had a tendency towards hype and dated showbiz information. And though the suggestions were interesting, they were mostly too general or against the direction I needed. If the usage of the information is not accurate, imagine what that would mean for health or political articles. But too be fair, it did generate other usable suggestions with less serious edits. It’s worth looking into those.

However, by this time, I felt I was better off writing the feature without the app, at least for this example. I guess it’s really a hit or miss. Even with so many content suggestions, I think you can still end up with inappropriate samples even if you find good ones. But at least you got a good title already. Personally, I’d rather go straight to researching on my own.

Framework Templates

Conversion.ai allows you to write copy based on marketing frameworks that have been used by professionals for years. It’s ideal for brands, products, and services you need to promote. This features includes the following templates:

• AIDA Framework: The AIDA template stands for Attention, Interest, Desire, and Action. This basically divides your copy into sections drawing attention from consumers and piquing their interest. The suggested copy also includes content that appeals to the consumer’s desire, then ends with a call to action.
• PAS Framework: The PAS template is structured by generating copy which highlights the consumer’s Problem, Agitate, and Solution. It’s focused on how a particular product will help solve a consumer’s problem.
• Bridge-After-Bridge Framework: Also known as BAB framework, this copywriting structure revolves around the idea of getting a consumer from a bad place to a better one. It shows the before and after scenario after benefitting from a product.

For this example, I used the AIDA template for an imagined non-invasive weight loss service company. The new company promotes fitness and advocates against fad diets. It performs non-surgical weight loss procedures, such as wraps and thermomagnetic massages.

Again, Jarvis asks for a description. It also requires you to specify the tone of the copy. I placed “friendly” and “professional” under the box. See my input below.

Here’s the first suggestion from Jarvis:

Based on this example, I’d say the AI-generated content is quite engaging. It tried to have a personal touch by letting the customer know they’re here to help. The writing empathizes with consumers who have a hard time losing weight. However, since this is for a new company, the introduction “We have helped thousands of people lose weight and get in shape,” does not apply. So as a writer, I simply have to remove it. This can be replaced with the intent to help more people lose weight and get in shape.

I actually pulled out at least 6 different content suggestions. From these, writers could get the best parts and edit them into one strong copy description. On it’s own, the content would still benefit from a lot of editing. Here are some issues you might encounter while generating copy suggestions:

• Hard Sell Copy. The sample content can be hard sell, even if you specify a professional tone of voice. It tends to use exclamation marks (!) per sample. I believe this depends on the product or service you are writing about. Certain products or services may sell more with the hard sell approach, so the AI suggests this strategy. It may also appear like the “proven” way to communicate to consumers. But if you’re going against this direction, it’s a nuance the AI tool might miss. If your business or client specifically avoids exclamation marks your copy, be ready to make the necessary edits.
• Can be Wordy, Long, Redundant. In terms of style, here’s where you can’t rely on Jarvis to write the entire thing. If you happen to input a long and detailed product description, the AI has a tendency to generate wordy variations of the copy. If you notice, some details are also redundant. In copywriting standards, this needs tightening. Conciseness can be an issue, most notably if you’re not used to brevity. Thus, I believe this tool will best benefit writers and editors who have considerable experience in crafting straightforward copy.

Product Description

The app comes with a special template for creating product descriptions. If you have a large inventory of product information for rewriting, this is the right tool to use. It even comes with an optional language output translation feature, which is available in other templates too.

However, the language feature is limited. I tried putting Thai, Italian, and Japanese and it generated few suggestions, some mixed with English. Same thing with Punjabi and Vietnamese. In other templates, they just keep making English suggestions. Filipino is also not recognized by the AI, which likely means it cannot translate a bunch of other languages. This feature obviously needs development. But it’s not the main feature, so I doubt they’ll do a lot of improvements.

For this example, I used an imagined tire center that offers products and services throughout the U.S. I specifically wrote that it’s the second most affordable tire center in the country. I asked for a professional and witty tone. I’m not at all fluent in Spanish, but I placed Spanish under the output language box.

Below is the first suggested copy in Spanish:

When translated through Google, it reads:

“Don’t think twice, Adam’s Tire Center is your best option because it offers the largest range of products for cars and wagons. Join our satisfied customers and insure your tires with the Road Hazard Warranty service. Call or visit our sales center in Miami, FL, where we are honored to help you.”

Obviously, I can’t comment much on the accuracy of the translation. Though certainly, I have doubts for how writing in another language can capture certain styles and tones. But right now, what I’m more concerned with is the tendency to use superlative descriptions that might not accurately fit the brand. Things like “we offer the largest range of products” should probably be tweaked to “we offer a wide range of products…” If your tire center does not offer the largest inventory, you should not be writing that. It also assumed a specific location, which prompts the writer to include the actual business location (this is a good suggestion). Again, the AI copy would benefit from fine-tuning to make it specific to your product or service.

Now, back to English. Here are three other content samples generated by Jarvis:

The English AI-generated samples are not so bad. But in the last sample, there is a tendency for hard sell terms like “unmatched in quality,” that you need to watch out for. You can get the best parts and put them into one solid brand description. But again, these tend to be wordy and long. It would help to use the Hemingway app or Grammarly to make the descriptions tight and concise.

Content Improver

Using the Content Improver template will help you tweak the product or service descriptions you came up with. To show you how it works, I placed the content I wrote based on the edited tire center descriptions Jarvis generated.

For this example, I placed professional and witty under tone of voice.

Suggested content from Jarvis:

Based on the sample suggestion, I’d say the first two can pretty much stand on their own. These are straightforward copies that address consumer needs with a direct call to action. Though the first one may sound a bit informal, it might fit the type of consumer demographic you are targeting. Finally, the last example gets a bit wordy but can be fixed with a couple of edits. The major issue is the number (555-5555), which the AI mistook for an address.

Marketing Angles

Besides churning out copy suggestions, Conversion.ai has a brainstorming tool. This basically takes your product or service and comes up with various campaign ideas to promote it. If you’re running out of concepts for promotion, Jarvis leverages on your product’s features and strengths. I appreciate that it tried to come up with benefit-driven copy based on the example I put.

For this example, the product I used is a gym management software. It helps gym owners manage activities, schedules, and handle payments. The software aims to run gyms more efficiently.

I personally find the following suggestions helpful in pushing the strengths of a product. I would definitely use this tool for brainstorming ideas. Here’s what Jarvis generated:

Unique Value Propositions

Another intriguing feature is the unique value propositions (UVP ) template. UVP is essentially a clear statement that describes the benefit your product offers. It also captures how you address your customer’s needs and what distinguishes you from the competition.

If you have a product or service, It claims to generate copy that describes your product’s unique advantage in a remarkable way. To test how this works, I used the previous example, which is the gym software. It came up with several statements that emphasized the product’s benefits. See Jarvis’ suggestions below. Personally, I like the idea of software that helps me make more money with less work.

Feature Benefit

The feature benefit template comes up with a list of advantages offered by your product. For this example, the product is a camisole for plus size women. You’ll see how it took the paragraph details and made bulleted benefits based on those features. It’s a useful tool if you want to break down your product’s unique selling points so you can further emphasize them in your campaign.

Persuasive Bullet Points

Another related function is the persuasive bullet points template. This is very similar to the feature benefit template. Personally, I think it’s either you use this or the feature benefit template if you want to highlight product advantages in bullet points. On the other hand, this template doesn’t categorize benefits as emotional or standard advantages.

Copy Headline and Sub-headline Templates

Conversioan.ai also comes with copy headline and sub-headline templates. They claim the AI is “trained with formulas from the world’s best copywriters.” It also guaranteed to create “high-converting headlines” for businesses. At this point, the only way to know if it does have high conversion is to see actual results. Right now, my review can’t prove any of that. But it would be interesting to know from companies who have been using this software for results.

• Perfect Headline: For this template, I used an earlier example that provides non-invasive weight loss services. You’ll see the product description I used, followed by the suggestions made by Jarvis. I specifically liked the headline: Science-based approach to safe, effective fat loss. It’s right concept I was going for.
  
  
• Website Sub-headline: I used the same product description for the sub-headline. I also used the suggested headline generated by Jarvis, which is “Science-based approach to safe, effective fat loss.” Based on Jarvis’ suggestions, I liked the last one, which emphasizes non-invasive slimming. It also tells consumers the procedure is safe. Though it tends to be wordy, I appreciate it provides different ways you can get your message across.
  

Sentence Expander

Another interesting feature is the sentence expander. It claims to make your sentence longer and more creative. I guess it should help you get to another thought if you caught writer’s block. But I’m wary what kind of suggestions it might give. When I tried it, it’s just another way to rewrite your sentence in a longer, more detailed way.

In any case, see my sentence below.

Here’s what Jarvis generated:

I’m actually not a fan of long-winded sentences. However, I do appreciate the extra details added by the AI. I can use these suggestions if I make further edits on them. But realistically, if I’m writing an article, I’d skip this and go directly to what I’m trying to say. That would save me time. If I want to talk about the negative psychological effects of social distancing, I’d write that point per point. My idea of expansion is moving an argument forward, not merely adding more details to what was already said.

Creative Story

Here’s an interesting template I was curious to try. I wonder how Jarvis would develop a two sentence plot. It’s fascinating to see how an AI that uses “proven high conversion data” would suggest story development.

For my example, I took a horror story plot inspired by the Bone Turner from a popular horror podcast called The Magnus Archives. See my plot description and the suggestions made by Jarvis.

Story suggestions by Jarvis:

I have to say, these are very interesting ideas for an introduction. It’s also funny how it used the name “Jonathon,” because the actual name of main character in the Magnus Archives is “Jonathan.” I kind of think that was on purpose, since the AI probably knows the Bone Turner is from a popular online show.

In any case, I particularly liked the second suggestion. With some editing and fine-tuning, you could fix the details to fit the story in your head. On the other hand, I’m wary authors might rely too much on this to bridge plot gaps. While it’s amusing, it’s more compelling to read plot twists and resolutions that are not forced. At this stage, I’m still not convinced the AI can make a story without contrived plot twists.

Email Subject Lines

Besides creative writing tools, Coversion.ai also has templates for email marketing. This feature is made for businesses or individuals who want to promote products and services via email. The app claims to come up with catchy subject lines that draw consumers to open your email. In this example, I used an imaginary cake shop that delivers throughout LA. I thought Jarvis came up with a long list of creative subject lines. These were spot on for the example. Since I am a cake person, I’d likely read this kind of email.

Personal and Company Bio

You can also generate creative personal and company bios through Jarvis. If you’re running a personal blog or website, Jarvis generates personal bios in first person or third person POV, whichever you are more comfortable with. I’m actually pleased with what the AI suggested. It’s a good start, because I find it hard writing about myself.

The example below is not me, of course. I made up Jessica Ackerman as the founder of Mad Cakes in LA.

Here’s what Jarvis generated:

It does sound like a personalized bio. Especially with the detail about cuddling with cats and dogs. Again, I’d edit it to be more particular about details. Other than that, I think it’s a good tool to use.

Next, Jarvis also generates company bios that sound professional. I put a three-sentence info about a company that boosts website conversion for businesses. I was surprised how long the suggestions were. It also presumed the names of clients the company has serviced (TripAdvisor, Yelp, etc.). Again, for particular information like this, it’s important to edit or remove them. Otherwise, you might publish copy with misleading details.

Suggestions from Jarvis:

Real Estate Listing – Residential

You can utilize this template to create creative and descriptive residential listings. It’s helpful for real estate agents and people who are planning to sell their property. The following shows information about a house for sale, followed by listing suggestions by Jarvis.

Suggestions from Jarvis:

It’s interesting how the suggested content appeals to the consumer’s idea of a perfect home. It tries to paint a picture of affluent living just based on the golf course description I supplied. But again, for accuracy, these added details should be edited by the writer.

Templates for Specific Online Platforms

Besides articles and product or brand descriptions, expect Conversion.ai to provide special writing features for online platforms. This includes Facebook, Instagram, YouTube, Google, and Amazon accounts. The AI’s content suggestions are based on posts and ads that have generated high traffic on these platforms. I think this a good tool to use if you want an edge over what already sells.

• Facebook Ad Headline: Makes catchy headlines for FB ads, claims to increase chances of clicks that lead to sales.
• Facebook Ad Primary Text: Claims to generate high converting copy for FB ad’s primary text section.

For the Facebook ad headline, my example is a cake shop that delivers a wide assortment of cakes in Los Angeles. It specifically mentions delivering cakes “within an hour or your money back.” Here’s the example and Jarvis’ suggested content.

AI ad sample headlines:

I must say these sound like fun and friendly FB headlines. I personally would like a last minute dessert. And if I don’t have time to pick up cake, I’d certainly like one delivered. Just not sure about “Get 500 Instagram Followers,” the suggestion is out-of-place. I’d use this tool for a fresh and exciting FB headline.

Here’s the AI sample for Facebook ad primary text:

Based on the FB text sample, the AI instantly suggested to give away free cake. Most of the generated samples headed toward this direction. It didn’t just generate engaging copy, it likely showed you what other cake shops do to draw more customers. I think it’s a great marketing strategy to have promos and free cake. I also like that it suggested catchy hashtags. But again, I’d fix the wordy and adjective-ridden descriptions. With a little editing, the samples should read more smoothly. Other than that, it’s a fast way to come up with social media copy.

Photo Post Captions for Instagram

You can use the app for a company or store’s IG accounts. Here are some samples based on a Mad Cakes Black Chocolate Indulgence photo. If you need ideas for your IG post, this tool can suggest copy that’s simple and straightforward for IG. Depending on your product or service, it suggests content that typically targets your customers base.

Video Writing Templates for YouTube

Next, Conversion.ai offers specialized templates for videos, specifically for platforms such as YouTube. But I also think you can use the content similarly if you’re posting on other video sites. However, the suggestions are based on content with high traffic on YouTube. It includes the following features:

Video Topic Ideas: For brainstorming video content concepts that rank well on YouTube. For example, your initial topic is baking homemade cake. It’s a useful tool for letting you know what people are actually interested in. It gives you an idea what to work on right off the batt. Here are the AI’s suggestions. It mentions concepts for cake baking videos many people look for:

Video Script Outline: Helps make script outlines for any topic. However, this works more suitably for how-to and listicle type videos, not the ones with a narrative. The example below for how to spot aurora borealis or Northern lights. From the AI suggestions, you can choose the best strategies to come up with your own outline. I noticed many suggestions can be too general, besides the more specific ones I posted below. It’s still best to do your own research to make your video content more nuanced and unique. Otherwise, you may just parrot what other content creators have already done.

Video Titles: Like the other templates, there’s also a video title feature. As an example, many users on YouTube like to create content about shows or films. Suppose you want to write a feature about the anime Attack on Titan. For the suggestion, the AI actually came up with pretty awesome titles and topics you can start researching on. While this is based on high-traffic fan search, what you can do is watch what’s already there. This will help you come up with more unique insights about the show that has not been tackled. Again, try to focus on what would set your content apart from what’s already there.

Blog Post Templates

Conversion.ai provides templates that help you conceptual blog posts for your brands. It has tools to help you brainstorm topic ideas and outline your content. These suggestions are all based on high ranking topics on Google. It also comes with features that help compose blog post introductions and conclusions.

• Blog Post Topic Ideas
• Blog Post Outline
• Blog Post Intro Paragraph
• Blog Post Conclusion Paragraph

For the example, let’s focus on the topic template. I used the earlier example, Best Shape, which is an imaginary non-invasive weight loss service. See the AI’s suggestions below.

Jarvis’s results show topics that trend around non-invasive weight loss methods. Trending topics around your market is always good to know. For ideas on blog topics, I think Conversion.ai will really be a useful tool. If you need help structuring your outline, I think it’s worth using it especially if you’re having trouble with organization.

Personally, after getting different topics, you can start writing your post without the app. You won’t need it especially if you already have an idea what to write. It’s still better to do proper research than rely on the app to add information on your post. As you’ve noticed, it has a tendency to supply the incorrect information, which you must diligently edit.

Would I Recommend This Software?

After crash testing Conversion.ai, I would recommend this tool to agencies or individuals that deal with extensive online copywriting and product rewrites. They will benefit the most by eliminating the time-consuming process of doing product descriptions. I would also recommend it for businesses that run social media campaigns, including Google and Amazon ads. This will help generate and organize copy ideas faster, especially if you have a lot of products and services to promote. And because the AI suggestions are based on high-ranking topics, you have a better idea of what your client base is also looking for. It can also enhance messaging concepts and help brainstorm new campaign ideas for a product or brand. Just remember to always edit the content suggestions.

On the other hand, I would not recommend this app for long-form writing. I do not think it is ideal for any writing that requires a lot of research. Because the AI suggestions tend towards incorrect information, you’re better off researching current data on your own. It’s an interesting tool for wring stories, but I also worry authors might be too reliant on the app for plot ideas. There is a difference between carefully worded prose versus long-winded sentences composed by this app. Human writing is still more precise with expression, which the AI has yet to learn.

While it’s a good tool to have, the bottom line is, you still need to edit your content. It will help you structure your outline and compose your post. However, the impetus for writing and the direction it will take is still on you, the writer. My verdict? AI writing technology won’t fully replace humans anytime soon.

On Wednesday SEMrush priced their IPO at $14 a share & listed Thursday.

There have been many marketing and online advertising companies which are publicly traded, but few that were so focused specifically on SEO while having a sizeable market cap. According to this SeekingAlpha post at the IPO price SEMrush had a valuation of about $1.95 to $1.99 billion. For comparison sake, here are some other companies & valuations.

• Facebook acquired Instagram for $1 billion.
• Google acquired YouTube for $1.65 billion.
• Yelp trades at around a $2.9 billion market cap.
• Yahoo! was acquired by Verizon for $4.48 billion.
• Hubspot has a market cap of around $20.4 billion.

A couple years ago Gannett bought AdWords reseller WordStream. A few years before that they bought ReachLocal. The Hearst publishing empire also bought iCrossing long ago. Marin Software remains publicly traded, but they are only valued at about $20 million.

Newspapers reselling Google AdWords ads isn’t really SEO though. Beyond those sorts of deals, many of the publicly traded SEO stuff has been only tangentially relevant to SEO, or crap.

There are some quality category-leading publishers which use SEO as a means of distribution but are not necessarily an SEO service provider like TripAdvisor, BankRate, and WebMD. Over time many of these sorts of companies have been gobbled up by Red Ventures or various private equity firms. Zillow, Yelp and TripAdvisor are some of the few examples which still exist as independent companies.

So that puts most of the publicly traded SEO stuff in one of the following categories…

• small scale – does anyone other than Andy Beal & Mike Grehan still remember KeywordRanking / WebSourced / Think Interactive / MarketSmart Interactive?
• hope and nope – sites like Business.com were repeatedly acquired but never really gained lasting relevance.
• affiliate networks – which reliant on partners with SEO traffic like Quinstreet & Commission Junction. many affiliate networks were hit hard as the barrier to entry in SEO increased over the years. Quinstreet is doing well in some verticals but sold their education division to Education Dynamics for $20 million. CJ was part of the Publicis Groupe acquisition of Epsilon.
• pump and dump scams – Demand Media, owner of eHow, which later rebranded as Leaf Group & still trades at a small fraction of their IPO price.

The one lasting counter-example to the above is Barry Diller’s IAC. His innovation ecosystem is surreal. Across time & across markets he is the best creator of vertical leading properties later spun off as their own companies. He’s owned Expedia, TripAdvisor, LendingTree, HomeAdvisor, Match.com, TicketMaster and so many other category leaders. His buying of Ask.com did not pan out as well as hoped as web browsers turned the address bar into a search box, his ability to differentiate the service went away after they shut down the engine in 2008, he was locked out of mobile search marketshare by default placement contracts & Google pushes back against extension bundling, but just about everything else he touched turned to gold. A lot of their current market cap is their ownership of Vimeo, which by itself is valued at $6 billion.

What is the most recent big bet for Barry Diller? MGM. Last August he bet $1 billion on the growth of online gambling. And he was willing to bet another billion to help them acquire Entain:

IAC has to date invested approximately US$1 billion in MGM with an initial investment thesis of accelerating MGM’s penetration of the $450 billion global gaming market. IAC notes in its letter of intent that IAC continues to strongly support this objective for MGM whether or not a transaction with Entain is consummated.

Barry Diller not accurately projects future trends, but he also has the ability to rehab broken companies past their due dates.

The New York Times bought About.com for $410 million in 2005 & did little with it as its relevance declined over time as its content got stale, Wikipedia grew and search engines kept putting more scraped content in the search results. The relentless growth of Wikipedia and Google launching “universal search” in 2007 diminished the value of About.com even as web usage was exploding.

IAC bought About.com from the New York Times for $300 million in August of 2012. They tried to grow it through improving usability, content depth and content quality but ultimately decided to blow it up.

They were bold enough to break it into vertical category branded sites. They’ve done amazingly well with it and in many cases they rank 2, 3, 4 times in the SERPs with different properties like TheSpruce, TheBalance, Investopedia, etc. As newspapers chains keep consolidating or going under, IAC is one of the few constant “always wins” online publishers.

At its peak TheBalance was getting roughly 2/3 the traffic About.com generated.

Part of the decline in the chart there was perhaps a Panda hit, but the reason traffic never fully recovered is they broke some of these category sites into niche sites using sub-brands.

All the above search traffic estimate trend charts are from SEMrush. :)

I could do a blog post titled 1001 ways to use SEMrush if you would like me to, though I haven’t yet as I already have affiliate ads for them here and don’t want to come across as a shill by overpromoting a tool I love & use regularly.

I tend to sort of “not get” a lot of SaaS stocks in terms of prices and multiples, though they seem to go to infinity and beyond more often than not. I actually like SEMrush more than most though & think they’ll do well for years to come. I get the sense with both them and Ahrefs that they were started by programmers who learned marketing rather than started by marketers who cobbled together offerings which they though would sell. If you ever have feedback on ways to improve SEMrush they are fast at integrating it, or at least were in the past whenever I had feedback.

When SEMrush released their S-1 Dan Barker did a quick analysis on Twitter.

Some stats from the S-1: $144 million in annual recurring revenues @ 50% compound annual growth rate, 76% gross margins, nearly 1,000 employees and over 67,000 paying customers.

SEMrush, the SEO tool, has filed to go public. Here’s the S-1: https://t.co/i1meSHts4Y

They spent $54 million on marketing last year, for revenue of $125 million.

(gross profit $95m, net loss $7m) pic.twitter.com/iz5nybcwfA— dan barker (@danbarker) March 1, 2021

At some point a lot of tool suits tend to overlap because much of their data either comes from scraping Google or crawling the open web. If something is strong enough of a point of differentiation to where it is widely talked about or marketed then competitors will try to clone it. Thus spending a bit extra on marketing to ensure you have the brand awareness to be the first tool people try is wise. Years ago when I ran a membership site here I paid to license the ability to syndicate some SEMrush data for our members & I have promoted them as an affiliate for what seems like a decade now.

When Dan Baker did his analysis of the S-1 it made me think SEMrush likely has brighter prospects than many would consider. A few of the reasons I could think of off the top of my head:

• each day their archive of historical data is larger, especially when you consider they crawl many foreign markets which some other competitive research tools ignore
• increasing ad prices promote SEO by making it relatively cheaper
• keyword not provided on organic search means third party competitive analysis tools are valuable not only for measuring competitors but also measuring your own site
• Google Ads has recently started broadening ad targeting further and hiding some keyword data so advertisers are paying for clicks where they are not even aware what the keyword was

That last point speaks to Google’s dominance over the search ecosystem. But it is also so absurd that even people who ran AdWords training workshops point out the absurdity.

Yesterday’s announcement on match type changes had me crawling through query data this morning. I’m staring at many 2-3 word exact match keywords that are matching to 8-word queries. G thinks ‘deck paint’ and ‘how do i put paint on my deck’ mean the exact same thing. CPA is 10x.— Brad Geddes (@bgtheory) February 5, 2021

In Google maximizing their income some nuance is lost for the advertiser who must dig into N-Gram analysis or look at historical data to find patterns to adjust:

The account overall has a CPA in the $450 range. If the word ‘how’ is in the query, our CPA is over double. If someone searches for ‘quote,’ our CPA is under $300. If they ask a question about cost, the CPA is over $1000. Obviously, looking for quotes versus cost data is very different in the eyes of a user, but not in the matching search terms of Google.

Every ad network has incentive to overstate its contribution to awareness and conversions so that more ad budget is allocated to them.

• Facebook kept having to restate their ad stats around video impressions, user reach, etc.
• Facebook gave themselves a 28 day window for credit for some app installs.
• Google AMP accidentally double counted unique users on Google Analytics (drives adoption = good).
• Google Analytics came with last click attribution, which over-credits the search channel you use near the end of a conversion journey.

There are a lot of Google water carriers who suggest any and all of their actions are at worst benevolent, but when I hear about hiding keyword data I am reminded of the following quote from the Texas AG Google lawsuit.

“Google employees agreed that, in the future, they should not directly lie to publishers, but instead find ways to convince publishers to act against their interest and remove header bidding on their own.”

That lawsuit details the great lengths Google went to in order to leverage their search monopoly to keep monopoly profit margins on their display ad serving business.

AMP was created with the explicit intent to kill header bidding as header bidding shifted power and profit margins to publishers. Some publishers saw a 50% rise in ad revenues from header bidding.

Remember how Google made companywide bonuses depend on the performance of the Google Facebook clone named Google+? Google later literally partnered with Facebook on a secret ad deal to prevent Facebook from launching a header bidding solution. The partnership agreement with Facebook explicitly mentioned antitrust repeatedly.

Bid-rigging?! Is this bid-rigging? As in, one of the “supreme evils of antitrust”? As in, the thing that if RE investors do it at foreclosure auctions they go to prison? pic.twitter.com/w7ez6gwfZd— John Newman (@johnmarknewman) December 16, 2020

When a company partners with its biggest direct competitor on a bid rigging scheme you can count on it that the intent is to screw others.

So when you see Google talk about benevolence, remember that they promise to no longer lie in the future & only deceive others into working against themselves via other coercive measures.

We went from the observation that you can’t copyright facts to promoting opinion instead:

The Internet commoditized the distribution of facts. The “news” media responded by pivoting wholesale into opinions and entertainment.— Naval (@naval) May 26, 2016

to where after many thousands of journalists have been laid off now the “newspaper of record” is promoting ponzi scheme garbage as a performance art piece:

The NYT made a NFT!

My new column is about NFTs, and I also turned the column into a NFT and put it up for auction on @withFND, with proceeds going to charity.

Bid away, and you could own the first NFT in the paper’s 170-year history. https://t.co/9ItGZvID8B— Kevin Roose (@kevinroose) March 24, 2021

The decline of About.com was literally going to be terminal without the work of Barry Diller to revive it. That slide reflected how over time a greater share of searches never actually leave Google:

Of those 5.1T searches, 33.59% resulted in clicks on organic search results. 1.59% resulted in clicks on paid search results. The remaining 64.82% completed a search without a direct, follow-up click to another web property. Searches resulting in a click are much higher on desktop devices (50.75% organic CTR, 2.78% paid CTR). Zero-click searches are much higher on mobile devices (77.22%)

The data from the above study came from SimilarWeb, which is another online marketing competitive research tool planning on going public soon.

Google “debunked” Rand’s take by focusing on absolute numbers instead of relative numbers. But if you keep buying default placements in a monopoly ecosystem where everyday more people have access to a computer in their pocket you would expect your marketshare and absolute numbers to increase even if the section of pie other publishers becomes a smaller slice of a bigger pie.

Google’s take there is disingenuous at the core. It reminds me of the time when they put out a study claiming brand bidding was beneficial and that it was too complex and expensive for advertisers to set up a scientific study, without any mention of the fact the reason that would be complex and expensive is because Google chooses not to provide those features in their ad offering. That parallels the way they now decide to hide keyword data even from paying advertisers in much the same way they hide ad fees and lie to publishers to protect their ad income.

Google suggests they don’t make money from news searches, but if they control most of the display ads technology stack & used search to ram AMP down publishers throats as a technological forced sunk cost while screwing third party ad networks and news publishers, Google can both be technically true in their statement and lying in spirit.

“Google employees agreed that, in the future, they should not directly lie to publishers, but instead find ways to convince publishers to act against their interest and remove header bidding on their own.”

There are many more treats in store for publishers.

Google will stop supporting third party cookies in Chrome next year. They are also going to stop selling ads where targeting is based on tracking user data across websites:

“Google plans to stop selling ads based on individuals’ browsing across multiple websites, a change that could hasten upheaval in the digital advertising industry. The Alphabet Inc. company said Wednesday that it plans next year to stop using or investing in tracking technologies that uniquely identify web users as they move from site to site across the internet. … Google had already announced last year that it would remove the most widely used such tracking technology, called third-party cookies, in 2022. But now the company is saying it won’t build alternative tracking technologies, or use those being developed by other entities, to replace third-party cookies for its own ad-buying tools. … Google says its announcement on Wednesday doesn’t cover its ad tools and unique identifiers for mobile apps, just for websites.”

Google stated they would make no replacement for the equivalent of the third party cookie tracking of individual users:

“we continue to get questions about whether Google will join others in the ad tech industry who plan to replace third-party cookies with alternative user-level identifiers. Today, we’re making explicit that once third-party cookies are phased out, we will not build alternate identifiers to track individuals as they browse across the web, nor will we use them in our products. We realize this means other providers may offer a level of user identity for ad tracking across the web that we will not — like PII graphs based on people’s email addresses. We don’t believe these solutions will meet rising consumer expectations for privacy, nor will they stand up to rapidly evolving regulatory restrictions, and therefore aren’t a sustainable long term investment.”

On the above announcement, other ad networks tanked, with TheTradeDesk falling 20% in two days.

These are all Google’s competitors in advertising technology, collapsing after Google announced that it won’t let them do targeted advertising anymore, but that Google itself will continue to do it. https://t.co/S6Axcrw5a0— Matt Stoller (@matthewstoller) March 5, 2021

Competing ad networks wonder if Google will play by their own rules:

“One clarification I’d like to hear from them is whether or not it means there’ll be no login for DBM [a historic name for Google’s DSP], no login for YouTube and no login for Google properties. I’m looking for them to play by the same rules that they so generously foisted upon the rest of the industry,” Magnite CTO Tom Kershaw said.

Regulators are looking into antitrust implications:

“Google’s plan to block a popular web tracking tool called “cookies” is a source of concern for U.S. Justice Department investigators who have been asking advertising industry executives whether the move by the search giant will hobble its smaller rivals, people familiar with the situation said.”

The web will continue to grow more complicated, but it isn’t going to get any more transparent anytime soon.

“Google employees agreed that, in the future, they should not directly lie to publishers, but instead find ways to convince publishers to act against their interest and remove header bidding on their own.”

As the Attention Merchants blur the ecosystem while shifting free clicks over to paid and charging higher ad rates on their owned and operated properties it increases the value of neutral third party measurement services.

The trend is not too hard to notice if you are remotely awake.

While I was writing this post Google announced the launch of a “best things” scraper website featuring their scraped re-representations of hot selling items.

If I could give you one key takeaway here, it would be this:

“Google employees agreed that, in the future, they should not directly lie to publishers, but instead find ways to convince publishers to act against their interest and remove header bidding on their own.”

On Wednesday SEMrush priced their IPO at $14 a share & listed Thursday.

There have been many marketing and online advertising companies which are publicly traded, but few that were so focused specifically on SEO while having a sizeable market cap. According to this SeekingAlpha post at the IPO price SEMrush had a valuation of about $1.95 to $1.99 billion. For comparison sake, here are some other companies & valuations.

• Facebook acquired Instagram for $1 billion.
• Google acquired YouTube for $1.65 billion.
• Yelp trades at around a $2.9 billion market cap.
• Yahoo! was acquired by Verizon for $4.48 billion.
• Hubspot has a market cap of around $20.4 billion.

A couple years ago Gannett bought AdWords reseller WordStream. A few years before that they bought ReachLocal. The Hearst publishing empire also bought iCrossing long ago. Marin Software remains publicly traded, but they are only valued at about $20 million.

Newspapers reselling Google AdWords ads isn’t really SEO though. Beyond those sorts of deals, many of the publicly traded SEO stuff has been only tangentially relevant to SEO, or crap.

There are some quality category-leading publishers which use SEO as a means of distribution but are not necessarily an SEO service provider like TripAdvisor, BankRate, and WebMD. Over time many of these sorts of companies have been gobbled up by Red Ventures or various private equity firms. Zillow, Yelp and TripAdvisor are some of the few examples which still exist as independent companies.

So that puts most of the publicly traded SEO stuff in one of the following categories…

• small scale – does anyone other than Andy Beal & Mike Grehan still remember KeywordRanking / WebSourced / Think Interactive / MarketSmart Interactive?
• hope and nope – sites like Business.com were repeatedly acquired but never really gained lasting relevance.
• affiliate networks – which reliant on partners with SEO traffic like Quinstreet & Commission Junction. many affiliate networks were hit hard as the barrier to entry in SEO increased over the years. Quinstreet is doing well in some verticals but sold their education division to Education Dynamics for $20 million. CJ was part of the Publicis Groupe acquisition of Epsilon.
• pump and dump scams – Demand Media, owner of eHow, which later rebranded as Leaf Group & still trades at a small fraction of their IPO price.

[Editorial note: 8 days after writing this post LEAF announced a $304.3 million all cash buyout offer from Graham Holdings at 21% above current market prices and was trading at $8.63 a share. If you bought shares at $40 or $30 or $20 and hoped it would at some point come back – nope – the losses are crystalized on a take out. Graham Holdings formerly owned the Washington Post but sold it to Jeff Bezos 8 years ago for $250 million.]

The one lasting counter-example to the above is Barry Diller’s IAC. His innovation ecosystem is surreal. Across time & across markets he is the best creator of vertical leading properties later spun off as their own companies. He’s owned Expedia, TripAdvisor, LendingTree, HomeAdvisor, Match.com, TicketMaster and so many other category leaders. His buying of Ask.com did not pan out as well as hoped as web browsers turned the address bar into a search box, his ability to differentiate the service went away after they shut down the engine in 2008, he was locked out of mobile search marketshare by default placement contracts & Google pushes back against extension bundling, but just about everything else he touched turned to gold. A lot of their current market cap is their ownership of Vimeo, which by itself is valued at $6 billion.

What is the most recent big bet for Barry Diller? MGM. Last August he bet $1 billion on the growth of online gambling. And he was willing to bet another billion to help them acquire Entain:

IAC has to date invested approximately US$1 billion in MGM with an initial investment thesis of accelerating MGM’s penetration of the $450 billion global gaming market. IAC notes in its letter of intent that IAC continues to strongly support this objective for MGM whether or not a transaction with Entain is consummated.

Barry Diller not only accurately projects future trends, but he also has the ability to rehab broken companies past their due dates.

The New York Times bought About.com for $410 million in 2005 & did little with it as its relevance declined over time as its content got stale, Wikipedia grew and search engines kept putting more scraped content in the search results. The relentless growth of Wikipedia and Google launching “universal search” in 2007 diminished the value of About.com even as web usage was exploding.

IAC bought About.com from the New York Times for $300 million in August of 2012. They tried to grow it through improving usability, content depth and content quality but ultimately decided to blow it up.

They were bold enough to break it into vertical category branded sites. They’ve done amazingly well with it and in many cases they rank 2, 3, 4 times in the SERPs with different properties like TheSpruce, TheBalance, Investopedia, etc. As newspapers chains keep consolidating or going under, IAC is one of the few constant “always wins” online publishers.

At its peak TheBalance was getting roughly 2/3 the traffic About.com generated.

Part of the decline in the chart there was perhaps a Panda hit, but the reason traffic never fully recovered is they broke some of these category sites into niche sites using sub-brands.

All the above search traffic estimate trend charts are from SEMrush. :)

I could do a blog post titled 1001 ways to use SEMrush if you would like me to, though I haven’t yet as I already have affiliate ads for them here and don’t want to come across as a shill by overpromoting a tool I love & use regularly.

I tend to sort of “not get” a lot of SaaS stocks in terms of prices and multiples, though they seem to go to infinity and beyond more often than not. I actually like SEMrush more than most though & think they’ll do well for years to come. I get the sense with both them and Ahrefs that they were started by programmers who learned marketing rather than started by marketers who cobbled together offerings which they though would sell. If you ever have feedback on ways to improve SEMrush they are fast at integrating it, or at least were in the past whenever I had feedback.

When SEMrush released their S-1 Dan Barker did a quick analysis on Twitter.

Some stats from the S-1: $144 million in annual recurring revenues @ 50% compound annual growth rate, 76% gross margins, nearly 1,000 employees and over 67,000 paying customers.

SEMrush, the SEO tool, has filed to go public. Here’s the S-1: https://t.co/i1meSHts4Y

They spent $54 million on marketing last year, for revenue of $125 million.

(gross profit $95m, net loss $7m) pic.twitter.com/iz5nybcwfA— dan barker (@danbarker) March 1, 2021

At some point a lot of tool suits tend to overlap because much of their data either comes from scraping Google or crawling the open web. If something is strong enough of a point of differentiation to where it is widely talked about or marketed then competitors will try to clone it. Thus spending a bit extra on marketing to ensure you have the brand awareness to be the first tool people try is wise. Years ago when I ran a membership site here I paid to license the ability to syndicate some SEMrush data for our members & I have promoted them as an affiliate for what seems like a decade now.

When Dan Barker did his analysis of the S-1 it made me think SEMrush likely has brighter prospects than many would consider. A few of the reasons I could think of off the top of my head:

• each day their archive of historical data is larger, especially when you consider they crawl many foreign markets which some other competitive research tools ignore
• increasing ad prices promote SEO by making it relatively cheaper
• keyword not provided on organic search means third party competitive analysis tools are valuable not only for measuring competitors but also measuring your own site
• Google Ads has recently started broadening ad targeting further and hiding some keyword data so advertisers are paying for clicks where they are not even aware what the keyword was

That last point speaks to Google’s dominance over the search ecosystem. But it is also so absurd that even people who ran AdWords training workshops point out the absurdity.

Yesterday’s announcement on match type changes had me crawling through query data this morning. I’m staring at many 2-3 word exact match keywords that are matching to 8-word queries. G thinks ‘deck paint’ and ‘how do i put paint on my deck’ mean the exact same thing. CPA is 10x.— Brad Geddes (@bgtheory) February 5, 2021

In Google maximizing their income some nuance is lost for the advertiser who must dig into N-Gram analysis or look at historical data to find patterns to adjust:

The account overall has a CPA in the $450 range. If the word ‘how’ is in the query, our CPA is over double. If someone searches for ‘quote,’ our CPA is under $300. If they ask a question about cost, the CPA is over $1000. Obviously, looking for quotes versus cost data is very different in the eyes of a user, but not in the matching search terms of Google.

Every ad network has incentive to overstate its contribution to awareness and conversions so that more ad budget is allocated to them.

• Facebook kept having to restate their ad stats around video impressions, user reach, etc.
• Facebook gave themselves a 28 day window for credit for some app installs.
• Google AMP accidentally double counted unique users on Google Analytics (drives adoption = good).
• Google Analytics came with last click attribution, which over-credits the search channel you use near the end of a conversion journey.

There are a lot of Google water carriers who suggest any and all of their actions are at worst benevolent, but when I hear about hiding keyword data I am reminded of the following quote from the Texas AG Google lawsuit.

“Google employees agreed that, in the future, they should not directly lie to publishers, but instead find ways to convince publishers to act against their interest and remove header bidding on their own.”

That lawsuit details the great lengths Google went to in order to leverage their search monopoly to keep monopoly profit margins on their display ad serving business.

AMP was created with the explicit intent to kill header bidding as header bidding shifted power and profit margins to publishers. Some publishers saw a 50% rise in ad revenues from header bidding.

Remember how Google made companywide bonuses depend on the performance of the Google Facebook clone named Google+? Google later literally partnered with Facebook on a secret ad deal to prevent Facebook from launching a header bidding solution. The partnership agreement with Facebook explicitly mentioned antitrust repeatedly.

Bid-rigging?! Is this bid-rigging? As in, one of the “supreme evils of antitrust”? As in, the thing that if RE investors do it at foreclosure auctions they go to prison? pic.twitter.com/w7ez6gwfZd— John Newman (@johnmarknewman) December 16, 2020

When a company partners with its biggest direct competitor on a bid rigging scheme you can count on it that the intent is to screw others.

So when you see Google talk about benevolence, remember that they promise to no longer lie in the future & only deceive others into working against themselves via other coercive measures.

We went from the observation that you can’t copyright facts to promoting opinion instead:

The Internet commoditized the distribution of facts. The “news” media responded by pivoting wholesale into opinions and entertainment.— Naval (@naval) May 26, 2016

to where after many thousands of journalists have been laid off now the “newspaper of record” is promoting ponzi scheme garbage as a performance art piece:

The NYT made a NFT!

My new column is about NFTs, and I also turned the column into a NFT and put it up for auction on @withFND, with proceeds going to charity.

Bid away, and you could own the first NFT in the paper’s 170-year history. https://t.co/9ItGZvID8B— Kevin Roose (@kevinroose) March 24, 2021

Is it any wonder people have lost trust in institutions?

A one-hour @CBCNews special that examines the media’s role in the polarization of America and the unmaking of a citizen — Big News is now streaming. pic.twitter.com/tm5QB2P4Ro— CBC Gem (@cbcgem) March 26, 2021

The decline of About.com was literally going to be terminal without the work of Barry Diller to revive it. That slide reflected how over time a greater share of searches never actually leave Google:

Of those 5.1T searches, 33.59% resulted in clicks on organic search results. 1.59% resulted in clicks on paid search results. The remaining 64.82% completed a search without a direct, follow-up click to another web property. Searches resulting in a click are much higher on desktop devices (50.75% organic CTR, 2.78% paid CTR). Zero-click searches are much higher on mobile devices (77.22%)

The data from the above study came from SimilarWeb, which is another online marketing competitive research tool planning on going public soon.

Google “debunked” Rand’s take by focusing on absolute numbers instead of relative numbers. But if you keep buying default placements in a monopoly ecosystem where everyday more people have access to a computer in their pocket you would expect your marketshare and absolute numbers to increase even if the section of pie other publishers becomes a smaller slice of a bigger pie.

Google’s take there is disingenuous at the core. It reminds me of the time when they put out a study claiming brand bidding was beneficial and that it was too complex and expensive for advertisers to set up a scientific study, without any mention of the fact the reason that would be complex and expensive is because Google chooses not to provide those features in their ad offering. That parallels the way they now decide to hide keyword data even from paying advertisers in much the same way they hide ad fees and lie to publishers to protect their ad income.

Google suggests they don’t make money from news searches, but if they control most of the display ads technology stack & used search to ram AMP down publishers throats as a technological forced sunk cost while screwing third party ad networks and news publishers, Google can both be technically true in their statement and lying in spirit.

“Google employees agreed that, in the future, they should not directly lie to publishers, but instead find ways to convince publishers to act against their interest and remove header bidding on their own.”

There are many more treats in store for publishers.

Google Chrome stopped sending full referrals for most web site visitors late last year. Google will stop supporting third party cookies in Chrome next year. They’ve even floated the idea of hiding user IP addresses from websites (good luck to those who need to prevent fraud!).

Google claims they also going to stop selling ads where targeting is based on tracking user data across websites:

“Google plans to stop selling ads based on individuals’ browsing across multiple websites, a change that could hasten upheaval in the digital advertising industry. The Alphabet Inc. company said Wednesday that it plans next year to stop using or investing in tracking technologies that uniquely identify web users as they move from site to site across the internet. … Google had already announced last year that it would remove the most widely used such tracking technology, called third-party cookies, in 2022. But now the company is saying it won’t build alternative tracking technologies, or use those being developed by other entities, to replace third-party cookies for its own ad-buying tools. … Google says its announcement on Wednesday doesn’t cover its ad tools and unique identifiers for mobile apps, just for websites.”

Google stated they would make no replacement for the equivalent of the third party cookie tracking of individual users:

“we continue to get questions about whether Google will join others in the ad tech industry who plan to replace third-party cookies with alternative user-level identifiers. Today, we’re making explicit that once third-party cookies are phased out, we will not build alternate identifiers to track individuals as they browse across the web, nor will we use them in our products. We realize this means other providers may offer a level of user identity for ad tracking across the web that we will not — like PII graphs based on people’s email addresses. We don’t believe these solutions will meet rising consumer expectations for privacy, nor will they stand up to rapidly evolving regulatory restrictions, and therefore aren’t a sustainable long term investment.”

On the above announcement, other ad networks tanked, with TheTradeDesk falling 20% in two days.

These are all Google’s competitors in advertising technology, collapsing after Google announced that it won’t let them do targeted advertising anymore, but that Google itself will continue to do it. https://t.co/S6Axcrw5a0— Matt Stoller (@matthewstoller) March 5, 2021

Competing ad networks wonder if Google will play by their own rules:

“One clarification I’d like to hear from them is whether or not it means there’ll be no login for DBM [a historic name for Google’s DSP], no login for YouTube and no login for Google properties. I’m looking for them to play by the same rules that they so generously foisted upon the rest of the industry,” Magnite CTO Tom Kershaw said.

Regulators are looking into antitrust implications:

“Google’s plan to block a popular web tracking tool called “cookies” is a source of concern for U.S. Justice Department investigators who have been asking advertising industry executives whether the move by the search giant will hobble its smaller rivals, people familiar with the situation said.”

The web will continue to grow more complicated, but it isn’t going to get any more transparent anytime soon.

“Google employees agreed that, in the future, they should not directly lie to publishers, but instead find ways to convince publishers to act against their interest and remove header bidding on their own.”

As the Attention Merchants blur the ecosystem while shifting free clicks over to paid and charging higher ad rates on their owned and operated properties it increases the value of neutral third party measurement services.

The trend is not too hard to notice if you are remotely awake.

While I was writing this post Google announced the launch of a “best things” scraper website featuring their scraped re-representations of hot selling items. And they are cross-promoting competitors in “knowledge” panels to dilute brand values & force the brand ad buy.

Oh man. Check out this bullshit on our GMB Knowledge Panel. Are they going to list competitors on everyone’s listings now? pic.twitter.com/ITwiZGyRxs— Darren Shaw (@DarrenShaw_) March 26, 2021

Shortly after Google launched their thin affiliate scraper site full of product ads they announced an update to demote other product review sites.

Where Google can get away with it, they will rig things in their favor to rip off other players in the ecosystem:

Google for years operated a secret program that used data from past bids in the company’s digital advertising exchange to allegedly give its own ad-buying system an advantage over competitors, according to court documents filed in a Texas antitrust lawsuit. The program, known as “Project Bernanke,” wasn’t disclosed to publishers who sold ads through Google’s ad-buying systems.

If I could give you one key takeaway here, it would be this:

“Google employees agreed that, in the future, they should not directly lie to publishers, but instead find ways to convince publishers to act against their interest and remove header bidding on their own.”

Google, Google, Google

For well over a decade Google has dominated search to where most stories in the search sphere were about Google or something on the periphery.

In 2019 Google generated $134.81 billion in ad revenues.

When Verizon bought core Yahoo three years ago the final purchase price was $4.48 billion. That amount was to own their finance vertical, news vertical, web portal, homepage, email & web search. It also included a variety of other services like Tumblr.

Part of what keeps Google so dominant in search is their brand awareness. That is also augmented by distribution as defaults in Chrome and Android. Then when it comes to buying search distribution from other players like Mozilla Firefox, Opera or Apple’s Safari they can outbid everyone else as they are much better at monetizing tier 2 markets and emerging markets than other search companies are since they have such strong ad depth. Even if Bing gave a 100% revshare to Apple they still could not compete with Google in most markets in terms of search monetization.

Apple as a Huge Search Traffic Driver

In 2019 Google paid just under £1.2 billion in default payments for UK search traffic. Most of that went to Apple. Historically when Google broke out their search revenues by region typically the US was around 45% to 46% of search ad revenue & the UK was around 11% to 12%, so it is likely Google is spending north of $10 billion a year to be the default search provider on Apple devices:

Apple submitted that search engines do not pay Apple for the right to be set as the primary default search engine on its devices. However, our assessment is that Google does pay to be the primary default on Apple devices. The agreement between Google and Apple states that Google will be the default web search provider and the same agreement states that Google will pay Apple a specified share of search advertising revenues. We also note that Google does not pay compensation to any partners that set Google Search as a secondary option. This further suggests that Google’s payment to Apple is in return for Apple setting Google as the primary default.

Apple is glad to cash those checks & let Google handle the core algorithmic search function in the web browser, but Apple also auto-completes many searches from within the address bar via various features like website history, top hit, news, Siri suggested website, suggested sites, etc.

A Unique Voice in Search

The nice thing about Apple powering some of those search auto-complete results themselves is their results are not simply a re-hash of the Google search results so they can add a unique voice to the search marketplace where if your site isn’t doing as well in Google it could still be promoted by Apple based on other factors.

High-traffic Shortcuts

Apple users generally have plenty of disposable personal income and a tendency to dispose of much of it, so if you are an Android user it is probably worth having an Apple device to see what they are recommending for core terms in your client’s markets. If you want to see recommendations for a particular country you may need to have a specialized router targeted to that country or use a web proxy or VPN.

Most users likely conduct full search queries and click through to listings from the Google search result page, but over time the search autocomplete feature that recommends previously viewed websites and other sites likely picks up incremental share of voice.

A friend of mine from the UK runs a local site and the following shows how the Apple ecosystem drove nearly 2/3 of his website traffic.

His website is only a couple years old, so it doesn’t get a ton of traffic from other sources yet. As of now his site does not have great Google rankings, but even if it did the boost by the Apple recommendations still provides a tailwind of free distribution and awareness (for however long it lasts).

For topics covered in news or repeat navigational searches Apple likely sends a lot of direct visits via their URL auto-completion features, but they do not use the feature broadly into the tail of search across other verticals, so it is a limited set of searches that ultimately benefit from the shortcuts.

Apple Search Ranking Factors

Apple recently updated their search page offering information about Applebot:

Apple Search may take the following into account when ranking web search results:

• Aggregated user engagement with search results
• Relevancy and matching of search terms to webpage topics and content
• Number and quality of links from other pages on the web
• User location based signals (approximate data)
• Webpage design characteristics

Search results may use the above factors with no (pre-determined) importance of ranking. Users of Search are subject to the privacy policy in Siri Suggestions, Search & Privacy.

I have seen some country-code TLDs do well in their local markets in spite of not necessarily being associated with large brands. Sites which do not rank well in Google can still end up in the mix provided the user experience is clean, the site is useful and it is easy for Apple to associate the site with a related keyword.

Panda-like Quality Updates

Markets like news change every day as the news changes, but I think Apple also does some Panda-like updates roughly quarterly where they do a broad refresh of what they recommend generally. As part of those updates sites which were once recommended can end up seeing the recommendation go away (especially if user experience declined since the initial recommendation via an ad heavy layout or similar) while other sites that have good engagement metrics get recommended on related searches.

A friend had a website they sort of forgot that was recommended by Apple. That site saw a big jump on July 9, 2018 then it slid back in early August that year, likely after the testing data showed it wasn’t as good as some other site Apple recommended. They noticed the spike in traffic & improved the site a bit. In early October it was widely recommended once again. That lasted until May of 2019 when it fell off a cliff once more. They had monetized the site with a somewhat spammy ad network & the recommendation mostly went away.

The recommendations happen as the person types and they may be different for searches where there is a space between keywords and the word is ran together. It is also worth noting Apple will typically recommend the www. version of a site over the m. version of a site for sites that offer both, so it makes sense to ensure if you used separate URLs that the www version also uses a responsive website design.

Indirect Impact on Google

While the Apple search shortcuts bypass Google search & thus do not create direct user signals to impact Google search, people who own an iPhone then search on a Windows computer at work or a Windows laptop at home might remember the site they liked from their iPhone and search for it once more, giving the site some awareness that could indirectly bleed over into impacting Google’s search rankings.

Apple could also eventually roll out their own fully featured search engine.

Google, Google, Google

For well over a decade Google has dominated search to where most stories in the search sphere were about Google or something on the periphery.

In 2019 Google generated $134.81 billion in ad revenues.

When Verizon bought core Yahoo three years ago the final purchase price was $4.48 billion. That amount was to own their finance vertical, news vertical, web portal, homepage, email & web search. It also included a variety of other services like Tumblr.

Part of what keeps Google so dominant in search is their brand awareness. That is also augmented by distribution as defaults in Chrome and Android. Then when it comes to buying search distribution from other players like Mozilla Firefox, Opera or Apple’s Safari they can outbid everyone else as they are much better at monetizing tier 2 markets and emerging markets than other search companies are since they have such strong ad depth. Even if Bing gave a 100% revshare to Apple they still could not compete with Google in most markets in terms of search monetization.

Apple as a Huge Search Traffic Driver

In 2019 Google paid just under £1.2 billion in default payments for UK search traffic. Most of that went to Apple. Historically when Google broke out their search revenues by region typically the US was around 45% to 46% of search ad revenue & the UK was around 11% to 12%, so it is likely Google is spending north of $10 billion a year to be the default search provider on Apple devices:

Apple submitted that search engines do not pay Apple for the right to be set as the primary default search engine on its devices. However, our assessment is that Google does pay to be the primary default on Apple devices. The agreement between Google and Apple states that Google will be the default web search provider and the same agreement states that Google will pay Apple a specified share of search advertising revenues. We also note that Google does not pay compensation to any partners that set Google Search as a secondary option. This further suggests that Google’s payment to Apple is in return for Apple setting Google as the primary default.

Apple is glad to cash those checks & let Google handle the core algorithmic search function in the web browser, but Apple also auto-completes many searches from within the address bar via various features like website history, top hit, news, Siri suggested website, suggested sites, etc.

A Unique Voice in Search

The nice thing about Apple powering some of those search auto-complete results themselves is their results are not simply a re-hash of the Google search results so they can add a unique voice to the search marketplace where if your site isn’t doing as well in Google it could still be promoted by Apple based on other factors.

High-traffic Shortcuts

Apple users generally have plenty of disposable personal income and a tendency to dispose of much of it, so if you are an Android user it is probably worth having an Apple device to see what they are recommending for core terms in your client’s markets. If you want to see recommendations for a particular country you may need to have a specialized router targeted to that country or use a web proxy or VPN.

Most users likely conduct full search queries and click through to listings from the Google search result page, but over time the search autocomplete feature that recommends previously viewed websites and other sites likely picks up incremental share of voice.

A friend of mine from the UK runs a local site and the following shows how the Apple ecosystem drove nearly 2/3 of his website traffic.

His website is only a couple years old, so it doesn’t get a ton of traffic from other sources yet. As of now his site does not have great Google rankings, but even if it did the boost by the Apple recommendations still provides a tailwind of free distribution and awareness (for however long it lasts).

For topics covered in news or repeat navigational searches Apple likely sends a lot of direct visits via their URL auto-completion features, but they do not use the feature broadly into the tail of search across other verticals, so it is a limited set of searches that ultimately benefit from the shortcuts.

Apple Search Ranking Factors

Apple recently updated their search page offering information about Applebot:

Apple Search may take the following into account when ranking web search results:

• Aggregated user engagement with search results
• Relevancy and matching of search terms to webpage topics and content
• Number and quality of links from other pages on the web
• User location based signals (approximate data)
• Webpage design characteristics

Search results may use the above factors with no (pre-determined) importance of ranking. Users of Search are subject to the privacy policy in Siri Suggestions, Search & Privacy.

I have seen some country-code TLDs do well in their local markets in spite of not necessarily being associated with large brands. Sites which do not rank well in Google can still end up in the mix provided the user experience is clean, the site is useful and it is easy for Apple to associate the site with a related keyword.

Panda-like Quality Updates

Markets like news change every day as the news changes, but I think Apple also does some Panda-like updates roughly quarterly where they do a broad refresh of what they recommend generally. As part of those updates sites which were once recommended can end up seeing the recommendation go away (especially if user experience declined since the initial recommendation via an ad heavy layout or similar) while other sites that have good engagement metrics get recommended on related searches.

A friend had a website they sort of forgot that was recommended by Apple. That site saw a big jump on July 9, 2018 then it slid back in early August that year, likely after the testing data showed it wasn’t as good as some other site Apple recommended. They noticed the spike in traffic & improved the site a bit. In early October it was widely recommended once again. That lasted until May of 2019 when it fell off a cliff once more. They had monetized the site with a somewhat spammy ad network & the recommendation mostly went away.

The recommendations happen as the person types and they may be different for searches where there is a space between keywords and the word is ran together. It is also worth noting Apple will typically recommend the www. version of a site over the m. version of a site for sites that offer both, so it makes sense to ensure if you used separate URLs that the www version also uses a responsive website design.

Indirect Impact on Google

While the Apple search shortcuts bypass Google search & thus do not create direct user signals to impact Google search, people who own an iPhone then search on a Windows computer at work or a Windows laptop at home might remember the site they liked from their iPhone and search for it once more, giving the site some awareness that could indirectly bleed over into impacting Google’s search rankings.

Apple could also eventually roll out their own fully featured search engine.

Late Funnel SEO Profits

Before the Panda update SEOs could easily focus almost all their energies on late funnel high-intent searches which were easy to monetize without needing to put a ton of effort into brand building or earlier funnel informational searches. This meant that SEOs could focus on phrases like [student credit cards] or [buy earbuds] or [best computer gaming headphones] or [vertical computer mouse] without needing to worry much about anything else. Make a good enough page on those topics, segment demand across options, and profit.

Due to the ability to focus content & efforts on those tiny subset high-intent commercial terms the absolute returns and CPMs from SEO investments were astronomical. Publishers could insert themselves arbitrarily just before the end of the value chain (just like Google AdWords) and extract a toll.

The Panda Shift / Eating the Info Supply Chain

Then Panda happened and sites needed to have stronger brands and/or more full funnel user experience and/or more differentiated content to be able to rank sustainably.

One over-simplified way to think of Panda and related algorithms would be: brand = rank.

Another way to look at it would be to consider the value chain of having many layers or pieces to it & Google wanting to remove as many unneeded or extra pieces from the chain as possible so that they themselves are capturing more of the value chain.

• That thin eHow article about a topic without any useful info? Not needed.
• The thin affiliate review which was buying Google AdSense ad impressions on that eHow article? Also not needed.
• All that is really needed is the consumer intent, Google & then either Google as the retailer (pay with your credentials stored in your phone) or another trusted retailer.

In some cases there may be value in mid-market in-depth reviews, but increasingly the aggregate value offered by many of them is captured inside the search snippets along with reviews directly incorporated into the knowledge graph & aggregate review scores.

The ability to remove the extra layers is driven largely by:

• the quality of the top players in the market
• the number of quality publishers in a market (as long as there are 2 or more, whoever is not winning will be willing to give a lot of value to Google to try to play catch up against their stronger competitor)
• the amount of usage data available in the market
• the ad depth of the market

If your competitor is strong and they keep updating in-depth content pieces you can’t set and forget your content and stay competitive. Across time searcher intent changes. Those who change with the markets should eventually have better engagement metrics and keep winning marketshare.

Benchmarking Your Competition

You only have to be better than whatever you are competing against to win.

If you have run out of ideas from your direct competitors in an emerging market you can typically find many more layers of optimization from looking at some of the largest and most successful players inside either the United States or China.

To give an example of how user data can be clean or a messy signal consider size 13 4E New Balance shoes. If you shop for these inside the United States a site like Amazon will have shoe size filters so you can see which shoes from that brand are available in that specific size.

In some smaller emerging markets ecommerce sites largely suck. They might allow you to filter shoes by the color blue but wanting to see the shoes available in your size is a choose your own adventure game as they do not offer those sorts of size filters, so you have to click into the shoe level, find out they do not have your size, and then try again. You do that about 100 times then eventually you get frustrated and buy off eBay or Amazon from someone who ships internationally.

In the first case it is very easy for Google to see the end user flow of users typically making their purchase at one of a few places like Amazon.com, the official New Balance store, or somewhere else like that which is likely to have the end product in stock. That second experience set is much harder to structure because the user signal is much more random with a lot more pogos back to Google.

Bigger, Better Ads

Over the past couple decades Google has grown much more aggressive at monetizing their search results. A website which sees its rank fall 1 position on mobile devices can see their mobile search traffic cut in half overnight. And desktop search results are also quite ad heavy to where sometimes a user can not see a single full organic result above the fold unless they have a huge monitor.

We tend to look at the present as being somewhat static. It is a part of human nature to think things are as they always were. But the general trend of the slow bleed squeeze is a function of math and time: “The relentless pressure to maintain Google’s growth, he said, had come at a heavy cost to the company’s users. Useful search results were pushed down the page to squeeze in more advertisements, and privacy was sacrificed for online tracking tools to keep tabs on what ads people were seeing.”

Some critics have captured the broad shift in ad labeling practices, but to get a grasp of how big the shift has been look at early Google search results.

Look at how bright those ad units from 2001 are.

Since then ad labeling has grown less intuitive while ad size has increased dramatically.

Traffic Mix Shift

As publishers have been crowded out on commercial searches via larger ads & Google’s vertical search properties a greater share of their overall search traffic is lower value visitors including people who have little to no commercial intent, people from emerging markets with lower disposable income and

Falling Ad Rates

Since 2010 online display ad rates have fallen about 40%.

Any individual publisher will experience those declines in a series of non-linear step function shifts. Any of the following could happen:

• Google Panda or another algorithm update from a different attention merchant hits your distribution hard
• a Softbank-backed competitor jumps into your market and gains a ton of press coverage using flammable money
• a roll-up player buys out a series of sites in the supply chain & then tries to make the numbers back out by cramming down on ad syndication partners (sometimes you have to gain enough scale to create your own network or keep rotating through ad networks to keep them honest)
• regulatory costs hit any part of the supply chain (the California parallel to GDPR just went live this month)
• consumer interest shifts to other markets or solutions (the mobile phone has replaced many gadgets)
• a recession causes broad-based advertiser pullbacks

Margin Eaters

In addition to lowering ad rates for peripheral websites, there are a couple other bonus margin eaters.

Junk Sunk Costs

Monopoly platforms push publishers to adopt proprietary closed code bases in order to maintain distribution: “the trade group says Google’s Accelerated Mobile Pages (AMP) format was foisted on news publishers with an implied threat — their websites wouldn’t show up in search results.”

Decreased Supply Chain Visibility

Technical overhead leading to programmatic middlemen eating a huge piece of the pie: “From every £1 spent by an advertiser, about half goes to a publisher, roughly 16p to advertising platforms, 11p to other technology companies and 7 per cent to agencies. Adtech companies that took part in the study included Google’s dv360 and Ad Manager, Amazon Advertising and the Rubicon Project.”

Selection Effect

Large attention merchants control conversion tracking systems and displace organic distribution for brands by re-routing demand through a layer of ads which allows the central network to claim responsibility for conversions which would have already happened had they not existed.

Internal employees in the marketing department and external internet marketing consultants have an incentive to play along with this game because:

• it requires low effort to arbitrage your own brand
• at first glance it looks wildly profitable so long as you do not realize what is going on
• those who get a percent of spend can use the phantom profits from arbitraging their own brand equity to spend more money elsewhere
• those who get performance based bonuses get a bonus without having to perform

Both eBay and Microsoft published studies which showed how perverse selection effect is.

The selection effect bias is the inverse of customer acquisition cost. The more well known your brand is the more incentive ad networks have to arbitrage it & the more ad networks will try to take credit for any conversion which happens.

2) Why does CAC (mostly) only go up?

When you think about, CAC is “lowest” in the beginning, because you have no customers. You can get the low-hanging fruit cost effectively.

Think ad spend. Outbound sales spend. etc. First movers are ready to buy quickly.— Elizabeth Yin (@dunkhippo33) July 6, 2020

These margin eaters are a big part of the reason so many publishers are trying to desperately shift away from ad-based business models toward subscription revenues.

Hitting Every Layer

The commodification of content hits every layer from photography….

Networking is an art and a skill… but if the gold you hold are your images, don’t trade them for the passive networking value.

Simple lesson that is difficult to accept.— Send it. (@johnondotcom) July 4, 2020

…on through to writing

When you think about it, even $1000 is really inexpensive for a single piece of content that generates 20,000+ visits from search in the 1-3 years it’s alive and ranks well. That’s only about 1,000 visits a month. Yet companies only want to pay writers only $200 an article — Dan Shure (@dan_shure) July 6, 2020

…and every other layer of the editorial chain.

Profiting from content creation at scale is harder than most appreciate.

The idea that a $200 piece of content is particularly cheap comes across as ill-informed as there are many headwinds and many variables. The ability to monetize content depends on a ton of factors including: how commercial is it, how hard is it to monetize, what revshare do you go, how hard is it to rank or get distribution in front of other high intent audience sets?

If an article costs $200 it would be hard to make that back if it monetizes at anything under a $10 RPM. 20,000 visits equates to 20 units of RPM.

Some articles will not spread in spite of being high quality. Other articles take significant marketing spend to help them spread. Suddenly that $200 “successful” piece is closer to $500 when one averages in nonperformers that don’t spread & marketing expenses on ones that do. So then they either need the RPM to double or triple from there or the successful article needs to get at least 50,000 visits in order to break even.

A $10 RPM is quite high for many topics unless the ads are quite aggressively integrated into the content. The flip side of that is aggressive ad integration inhibits content spread & can cause algorithmic issues which prevent sustained rankings. Recall that in the most recent algorithm update Credit Karma saw some of their “money” credit card pages slide down the rankings due to aggressive monetization. And that happened to a big site which was purchased for over $7 billion. Smaller sites see greater levels of volatility. And nobody is investing $100,000s trying to break even many years down the road. If they were only trying to break even they’d buy bonds and ignore the concept of actively running a business of any sort.

Back in 2018 AdStage analyzed the Google display network and found the following: “In Q1 2018, advertisers spent, on average, $2.80 per thousand impressions (CPM), and $0.75 per click (CPC). The average click-through rate (CTR) on the GDN was 0.35%.”

A web page which garnered 20,000 pageviews and had 3 ad units on each page would get a total of 210 ad clicks given a 0.35% ad CTR. At 75 cents per click that would generate $157.50.

Suddenly a “cheap” $200 article doesn’t look so cheap. What’s more is said business would also have other costs beyond the writing. They have to pay for project management, editorial review, hosting, ad partnerships & biz dev, etc. etc. etc.

After all those other layers of overhead a $200 article would likely need to get about 50,000 pageviews to back out. And a $1,000 piece of content might need to get a quarter million or more pageviews to back out.

Late Funnel SEO Profits

Before the Panda update SEOs could easily focus almost all their energies on late funnel high-intent searches which were easy to monetize without needing to put a ton of effort into brand building or earlier funnel informational searches. This meant that SEOs could focus on phrases like [student credit cards] or [buy earbuds] or [best computer gaming headphones] or [vertical computer mouse] without needing to worry much about anything else. Make a good enough page on those topics, segment demand across options, and profit.

Due to the ability to focus content & efforts on those tiny subset high-intent commercial terms the absolute returns and CPMs from SEO investments were astronomical. Publishers could insert themselves arbitrarily just before the end of the value chain (just like Google AdWords) and extract a toll.

The Panda Shift / Eating the Info Supply Chain

Then Panda happened and sites needed to have stronger brands and/or more full funnel user experience and/or more differentiated content to be able to rank sustainably.

One over-simplified way to think of Panda and related algorithms would be: brand = rank.

Another way to look at it would be to consider the value chain of having many layers or pieces to it & Google wanting to remove as many unneeded or extra pieces from the chain as possible so that they themselves are capturing more of the value chain.

• That thin eHow article about a topic without any useful info? Not needed.
• The thin affiliate review which was buying Google AdSense ad impressions on that eHow article? Also not needed.
• All that is really needed is the consumer intent, Google & then either Google as the retailer (pay with your credentials stored in your phone) or another trusted retailer.

In some cases there may be value in mid-market in-depth reviews, but increasingly the aggregate value offered by many of them is captured inside the search snippets along with reviews directly incorporated into the knowledge graph & aggregate review scores.

The ability to remove the extra layers is driven largely by:

• the quality of the top players in the market
• the number of quality publishers in a market (as long as there are 2 or more, whoever is not winning will be willing to give a lot of value to Google to try to play catch up against their stronger competitor)
• the amount of usage data available in the market
• the ad depth of the market

If your competitor is strong and they keep updating in-depth content pieces you can’t set and forget your content and stay competitive. Across time searcher intent changes. Those who change with the markets should eventually have better engagement metrics and keep winning marketshare.

Benchmarking Your Competition

You only have to be better than whatever you are competing against to win.

If you have run out of ideas from your direct competitors in an emerging market you can typically find many more layers of optimization from looking at some of the largest and most successful players inside either the United States or China.

To give an example of how user data can be clean or a messy signal consider size 13 4E New Balance shoes. If you shop for these inside the United States a site like Amazon will have shoe size filters so you can see which shoes from that brand are available in that specific size.

In some smaller emerging markets ecommerce sites largely suck. They might allow you to filter shoes by the color blue but wanting to see the shoes available in your size is a choose your own adventure game as they do not offer those sorts of size filters, so you have to click into the shoe level, find out they do not have your size, and then try again. You do that about 100 times then eventually you get frustrated and buy off eBay or Amazon from someone who ships internationally.

In the first case it is very easy for Google to see the end user flow of users typically making their purchase at one of a few places like Amazon.com, the official New Balance store, or somewhere else like that which is likely to have the end product in stock. That second experience set is much harder to structure because the user signal is much more random with a lot more pogos back to Google.

Bigger, Better Ads

Over the past couple decades Google has grown much more aggressive at monetizing their search results. A website which sees its rank fall 1 position on mobile devices can see their mobile search traffic cut in half overnight. And desktop search results are also quite ad heavy to where sometimes a user can not see a single full organic result above the fold unless they have a huge monitor.

We tend to look at the present as being somewhat static. It is a part of human nature to think things are as they always were. But the general trend of the slow bleed squeeze is a function of math and time: “The relentless pressure to maintain Google’s growth, he said, had come at a heavy cost to the company’s users. Useful search results were pushed down the page to squeeze in more advertisements, and privacy was sacrificed for online tracking tools to keep tabs on what ads people were seeing.”

Some critics have captured the broad shift in ad labeling practices, but to get a grasp of how big the shift has been look at early Google search results.

Look at how bright those ad units from 2001 are.

Since then ad labeling has grown less intuitive while ad size has increased dramatically.

Traffic Mix Shift

As publishers have been crowded out on commercial searches via larger ads & Google’s vertical search properties a greater share of their overall search traffic is lower value visitors including people who have little to no commercial intent, people from emerging markets with lower disposable income and

Falling Ad Rates

Since 2010 online display ad rates have fallen about 40%.

Any individual publisher will experience those declines in a series of non-linear step function shifts. Any of the following could happen:

• Google Panda or another algorithm update from a different attention merchant hits your distribution hard
• a Softbank-backed competitor jumps into your market and gains a ton of press coverage using flammable money
• a roll-up player buys out a series of sites in the supply chain & then tries to make the numbers back out by cramming down on ad syndication partners (sometimes you have to gain enough scale to create your own network or keep rotating through ad networks to keep them honest)
• regulatory costs hit any part of the supply chain (the California parallel to GDPR just went live this month)
• consumer interest shifts to other markets or solutions (the mobile phone has replaced many gadgets)
• a recession causes broad-based advertiser pullbacks

Margin Eaters

In addition to lowering ad rates for peripheral websites, there are a couple other bonus margin eaters.

Junk Sunk Costs

Monopoly platforms push publishers to adopt proprietary closed code bases in order to maintain distribution: “the trade group says Google’s Accelerated Mobile Pages (AMP) format was foisted on news publishers with an implied threat — their websites wouldn’t show up in search results.”

Decreased Supply Chain Visibility

Technical overhead leading to programmatic middlemen eating a huge piece of the pie: “From every £1 spent by an advertiser, about half goes to a publisher, roughly 16p to advertising platforms, 11p to other technology companies and 7 per cent to agencies. Adtech companies that took part in the study included Google’s dv360 and Ad Manager, Amazon Advertising and the Rubicon Project.”

Selection Effect

Large attention merchants control conversion tracking systems and displace organic distribution for brands by re-routing demand through a layer of ads which allows the central network to claim responsibility for conversions which would have already happened had they not existed.

Internal employees in the marketing department and external internet marketing consultants have an incentive to play along with this game because:

• it requires low effort to arbitrage your own brand
• at first glance it looks wildly profitable so long as you do not realize what is going on
• those who get a percent of spend can use the phantom profits from arbitraging their own brand equity to spend more money elsewhere
• those who get performance based bonuses get a bonus without having to perform

Both eBay and Microsoft published studies which showed how perverse selection effect is.

The selection effect bias is the inverse of customer acquisition cost. The more well known your brand is the more incentive ad networks have to arbitrage it & the more ad networks will try to take credit for any conversion which happens.

2) Why does CAC (mostly) only go up?

When you think about, CAC is “lowest” in the beginning, because you have no customers. You can get the low-hanging fruit cost effectively.

Think ad spend. Outbound sales spend. etc. First movers are ready to buy quickly.— Elizabeth Yin (@dunkhippo33) July 6, 2020

These margin eaters are a big part of the reason so many publishers are trying to desperately shift away from ad-based business models toward subscription revenues.

Hitting Every Layer

The commodification of content hits every layer from photography….

Networking is an art and a skill… but if the gold you hold are your images, don’t trade them for the passive networking value.

Simple lesson that is difficult to accept.— Send it. (@johnondotcom) July 4, 2020

…on through to writing

When you think about it, even $1000 is really inexpensive for a single piece of content that generates 20,000+ visits from search in the 1-3 years it’s alive and ranks well. That’s only about 1,000 visits a month. Yet companies only want to pay writers only $200 an article — Dan Shure (@dan_shure) July 6, 2020

…and every other layer of the editorial chain.

Profiting from content creation at scale is harder than most appreciate.

The idea that a $200 piece of content is particularly cheap comes across as ill-informed as there are many headwinds and many variables. The ability to monetize content depends on a ton of factors including: how commercial is it, how hard is it to monetize, what revshare do you go, how hard is it to rank or get distribution in front of other high intent audience sets?

If an article costs $200 it would be hard to make that back if it monetizes at anything under a $10 RPM. 20,000 visits equates to 20 units of RPM.

Some articles will not spread in spite of being high quality. Other articles take significant marketing spend to help them spread. Suddenly that $200 “successful” piece is closer to $500 when one averages in nonperformers that don’t spread & marketing expenses on ones that do. So then they either need the RPM to double or triple from there or the successful article needs to get at least 50,000 visits in order to break even.

A $10 RPM is quite high for many topics unless the ads are quite aggressively integrated into the content. The flip side of that is aggressive ad integration inhibits content spread & can cause algorithmic issues which prevent sustained rankings. Recall that in the most recent algorithm update Credit Karma saw some of their “money” credit card pages slide down the rankings due to aggressive monetization. And that happened to a big site which was purchased for over $7 billion. Smaller sites see greater levels of volatility. And nobody is investing $100,000s trying to break even many years down the road. If they were only trying to break even they’d buy bonds and ignore the concept of actively running a business of any sort.

Back in 2018 AdStage analyzed the Google display network and found the following: “In Q1 2018, advertisers spent, on average, $2.80 per thousand impressions (CPM), and $0.75 per click (CPC). The average click-through rate (CTR) on the GDN was 0.35%.”

A web page which garnered 20,000 pageviews and had 3 ad units on each page would get a total of 210 ad clicks given a 0.35% ad CTR. At 75 cents per click that would generate $157.50.

Suddenly a “cheap” $200 article doesn’t look so cheap. What’s more is said business would also have other costs beyond the writing. They have to pay for project management, editorial review, hosting, ad partnerships & biz dev, etc. etc. etc.

After all those other layers of overhead a $200 article would likely need to get about 50,000 pageviews to back out. And a $1,000 piece of content might need to get a quarter million or more pageviews to back out.

Links = Rank

Old Google (pre-Panda) was to some degree largely the following: links = rank.

Once you had enough links to a site you could literally pour content into a site like water and have the domain’s aggregate link authority help anything on that site rank well quickly.

As much as PageRank was hyped & important, having a diverse range of linking domains and keyword-focused anchor text were important.

Brand = Rank

After Vince then Panda a site’s brand awareness (or, rather, ranking signals that might best simulate it) were folded into the ability to rank well.

Panda considered factors beyond links & when it first rolled out it would clip anything on a particular domain or subdomain. Some sites like HubPages shifted their content into subdomains by users. And some aggressive spammers would rotate their entire site onto different subdomains repeatedly each time a Panda update happened. That allowed those sites to immediately recover from the first couple Panda updates, but eventually Google closed off that loophole.

Any signal which gets relied on eventually gets abused intentionally or unintentionally. And over time it leads to a “sameness” of the result set unless other signals are used:

Google is absolute garbage for searching anything related to a product. If I’m trying to learn something invariably I am required to search another source like Reddit through Google. For example, I became introduced to the concept of weighted blankets and was intrigued. So I Google “why use a weighted blanket” and “weighted blanket benefits”. Just by virtue of the word “weighted blanket” being in the search I got pages and pages of nothing but ads trying to sell them, and zero meaningful discourse on why I would use one

Getting More Granular

Over time as Google got more refined with Panda broad-based sites outside of the news vertical often fell on tough times unless they were dedicated to some specific media format or had a lot of user engagement metrics like a strong social network site. That is a big part of why the New York Times sold About.com for less than they paid for it & after IAC bought it they broke it down into a variety of sites like: Verywell (health), the Spruce (home decor), the Balance (personal finance), Lifewire (technology), Tripsavvy (travel) and ThoughtCo (education & self-improvement).

Penguin further clipped aggressive anchor text built on low quality links. When the Penguin update rolled out Google also rolled out an on-page spam classifier to further obfuscate the update. And the Penguin update was sandwiched by Panda updates on either side, making it hard for people to reverse engineer any signal out of weekly winners and losers lists from services that aggregate massive amounts of keyword rank tracking data.

So much of the link graph has been decimated that Google reversed their stance on nofollow to where in March 1st of this year they started treating it as a hint versus a directive for ranking purposes. Many mainstream media websites were overusing nofollow or not citing sources at all, so this additional layer of obfuscation on Google’s part will allow them to find more signal in that noise.

May 4, 2020 Algo Update

On May 4th Google rolled out another major core update.

Later today, we are releasing a broad core algorithm update, as we do several times per year. It is called the May 2020 Core Update. Our guidance about such updates remains as we’ve covered before. Please see this blog post for more about that:https://t.co/e5ZQUAlt0G— Google SearchLiaison (@searchliaison) May 4, 2020

I saw some sites which had their rankings suppressed for years see a big jump. But many things changed at once.

Wedge Issues

On some political search queries which were primarily classified as being news related Google is trying to limit political blowback by showing official sites and data scraped from official sites instead of putting news front & center.

“Google’s pretty much made it explicit that they’re not going to propagate news sites when it comes to election related queries and you scroll and you get a giant election widget in your phone and it shows you all the different data on the primary results and then you go down, you find Wikipedia, you find other like historical references, and before you even get to a single news article, it’s pretty crazy how Google’s changed the way that the SERP is intended.”

That change reflects the permanent change to the news media ecosystem brought on by the web.

The Internet commoditized the distribution of facts. The “news” media responded by pivoting wholesale into opinions and entertainment.— Naval (@naval) May 26, 2016

YMYL

A blog post by Lily Ray from Path Interactive used Sistrix data to show many of the sites which saw high volatility were in the healthcare vertical & other your money, your life (YMYL) categories.

Aggressive Monetization

One of the more interesting pieces of feedback on the update was from Rank Ranger, where they looked at particular pages that jumped or fell hard on the update. They noticed sites that put ads or ad-like content front and center may have seen sharp falls on some of those big money pages which were aggressively monetized:

Seeing this all but cements the notion (in my mind at least) that Google did not want content unrelated to the main purpose of the page to appear above the fold to the exclusion of the page’s main content! Now for the second wrinkle in my theory…. A lot of the pages being swapped out for new ones did not use the above-indicated format where a series of “navigation boxes” dominated the page above the fold.

The above shift had a big impact on some sites which are worth serious money. Intuit paid over $7 billion to acquire Credit Karma, but their credit card affiliate pages recently slid hard.

Credit Karma lost 40% traffic from May core update. That’s insane, they do major TV ads and likely pay millions in SEO expenses. Think about that folks. Your site isn’t safe. Google changes what they want radically with every update, while telling us nothing!— SEOwner (@tehseowner) May 14, 2020

The above sort of shift reflects Google getting more granular with their algorithms. Early Panda was all or nothing. Then it started to have different levels of impact throughout different portions of a site.

Brand was sort of a band aid or a rising tide that lifted all (branded) boats. Now we are seeing Google get more granular with their algorithms where a strong brand might not be enough if they view the monetization as being excessive. That same focus on page layout can have a more adverse impact on small niche websites.

One of my old legacy clients had a site which was primarily monetized by the Amazon affiliate program. About a month ago Amazon chopped affiliate commissions in half & then the aggressive ad placement caused search traffic to the site to get chopped in half when rankings slid on this update.

Their site has been trending down over the past couple years largely due to neglect as it was always a small side project. They recently improved some of the content about a month or so ago and that ended up leading to a bit of a boost, but then this update came. As long as that ad placement doesn’t change the declines are likely to continue.

They just recently removed that ad unit, but that meant another drop in income as until there is another big algo update they’re likely to stay at around half search traffic. So now they have a half of a half of a half. Good thing the site did not have any full time employees or they’d be among the millions of newly unemployed. That experience though really reflects how websites can be almost like debt levered companies in terms of going under virtually overnight. Who can have revenue slide around 88% and then take increase investment in the property using the remaining 12% while they wait for the site to be rescored for a quarter year or more?

“If you have been negatively impacted by a core update, you (mostly) cannot see recovery from that until another core update. In addition, you will only see recovery if you significantly improve the site over the long-term. If you haven’t done enough to improve the site overall, you might have to wait several updates to see an increase as you keep improving the site. And since core updates are typically separated by 3-4 months, that means you might need to wait a while.”

Almost nobody can afford to do that unless the site is just a side project.

Google could choose to run major updates more frequently, allowing sites to recover more quickly, but they gain economic benefit in defunding SEO investments & adding opportunity cost to aggressive SEO strategies by ensuring ranking declines on major updates last a season or more.

Choosing a Strategy vs Letting Things Come at You

They probably should have lowered their ad density when they did those other upgrades. If they had they likely would have seen rankings at worst flat or likely up as some other competing sites fell. Instead they are rolling with a half of a half of a half on the revenue front. Glenn Gabe preaches the importance of fixing all the problems you can find rather than just fixing one or two things and hoping it is enough. If you have a site which is on the edge you sort of have to consider the trade offs between various approaches to monetization.

• monetize it lightly and hope the site does well for many years
• monetize it slightly aggressively while using the extra income to further improve the site elsewhere and ensure you have enough to get by any lean months
• aggressively monetize the shortly after a major ranking update if it was previously lightly monetized & then hope to sell it off a month or two later before the next major algorithm update clips it again

Outcomes will depend partly on timing and luck, but consciously choosing a strategy is likely to yield better returns than doing a bit of mix-n-match while having your head buried in the sand.

Reading the Algo Updates

You can spend 50 or 100 hours reading blog posts about the update and learn precisely nothing in the process if you do not know which authors are bullshitting and which authors are writing about the correct signals.

But how do you know who knows what they are talking about?

It is more than a bit tricky as the people who know the most often do not have any economic advantage in writing specifics about the update. If you primarily monetize your own websites, then the ignorance of the broader market is a big part of your competitive advantage.

Making things even trickier, the less you know the more likely Google would be to trust you with sending official messaging through you. If you syndicate their messaging without questioning it, you get a treat – more exclusives. If you question their messaging in a way that undermines their goals, you’d quickly become persona non grata – something cNet learned many years ago when they published Eric Schmidt’s address.

It would be unlikely you’d see the following sort of Tweet from say Blue Hat SEO or Fantomaster or such.

I asked Gary about E-A-T. He said it’s largely based on links and mentions on authoritative sites. i.e. if the Washington post mentions you, that’s good.

He recommended reading the sections in the QRG on E-A-T as it outlines things well.@methode #Pubcon— Marie Haynes (@Marie_Haynes) February 21, 2018

To be able to read the algorithms well you have to have some market sectors and keyword groups you know well. Passively collecting an archive of historical data makes the big changes stand out quickly.

Everyone who depends on SEO to make a living should subscribe to an online rank tracking service or run something like Serposcope locally to track at least a dozen or two dozen keywords. If you track rankings locally it makes sense to use a set of web proxies and run the queries slowly through each so you don’t get blocked.

You should track at least a diverse range to get a true sense of the algorithmic changes.

• a couple different industries
• a couple different geographic markets (or at least some local-intent vs national-intent terms within a country)
• some head, midtail and longtail keywords
• sites of different size, age & brand awareness within a particular market

Some tools make it easy to quickly add or remove graphing of anything which moved big and is in the top 50 or 100 results, which can help you quickly find outliers. And some tools also make it easy to compare their rankings over time. As updates develop you’ll often see multiple sites making big moves at the same time & if you know a lot about the keyword, the market & the sites you can get a good idea of what might have been likely to change to cause those shifts.

Once you see someone mention outliers most people miss that align with what you see in a data set, your level of confidence increases and you can spend more time trying to unravel what signals changed.

I’ve read influential industry writers mention that links were heavily discounted on this update. I have also read Tweets like this one which could potentially indicate the opposite.

Check out https://t.co/1GhD2U01ch . Up even more than Pinterest and ranking for some real freaky shit.— Paul Macnamara (@TheRealpmac) May 12, 2020

If I had little to no data, I wouldn’t be able to get any signal out of that range of opinions. I’d sort of be stuck at “who knows.”

By having my own data I track I can quickly figure out which message is more inline with what I saw in my subset of data & form a more solid hypothesis.

No Single Smoking Gun

As Glenn Gabe is fond of saying, sites that tank usually have multiple major issues.

Google rolls out major updates infrequently enough that they can sandwich a couple different aspects into major updates at the same time in order to make it harder to reverse engineer updates. So it does help to read widely with an open mind and imagine what signal shifts could cause the sorts of ranking shifts you are seeing.

Sometimes site level data is more than enough to figure out what changed, but as the above Credit Karma example showed sometimes you need to get far more granular and look at page-level data to form a solid hypothesis.

As the World Changes, the Web Also Changes

About 15 years ago online dating was seen as a weird niche for recluses who perhaps typically repulsed real people in person. Now there are all sorts of niche specialty dating sites including a variety of DTF type apps. What was once weird & absurd had over time become normal.

The COVID-19 scare is going to cause lasting shifts in consumer behavior that accelerate the movement of commerce online. A decade of change will happen in a year or two across many markets.

Telemedicine will grow quickly. Facebook is adding commerce featured directly onto their platform through partnering with Shopify. Spotify is spending big money to buy exclusives rights to distribute widely followed podcasters like Joe Rogan. Uber recently offered to acquire GrubHub. Google and Apple will continue adding financing features to their mobile devices. Movie theaters have lost much of their appeal.

Tons of offline “value” businesses ended up having no value after months of revenue disappearing while large outstanding debts accumulated interest. There is a belief that some of those brands will have strong latent brand value that carries over online, but if they were weak even when the offline stores acting like interactive billboards subsidized consumer awareness of their brands then as those stores close the consumer awareness & loyalty from in-person interactions will also dry up. A shell of a company rebuilt around the Toys R’ Us brand is unlikely to beat out Amazon’s parallel offering or a company which still runs stores offline.

Big box retailers like Target & Walmart are growing their online sales at hundreds of percent year over year.

There will be waves of bankruptcies, shifts in commercial real estate prices, more people working remotely (shifting residential real estate demand from the urban core back out into suburbs).

More and more activities will become normal online activities.

The University of California has about a half-million students & in the fall semester they are going to try to have most of those classes happen online. How much usage data does Google gain as thousands of institutions put more and more of their infrastructure and service online?

Colleges have to convince students for the next year that a remote education is worth every bit as much as an in-person one, and then pivot back before students actually start believing it.

It’s like only being able to sell your competitor’s product for a year.— Naval (@naval) May 6, 2020

A lot of B & C level schools are going to go under as the like-vs-like comparison gets easier. Back when I ran a membership site here a college paid us to have students gain access to our membership area of the site. As online education gets normalized many unofficial trade-related sites will look more economically attractive on a relative basis.

Links = Rank

Old Google (pre-Panda) was to some degree largely the following: links = rank.

Once you had enough links to a site you could literally pour content into a site like water and have the domain’s aggregate link authority help anything on that site rank well quickly.

As much as PageRank was hyped & important, having a diverse range of linking domains and keyword-focused anchor text were important.

Brand = Rank

After Vince then Panda a site’s brand awareness (or, rather, ranking signals that might best simulate it) were folded into the ability to rank well.

Panda considered factors beyond links & when it first rolled out it would clip anything on a particular domain or subdomain. Some sites like HubPages shifted their content into subdomains by users. And some aggressive spammers would rotate their entire site onto different subdomains repeatedly each time a Panda update happened. That allowed those sites to immediately recover from the first couple Panda updates, but eventually Google closed off that loophole.

Any signal which gets relied on eventually gets abused intentionally or unintentionally. And over time it leads to a “sameness” of the result set unless other signals are used:

Google is absolute garbage for searching anything related to a product. If I’m trying to learn something invariably I am required to search another source like Reddit through Google. For example, I became introduced to the concept of weighted blankets and was intrigued. So I Google “why use a weighted blanket” and “weighted blanket benefits”. Just by virtue of the word “weighted blanket” being in the search I got pages and pages of nothing but ads trying to sell them, and zero meaningful discourse on why I would use one

Getting More Granular

Over time as Google got more refined with Panda broad-based sites outside of the news vertical often fell on tough times unless they were dedicated to some specific media format or had a lot of user engagement metrics like a strong social network site. That is a big part of why the New York Times sold About.com for less than they paid for it & after IAC bought it they broke it down into a variety of sites like: Verywell (health), the Spruce (home decor), the Balance (personal finance), Lifewire (technology), Tripsavvy (travel) and ThoughtCo (education & self-improvement).

Penguin further clipped aggressive anchor text built on low quality links. When the Penguin update rolled out Google also rolled out an on-page spam classifier to further obfuscate the update. And the Penguin update was sandwiched by Panda updates on either side, making it hard for people to reverse engineer any signal out of weekly winners and losers lists from services that aggregate massive amounts of keyword rank tracking data.

So much of the link graph has been decimated that Google reversed their stance on nofollow to where in March 1st of this year they started treating it as a hint versus a directive for ranking purposes. Many mainstream media websites were overusing nofollow or not citing sources at all, so this additional layer of obfuscation on Google’s part will allow them to find more signal in that noise.

May 4, 2020 Algo Update

On May 4th Google rolled out another major core update.

Later today, we are releasing a broad core algorithm update, as we do several times per year. It is called the May 2020 Core Update. Our guidance about such updates remains as we’ve covered before. Please see this blog post for more about that:https://t.co/e5ZQUAlt0G— Google SearchLiaison (@searchliaison) May 4, 2020

I saw some sites which had their rankings suppressed for years see a big jump. But many things changed at once.

Wedge Issues

On some political search queries which were primarily classified as being news related Google is trying to limit political blowback by showing official sites and data scraped from official sites instead of putting news front & center.

“Google’s pretty much made it explicit that they’re not going to propagate news sites when it comes to election related queries and you scroll and you get a giant election widget in your phone and it shows you all the different data on the primary results and then you go down, you find Wikipedia, you find other like historical references, and before you even get to a single news article, it’s pretty crazy how Google’s changed the way that the SERP is intended.”

That change reflects the permanent change to the news media ecosystem brought on by the web.

The Internet commoditized the distribution of facts. The “news” media responded by pivoting wholesale into opinions and entertainment.— Naval (@naval) May 26, 2016

YMYL

A blog post by Lily Ray from Path Interactive used Sistrix data to show many of the sites which saw high volatility were in the healthcare vertical & other your money, your life (YMYL) categories.

Aggressive Monetization

One of the more interesting pieces of feedback on the update was from Rank Ranger, where they looked at particular pages that jumped or fell hard on the update. They noticed sites that put ads or ad-like content front and center may have seen sharp falls on some of those big money pages which were aggressively monetized:

Seeing this all but cements the notion (in my mind at least) that Google did not want content unrelated to the main purpose of the page to appear above the fold to the exclusion of the page’s main content! Now for the second wrinkle in my theory…. A lot of the pages being swapped out for new ones did not use the above-indicated format where a series of “navigation boxes” dominated the page above the fold.

The above shift had a big impact on some sites which are worth serious money. Intuit paid over $7 billion to acquire Credit Karma, but their credit card affiliate pages recently slid hard.

Credit Karma lost 40% traffic from May core update. That’s insane, they do major TV ads and likely pay millions in SEO expenses. Think about that folks. Your site isn’t safe. Google changes what they want radically with every update, while telling us nothing!— SEOwner (@tehseowner) May 14, 2020

The above sort of shift reflects Google getting more granular with their algorithms. Early Panda was all or nothing. Then it started to have different levels of impact throughout different portions of a site.

Brand was sort of a band aid or a rising tide that lifted all (branded) boats. Now we are seeing Google get more granular with their algorithms where a strong brand might not be enough if they view the monetization as being excessive. That same focus on page layout can have a more adverse impact on small niche websites.

One of my old legacy clients had a site which was primarily monetized by the Amazon affiliate program. About a month ago Amazon chopped affiliate commissions in half & then the aggressive ad placement caused search traffic to the site to get chopped in half when rankings slid on this update.

Their site has been trending down over the past couple years largely due to neglect as it was always a small side project. They recently improved some of the content about a month or so ago and that ended up leading to a bit of a boost, but then this update came. As long as that ad placement doesn’t change the declines are likely to continue.

They just recently removed that ad unit, but that meant another drop in income as until there is another big algo update they’re likely to stay at around half search traffic. So now they have a half of a half of a half. Good thing the site did not have any full time employees or they’d be among the millions of newly unemployed. That experience though really reflects how websites can be almost like debt levered companies in terms of going under virtually overnight. Who can have revenue slide around 88% and then take increase investment in the property using the remaining 12% while they wait for the site to be rescored for a quarter year or more?

“If you have been negatively impacted by a core update, you (mostly) cannot see recovery from that until another core update. In addition, you will only see recovery if you significantly improve the site over the long-term. If you haven’t done enough to improve the site overall, you might have to wait several updates to see an increase as you keep improving the site. And since core updates are typically separated by 3-4 months, that means you might need to wait a while.”

Almost nobody can afford to do that unless the site is just a side project.

Google could choose to run major updates more frequently, allowing sites to recover more quickly, but they gain economic benefit in defunding SEO investments & adding opportunity cost to aggressive SEO strategies by ensuring ranking declines on major updates last a season or more.

Choosing a Strategy vs Letting Things Come at You

They probably should have lowered their ad density when they did those other upgrades. If they had they likely would have seen rankings at worst flat or likely up as some other competing sites fell. Instead they are rolling with a half of a half of a half on the revenue front. Glenn Gabe preaches the importance of fixing all the problems you can find rather than just fixing one or two things and hoping it is enough. If you have a site which is on the edge you sort of have to consider the trade offs between various approaches to monetization.

• monetize it lightly and hope the site does well for many years
• monetize it slightly aggressively while using the extra income to further improve the site elsewhere and ensure you have enough to get by any lean months
• aggressively monetize the shortly after a major ranking update if it was previously lightly monetized & then hope to sell it off a month or two later before the next major algorithm update clips it again

Outcomes will depend partly on timing and luck, but consciously choosing a strategy is likely to yield better returns than doing a bit of mix-n-match while having your head buried in the sand.

Reading the Algo Updates

You can spend 50 or 100 hours reading blog posts about the update and learn precisely nothing in the process if you do not know which authors are bullshitting and which authors are writing about the correct signals.

But how do you know who knows what they are talking about?

It is more than a bit tricky as the people who know the most often do not have any economic advantage in writing specifics about the update. If you primarily monetize your own websites, then the ignorance of the broader market is a big part of your competitive advantage.

Making things even trickier, the less you know the more likely Google would be to trust you with sending official messaging through you. If you syndicate their messaging without questioning it, you get a treat – more exclusives. If you question their messaging in a way that undermines their goals, you’d quickly become persona non grata – something cNet learned many years ago when they published Eric Schmidt’s address.

It would be unlikely you’d see the following sort of Tweet from say Blue Hat SEO or Fantomaster or such.

I asked Gary about E-A-T. He said it’s largely based on links and mentions on authoritative sites. i.e. if the Washington post mentions you, that’s good.

He recommended reading the sections in the QRG on E-A-T as it outlines things well.@methode #Pubcon— Marie Haynes (@Marie_Haynes) February 21, 2018

To be able to read the algorithms well you have to have some market sectors and keyword groups you know well. Passively collecting an archive of historical data makes the big changes stand out quickly.

Everyone who depends on SEO to make a living should subscribe to an online rank tracking service or run something like Serposcope locally to track at least a dozen or two dozen keywords. If you track rankings locally it makes sense to use a set of web proxies and run the queries slowly through each so you don’t get blocked.

You should track at least a diverse range to get a true sense of the algorithmic changes.

• a couple different industries
• a couple different geographic markets (or at least some local-intent vs national-intent terms within a country)
• some head, midtail and longtail keywords
• sites of different size, age & brand awareness within a particular market

Some tools make it easy to quickly add or remove graphing of anything which moved big and is in the top 50 or 100 results, which can help you quickly find outliers. And some tools also make it easy to compare their rankings over time. As updates develop you’ll often see multiple sites making big moves at the same time & if you know a lot about the keyword, the market & the sites you can get a good idea of what might have been likely to change to cause those shifts.

Once you see someone mention outliers most people miss that align with what you see in a data set, your level of confidence increases and you can spend more time trying to unravel what signals changed.

I’ve read influential industry writers mention that links were heavily discounted on this update. I have also read Tweets like this one which could potentially indicate the opposite.

Check out https://t.co/1GhD2U01ch . Up even more than Pinterest and ranking for some real freaky shit.— Paul Macnamara (@TheRealpmac) May 12, 2020

If I had little to no data, I wouldn’t be able to get any signal out of that range of opinions. I’d sort of be stuck at “who knows.”

By having my own data I track I can quickly figure out which message is more inline with what I saw in my subset of data & form a more solid hypothesis.

No Single Smoking Gun

As Glenn Gabe is fond of saying, sites that tank usually have multiple major issues.

Google rolls out major updates infrequently enough that they can sandwich a couple different aspects into major updates at the same time in order to make it harder to reverse engineer updates. So it does help to read widely with an open mind and imagine what signal shifts could cause the sorts of ranking shifts you are seeing.

Sometimes site level data is more than enough to figure out what changed, but as the above Credit Karma example showed sometimes you need to get far more granular and look at page-level data to form a solid hypothesis.

As the World Changes, the Web Also Changes

About 15 years ago online dating was seen as a weird niche for recluses who perhaps typically repulsed real people in person. Now there are all sorts of niche specialty dating sites including a variety of DTF type apps. What was once weird & absurd had over time become normal.

The COVID-19 scare is going to cause lasting shifts in consumer behavior that accelerate the movement of commerce online. A decade of change will happen in a year or two across many markets.

Telemedicine will grow quickly. Facebook is adding commerce featured directly onto their platform through partnering with Shopify. Spotify is spending big money to buy exclusives rights to distribute widely followed podcasters like Joe Rogan. Uber recently offered to acquire GrubHub. Google and Apple will continue adding financing features to their mobile devices. Movie theaters have lost much of their appeal.

Tons of offline “value” businesses ended up having no value after months of revenue disappearing while large outstanding debts accumulated interest. There is a belief that some of those brands will have strong latent brand value that carries over online, but if they were weak even when the offline stores acting like interactive billboards subsidized consumer awareness of their brands then as those stores close the consumer awareness & loyalty from in-person interactions will also dry up. A shell of a company rebuilt around the Toys R’ Us brand is unlikely to beat out Amazon’s parallel offering or a company which still runs stores offline.

Big box retailers like Target & Walmart are growing their online sales at hundreds of percent year over year.

There will be waves of bankruptcies, dramatic shifts in commercial real estate prices (already reflected in plunging REIT prices), and more people working remotely (shifting residential real estate demand from the urban core back out into suburbs).

People who work remote are easier to hire and easier to fire. Those who keep leveling up their skills will eventually get rewarded while those who don’t will rotate jobs every year or two. The lack of stability will increase demand for education, though much of that incremental demand will be around new technologies and specific sectors – certificates or informal training programs instead of degrees.

More and more activities will become normal online activities.

The University of California has about a half-million students & in the fall semester they are going to try to have most of those classes happen online. How much usage data does Google gain as thousands of institutions put more and more of their infrastructure and service online?

Colleges have to convince students for the next year that a remote education is worth every bit as much as an in-person one, and then pivot back before students actually start believing it.

It’s like only being able to sell your competitor’s product for a year.— Naval (@naval) May 6, 2020

A lot of B & C level schools are going to go under as the like-vs-like comparison gets easier. Back when I ran a membership site here a college paid us to have students gain access to our membership area of the site. As online education gets normalized many unofficial trade-related sites will look more economically attractive on a relative basis.

If core institutions of the state deliver most of their services online, then other companies can be expected to follow. When big cities publish lists of crimes they will not respond to during economic downturns they are effectively subsidizing more crime. That in turn makes moving to somewhere a bit more rural & cheaper make sense, particularly when you no longer need to live near your employer.

The most important implication of this permanent WFH movement are state income taxes.

The warm, sunny states with affordable housing and zero taxes will see an influx of educated, rich workers. States will need to cut taxes to keep up.

The biggest loser in this is CA.— Chamath Palihapitiya (@chamath) May 21, 2020

To Teach, One Must Learn

One of the benefits of writing is it forces you to structure your thoughts.

If you are doing something to pass a test rote memorization can work, but if you are trying to teach someone else and care it forces you to know with certainty what you are teaching.

When I was in nuclear power school one guy was about to flunk out and I did not want to let him so I taught him stuff for days. He passed that test and as a side effect I got my highest score I ever got on one of those tests. He eventually did flunk out, but he knew other people were rooting for him and tried to help him.

Market Your Work or Become Redundant

Going forward as more work becomes remote it is going to be easier to hire and fire people. The people who are great at sharing their work and leaving a public record of it will likely be swimming in great opportunities, whereas some equally talented people who haven’t built up a bit of personal brand equity will repeatedly get fired in spite of being amazingly talented, simply because there was a turn in the economy and management is far removed from the talent. As bad as petty office politics can be, it will likely become more arbitrary when everyone is taking credit for the work of others & people are not sitting side by side to see who actually did the work.

Uber recently announced they were laying off thousands of employees while looking to move a lot of their core infrastructure work overseas where labor is cheaper. Lots of people will be made redundant as unicorn workers in a recession suddenly enjoy the job stability and all the perks of the gig working economy.

Design

We have a great graphic designer who is deeply passionate about his work. He can hand draw amazing art or comics and is also great at understanding illustration software, web design, web usability, etc. I have no idea why he was fired from his prior employer but am thankful he was as he has been a joy to work with.

Before COVID-19 killed office work I sat right next to our lead graphic designer and when I would watch him use Adobe Illustrator I was both in awe of him and annoyed at how easy he would make things look. He is so good at it that and endless array of features are second nature to him. When I would ask him how to do something I just saw him do frequently it would be harder for him to explain how he does it than doing it.

Programming

Our graphics designer is also a quite solid HTML designer, though strictly front end design. One day when I took an early lunch with my wife I asked him to create a Wordpress theme off his HTML design and when I got back he was like … ummm. :)

We are all wizards at some things and horrible at others. When I use Adobe Illustrator for even the most basic tasks I feel like a guy going to a breakdancing party with no cardboard and 2 left shoes.

There are a number of things that are great about programming

• it is largely logic-based
• people drawn toward it tend to be smart
• people who can organize code also tend to use language directly (making finding solutions via search rather easy)

Though over time programming languages change features & some changes are not backward compatible. And as some free & open source projects accumulate dependencies they end up promoting the use of managers. Some of these may not be easy to install & configure on a remote shared server (with user permission issues) from a Windows computer. So then you install another package on your local computer and then have to research how it came with a deprecated php track_errors setting. And on and on.

One software program I installed on about a half-dozen sites many moons ago launched a new version recently & the typical quick 5 minute install turned into a half day of nothing. The experience felt a bit like a “choose your own adventure” book, where almost every choice you make leads to: start again at the beginning.

At that point a lot of the advice one keeps running into sort of presumes one has the exact same computer set up they do, so search again, solve that problem, turn on error messaging, and find the next problem to … once again start at the beginning.

That sort of experience is more than a bit humbling & very easy to run into when one goes outside their own sphere of expertise.

Losing the Beginner’s Mindset

If you do anything for an extended period of time it is easy to take many things for granted as you lose the beginner’s mindset.

One of the reasons it is important to go outside your field of expertise is to remind yourself of what that experience feels like.

Anyone who has been in SEO for a decade likely does the same thing when communicating about search by presuming the same level of domain expertise and talking past people. Some aspects of programming are hard because they are complex. But when things absolutely do not work you often get the answer right away. Whereas with SEO you can be unsure of the results of a large capital and labor investment until the next time a core algorithm update happens a quarter year from now. That uncertainty acts as the barrier to entry & blocker of institutional investments which allow for sustained above average profit margins for those who make the cut, but it also means a long lag time and requiring a high level of certainty to make a big investment.

The hard part about losing the beginners mindset with SEO is sometimes the algorithms do change dramatically and you have to absolutely reinvent yourself while throwing out what you know (use keyword rich anchor text aggressively, build tons of links, exact match domains beat out brands, repeat keyword in bold on page, etc.) and start afresh as the algorithms reshuffle the playing field.

The Web Keeps Changing

While the core algorithms are shifting so too is how people use the web. Any user behaviors are shifting as search results add more features and people search on mobile devices or search using their voice. Now that user engagement is a big part of ranking, anything which impacts brand perception or user experience also impacts SEO. Social distancing will have major impacts on how people engage with search. We have already seen a rapid rise of e-commerce at the expense of offline sales & some colleges are planning on holding next year entirely online. The University of California will have roughly a half-million students attending school online next year unless students opt for something cheaper.

Colleges have to convince students for the next year that a remote education is worth every bit as much as an in-person one, and then pivot back before students actually start believing it.

It’s like only being able to sell your competitor’s product for a year.— Naval (@naval) May 6, 2020

What Resolution?

I am horrible with Adobe Illustrator. But one of the things I have learned with that and Photoshop is that if you edit in a rather high resolution you can have many of your errors disappear to the naked eye when it is viewed at a normal resolution. The same analogy holds true for web design but in the opposite direction … if your usability is solid on a mobile device & the design looks good on a mobile device then it will probably be decent on desktop as well.

Some people also make a resolution mistake with SEO.

• If nobody knows about a site or brand or company having perfect valid HTML, supporting progressive web apps, supporting AMP, using microformats, etc. … does not matter.
• On the flip side, if a site is well known it can get away with doing many things sub-optimally & can perhaps improve a lot by emulating sites which are growing over time in spite of having weaker brand strength.

Free, so Good Enough?

Many open source software programs do not do usability testing or track the efforts of a somewhat average user or new user in their ability to download and install software because they figure it is free so oh well people should figure it out. That thinking is a mistake though, because each successive increase in barrier to entry limits your potential market size & eventually some old users leave for one reason or another.

Any free software project which accumulates attention and influence can be monetized in other ways (through consulting, parallel SaaS offerings, affiliate ad integration, partnering with Hot Nacho to feature some great content in a hidden div using poetic code, etc.). But if they lack reach, see slowing growth, and then increase the barrier to entry they are likely to die.

When you ask someone to pay for something you’ll know if they like it and where they think it can be improved. Relying on the free price point hides many problems and allows them to accumulate.

The ability to make things easy for absolute beginners is a big part of why Wordpress is worth many multiples of what Acquia sold for. And Wordpress has their VIP hosting service, Akismet, and a bunch of other revenue streams while Acquia is now owned by a private equity company.

The ability to be 0.0000001% as successful as Wordpress has been without losing the beginner mindset is hard.