Most people talking about AI search are still guessing.

We’re not.

In May, we’re running a 2-day intensive AEO course for people who want to understand what actually works and how to apply it.

This isn’t theory. It’s the exact playbook we use:

• How AI search really works (and how it differs from SEO)

• How to build visibility across AI platforms

• Where AI helps and where it kills quality

• The workflows, templates, and tools behind our processes

The course is live, hands-on, and capped at 30 people.

If you want to move past noise and build real visibility in AI search, this is for you.

Join the cohort

Last week, Profound introduced a new role to the marketing world:

The Marketing Engineer

And, as usual, LinkedIn went ballistic.

My feed was flooded with hot takes.

Some people loved it. Others hated it. And one person pointed out that the term has existed since 1959.

Many of you reached out to tell me you liked my take on the content engineer.

So, I thought I’d do a similar piece for this one.

What Happened

James Cadwallader, co-founder and CEO of Profound, published a post announcing that the company was formalizing the Marketing Engineer as a new role.

Nick Lafferty, Profound’s first marketing hire, became the Founding Marketing Engineer.

The first person to hold that title at a company fully behind it.

According to Cadwallader’s post, Marketing Engineers build agents that monitor media coverage and flag sentiment shifts, track competitor moves and rewrite battlecards, and turn webinars into brand-voice articles queued for review.

Part builder, part strategist.

Profound also launched a free course through Profound University to teach people how to become Marketing Engineers.

Three modules covering systems thinking, agent building, and operating as an engineer inside a marketing team.

This happened approximately two months after Profound announced its $96 million Series C at a $1 billion valuation. (Read: the timing was not accidental)

This Is Not New

The concept of a marketing engineer is not new.

Phil Gamache, founder of Humans of Martech, shared an interesting post on LinkedIn, where he cited an academic paper from 1959 by H.G. Burger titled “The Need for Marketing Engineering,” published in the Journal of Marketing.

This was in 1959, so the term is 67 years old.

But the broader pattern here is even more important:

Tech companies have been coining role names for years to create categories around their products.

• HubSpot coined the Inbound Marketer

• Clay coined the GTM Engineer

• Drift popularized the Conversational Marketer

• AirOps popularized the Content Engineer

• And now Profound is introducing the Marketing Engineer

Every single one of these terms was born from the same playbook.

The Playbook

What most of these companies are actually doing is that they are running a brand strategy play disguised as a talent movement.

The sequence is somewhat familiar:

1. You build a product

2. You realize the product needs a certain role (or skillset) to operate it well

3. You give that role a name

4. You build a course or certification around that name

5. You create a manifesto and introduce the role

6. You hire for the role internally to show that you lead by example

7. Then you watch as other companies start posting the same role title in their own job listings (and, sure enough, they will)

Profound followed this playbook step by step.

They announced the role —> They launched the course —> They gave Nick Lafferty the title of Founding Marketing Engineer

And within days, Marvin Chow, a marketing executive at Google, posted that he was hiring their first Marketing Engineer too. He called it “the hire of 2026.”

That is the goal.

When other companies start hiring for the role you named, you own the category.

Why This Name

Here’s the thing.

Profound couldn’t use “Content Engineer” because AirOps already owns that term.

They couldn’t use “GTM Engineer” because Clay already owns that one.

And neither term really fits what Profound does anyway.

Profound is positioning itself as a platform, not a point solution for content.

Their product touches AI search tracking, competitive intelligence, agent workflows and more.

They needed a term broad enough to cover all of that.

“Marketing Engineer” gives them room. It sounds bigger than content, more strategic than operations.

It positions the person using the product as someone who builds systems. Not someone who runs campaigns.

In my view, most of what a Marketing Engineer would theoretically do, according to Profound’s own description, the product cannot fully support today.

Agents that monitor media coverage, rewrite battlecards, draft journalist outreach?

As I see it, that is where they want to take the product.

The role is already out there, ahead of the roadmap.

That is smart marketing.

You define the destination before you ship the vehicle.

The LinkedIn Reaction

The response was mixed. (Predictably so!)

The enthusiasts

Josh Grant, who’s an ex-VP Growth at Webflow, called it “The Great Convergence.”

His argument: every major function already has an engineering layer.

• Finance has financial engineering

• Data has data engineering

• Sales has sales engineering

Marketing was the last one standing without one.

The skeptics

Geoffrey Lyman, a full-stack marketing leader, responded with a simple question:

What am I missing? This is no different than a GTM Engineer, just branded for marketers.

His point was that good marketing operators have always done these things.

They just have better tools now.

The critical thinkers

Miranda Shanahan, a brand consultant, posted a TikTok that drew historical parallels.

She pointed out that engineering is one of the most male-dominated workforces in America, while marketing is led by women.

Her take: marketing jobs are being rebranded with technical-sounding titles, and the implications of that deserve more scrutiny.

Fast Company picked up the story.

The system thinkers

Mayur Gupta, who leads growth at Kraken (formerly at Spotify), posted that marketing and engineering must be inseparable.

His framing was less about the title and more about the skill set:

Marketers have to be system thinkers now, building ideas rooted in AI-native systems.

Each perspective has merit.

But I think most people are missing the bigger picture.

My Take (For Now)

I give Profound credit for the marketing execution.

• They generated buzz

• They got a Google exec to post about hiring the same role

• They launched a course

• Created a manifesto

• Companies will soon be posting “Marketing Engineer” job ads

That is category creation done well.

But let’s be honest about what this is:

It is a brand play. And a very effective one.

And let me be emphatic about this:

And there is nothing wrong with that.

HubSpot did the same thing with “inbound marketing” and built a $30 billion company around it.

What concerns me is something different.

Something I keep coming back to every time a new “engineer” title drops in the marketing world.

All this engineering-focused language around marketing and go-to-market jobs tends to take away creativity. (Stay with me.)

It turns the role of marketing into something deterministic.

As if the entire discipline can be reduced to systems, workflows and agents.

Marketing is not engineering.

The best marketing has always come from taste, intuition and creative risk.

Systems can support that work.

They can scale it.

But they cannot replace the part that makes marketing actually work:

When you call someone an engineer, you are framing their job as building systems.

You are telling them that the value they create comes from technical infrastructure.

That framing subtly pushes out the people who are great at the creative, messy, human side of marketing.

The storytellers. The brand builders.

The people who can feel what an audience wants before any data confirms it.

I wrote about this a few weeks ago, in the context of the Content Engineer.

The same concerns apply here, maybe even more so.

Because marketing engineering is broader.

It implies the entire marketing function should think in systems.

Some of it should. A lot of it should not.

The Real Question

The question I keep asking myself is this: who does the “engineer” framing actually serve?

1. It serves the software companies

Because if your job is to be an engineer, you need engineering tools.

You need Profound. You need Clay. You need AirOps.

You need a platform, a certification and a community built around that platform.

2. It serves the marketers who are already technical

The ones who code, build automations and architect workflows.

They get a title that validates what they have been doing.

3. It serves the marketplace

When a new role, such as marketing engineer, is introduced, there are always new opportunities that emerge.

Fundamentally that’s a good thing and it benefits the marketplace.

But do the introduction of these roles or skillsets serve the marketing discipline as a whole? Yeah, I am not so sure about that.

Because beyond all the LinkedIn buzz, there is a philosophical question:

Do we really want marketing to be an engineering discipline? Do we want to train the next generation of marketers to think of themselves merely as system builders and not as creative thinkers?

My answer, for now, is no.

I think the best marketers will always be the ones who can hold both.

Who can build the system and know when to override it.

Who can set up the automation and also write the headline that makes someone stop scrolling.

Calling that person an engineer captures half the picture.

The half that is easier to sell software for.

Final Thoughts

Every few months, a new role name drops…

• GTM Engineer

• Content Engineer

• Marketing Engineer

Each time, LinkedIn lights up.

People debate whether the title is necessary, whether the skills are real.

To a certain extent, what’s happening is this:

Software companies are racing to name the person who will buy their product.

That is the game.

The role name is the marketing. The certification is the lead gen. The manifesto is the content strategy.

None of that is cynical. It is just brand marketing. And I respect the craft behind it.

But I would also encourage anyone reading this to separate the brand play from the career advice.

The skills these roles describe are real.

Systems thinking, automation, AI-native workflows: these are worth learning.

You do not need a new job title to learn them.

And you definitely do not need to abandon the creative, human side of marketing to adopt them.

Build the systems. Learn the tools. But do not let anyone convince you that marketing is just engineering.

It is something bigger than that.

Thank you for reading today’s note, and see you again next week.

Research Disclaimers and Limitations

GrowthWaves and its author are not sponsored by or compensated by any company mentioned in this note. This is independent editorial analysis and does not constitute investment, financial, or legal advice. The author may have relationships with, work with, or hold equity in companies referenced; however, no content in this piece was influenced, commissioned, or incentivized by any such relationship. AI tools were used as a research assistant in the preparation of this piece. All claims are sourced and linked throughout.

Sources

• James Cadwallader, LinkedIn post announcing the Marketing Engineer

• Nick Lafferty, LinkedIn post on becoming Founding Marketing Engineer

• Josh Grant, LinkedIn post on The Great Convergence

• Marvin Chow, LinkedIn post on hiring a Marketing Engineer at Google

• Mayur Gupta, LinkedIn post on marketing and engineering convergence

• Phil Gamache, LinkedIn post citing the 1959 marketing engineering paper

• Miranda Shanahan, TikTok on gender dynamics of engineering-coded job titles

• Fast Company, “There’s a curious phenomenon happening in the marketing industry”

• Profound University, Marketing Engineering Course

• Burger, H.G. (1959), “The Need for Marketing Engineering,” Journal of Marketing, 23(3)

Most people talking about AI search are still guessing.

We’re not.

In May, we’re running a 2-day intensive AEO course for people who want to understand what actually works and how to apply it.

This isn’t theory. It’s the exact playbook we use:

• How AI search really works (and how it differs from SEO)

• How to build visibility across AI platforms

• Where AI helps and where it kills quality

• The workflows, templates, and tools behind our processes

The course is live, hands-on, and capped at 30 people.

If you want to move past noise and build real visibility in AI search, this is for you.

Reserve your spot

I’ve been thinking about listicles for a long time.

Probably longer than most people in this industry, given that Minuttia works with B2B SaaS companies on content and SEO for a living.

• We’ve seen every permutation of the “Best [Category] Tools in 2026” blog post.

• We’ve watched companies scale these pages from a handful to hundreds.

• We’ve seen what works, what doesn’t, and what crosses the line.

And over the past twelve months, a correction has started. Not a hypothetical one. A measurable one, with data to back it up and regulatory teeth behind it.

This is going to be a long piece. I want it to be the definitive resource on this topic because I believe self-promotional listicles are at an inflection point that most companies haven’t fully processed yet.

The ground beneath this entire tactic is shifting in at least four directions simultaneously:

1. Google’s algorithm

2. AI search engines

3. The FTC

4. International advertising law

Let’s go.

How We Got Here: The Rise of the Self-Promotional Listicle

Before we talk about the correction, we need to understand why this tactic became so widespread in the first place.

Self-promotional listicles didn’t emerge out of thin air. They spread because they sit at the intersection of several powerful incentives:

1. Commercial intent is high

When someone searches “best project management software” or “top CRM tools for startups,” they’re (usually) deep in the buying cycle.

These are transactional queries with real revenue potential behind them.

For SaaS companies, ranking for these terms means capturing demand at the moment of purchase decision.

That’s irresistible.

2. Affiliate economics supercharged it

Review sites like G2, Capterra, and dozens of smaller players built entire business models on monetizing “best of” queries.

SaaS companies watched these third-party sites capture their most valuable traffic and thought: why are we paying someone else to rank for our category?

We can publish our own list and keep that traffic in-house.

3. The barrier to entry was almost zero

You don’t need original research to write a listicle.

You don’t need proprietary data or deep expertise.

You need a list of competitors, some publicly available information about each one and a blog. That’s it.

Any company with a content team and a CMS could produce these at scale.

4. Crowd mentality kicked in

Once a few companies in a vertical started publishing self-promotional listicles, everyone else followed.

If your competitor has a “Best [Category] Tools” page and you don’t, you feel like you’re leaving money on the table.

This created a cascading effect where entire SaaS categories ended up with dozens of nearly identical listicles, each with the publishing company conveniently ranked first.

5. And let’s not forget that it worked

For years, self-promotional listicles drove real traffic and real pipeline.

• Google ranked them

• Users clicked on them

• Sales teams loved them

This was not an irrational tactic. Given the incentive structure and Google’s historical tolerance, publishing these pages was, for a long time, a rational business decision.

But rational doesn’t mean sustainable.

And what worked (and is still working) for so many years is now running headfirst into a wall.

How Companies Gamed the System

Let me be clear about something:

There’s a spectrum here. On one end, you have a company writing a comparison post that includes their own product, acknowledges their bias, and provides useful context to buyers.

On the other end, you have companies manufacturing hundreds of listicles with fabricated scoring systems, fake schema markup, and AI-generated content designed to look like independent editorial review.

The problem is that the industry drifted hard toward the second end of that spectrum.

Here’s what I mean.

1. Fabricated rating systems

Lily Ray, VP of SEO and AI Search at Amsive, documented this pattern extensively in her research.

Companies created proprietary scoring methodologies with no disclosed criteria, assigned themselves perfect or near-perfect scores, and used those scores to justify their number-one ranking.

The ratings looked scientific. They weren’t.

Lily Ray

Is Google Finally Cracking Down on Self-Promotional Listicles?

Jump straight to examples of affected websites…

Read more

3 months ago · 92 likes · 13 comments · Lily Ray

2. Structured data abuse

Some companies went further.

They implemented schema review markup on these pages, generating rich snippet stars in search results.

The problem:

Google’s structured data guidelines explicitly state that you shouldn’t use self-serving reviews for the purpose of generating rich snippet stars.

These companies did it anyway.

By March 2026, Google’s spam update began stripping rich results from pages with abusive FAQ, Review, and How-To schema.

3. Scale with AI

Ray’s research from above found that AI content detection tools flagged some of these listicle pages with 100% confidence as AI-generated content.

Companies weren’t just publishing a few comparison posts. Some had 191 to 340 self-promotional listicles on their blogs.

When you’re producing at that volume, the content is being manufactured, not written.

Let’s move on to the next one.

The Google Correction: January 2026

For years, the SEO industry speculated about whether Google would ever meaningfully address self-promotional listicles.

The company never made a public statement. No specific algorithm update was announced targeting this content type.

Then the December 2025 Core Update finished rolling out. And in January 2026, the data told a different story.

Ray’s analysis documented visibility drops across multiple SaaS companies that had invested heavily in self-promotional listicles.

The numbers were bad:

One $8 billion B2B brand saw organic visibility drop 49% between January 21st and February 2nd.

Others experienced double-digit declines.

By March 2026, Ray had compiled a list of approximately 30 sites matching the same pattern.

What made these drops distinctive is that they weren’t domain-wide.

The declines were concentrated in blog, guide, and tutorial subfolders.

The same companies’ product pages, documentation, and core site content remained largely unaffected.

Google wasn’t penalizing the domains. It was devaluing a specific content type.

The companies hit hardest shared several characteristics:

• They’re in the SaaS space (thus, more likely to follow AEO/GEO trends)

• Blogs with several self-promotional listicles on their website

• AI-generated content detected at high confidence levels

• Schema markup that violated Google’s own guidelines

• The publishing company ranked at position number one in every listicle

In a LinkedIn post he made a few weeks ago, Cyrus Shepard predicted what would come next. His forecast:

Google would add specific language to the Quality Rater Guidelines asking raters to explicitly downgrade self-serving listicles, begin classifying more of them as spam, and turn up Authority and Trust metrics in these cases.

None of this is going to happen in the next few weeks, but in the next few months? I wouldn’t bet against it.

I don’t think he is wrong.

It’s just a matter of when and not if, as I see it.

Which means that the self-promotional listicles correction is real.

And… it’s interesting because Minuttia’s team recently analyzed a domain (before it got hit).

This is a B2B SaaS company that, at the time of our analysis, had:

• 140 reviews of their competitors (direct and indirect)

• 140 competitor comparisons (x vs y) and alternative pages (x alternatives)

• 281 software listicles on relevant terms

According to Ahrefs, between January and mid-April, they lost almost 40.35% of their organic traffic.

No bueno.

But to be clear: this is a website with literally hundreds of these pages.

Meaning, they picked up the listicle ball and ran to the moon with it.

In my view, a SaaS website with a couple of dozen listicles and comparison pages doesn’t fall into the same category as other websites, and thus has almost no risk of being penalized.

All that aside, what we discussed here is just one part of the picture…

The “AI Search Filter” Problem

Here’s where things get especially interesting, and where most companies haven’t connected the dots yet.

Glen Allsopp at Ahrefs published a study of 26,283 source URLs cited by ChatGPT.

The headline finding:

“best X” blog lists accounted for 43.8% of all page types referenced in ChatGPT’s responses.

That’s not a typo. Nearly half of all source pages ChatGPT cited were listicle-format content.

The study revealed other patterns worth noting:

• Brands positioned higher on listicles were more likely to be recommended by ChatGPT.

• Self-promotional blog lists appeared in roughly one out of every three software-related ChatGPT responses.

• And 35% of these source pages were hosted on low-authority domains.

This paints a dream scenario for companies gaming listicles.

Not only can you rank in Google, but you can also get your brand recommended by ChatGPT.

This intensifies the incentive to produce more listicles.

But there’s a problem with building your AI visibility strategy on self-promotional listicles, and Dan Petrovic at DEJAN explained it in a research paper on AI search filters.

His finding: only about one-third of a webpage’s content actually survives the “AI search filter,” the process by which AI models extract and synthesize information from source pages.

According to the study, overall citation coverage was 32.16%.

What does that mean in practice? That you don’t control the narrative as much as you’d like to think that you do.

You can write 5,000 words positioning your product as the clear winner, but the AI model might extract a single sentence. And that sentence might not be the one you wanted.

Wil Reynolds at Seer Interactive ran a GEO experiment that made this point viscerally.

Seer Interactive has been in business for 20+ years with an outstanding reputation.

In that entire period, they received exactly one negative review (one from 2018, while they incorporated in 2002).

When Wil tested branded prompts in AI search, that single negative review appeared in one out of every three AI-generated responses about his company. Clutch, a third-party review site, appeared in 16% of branded outputs.

Wil’s conclusion can simply be summarized as (my words):

Listicles are spam.

AI systems are hardwired to present both pros and cons.

You can publish a hundred listicles ranking yourself first, but if one third-party source says something negative, AI will surface that too.

And unlike Google, where you could bury negative results with more content, AI synthesizes everything into a single answer. There’s nowhere to hide.

Wil’s recommendation: build defensible data, create a centralized source of truth for your brand, and stop relying on manufactured listicles to shape perception.

Let’s move on to the next one.

Third-Party Listicles Aren’t Safe Either

Some companies responded to the Google correction by expanding their listicle strategy.

If publishing self-promotional listicles on your own blog is risky, why not get other sites to mention you instead?

This approach has its own problems:

The Ahrefs study I mentioned above

found that 35% of the “best X” pages cited by ChatGPT were hosted on low-authority domains. These are sites with thin content, minimal editorial standards, and questionable link profiles.

Getting your brand mentioned on these pages doesn’t build authority. It associates your brand with the digital equivalent of a strip mall.

There’s also the review platform consolidation to consider.

In January 2026, G2 announced the acquisition of Capterra, Software Advice, and GetApp from Gartner.

In June 2025, TrustRadius was acquired by HG Insights.

The review platform market, which used to have five or six major players competing for SaaS review content, is consolidating rapidly.

Meanwhile, Trustpilot reported its 2025 annual results and the numbers were striking:

• Revenue grew 24% to $261.1 million.

• Operating profit hit $16 million, up 320% from $3.8 million the prior year.

• Underlying EBITDA surged 69% to $40.7 million.

And here’s the number that caught my attention:

AI search tools drove a 1,490% surge in click-throughs to Trustpilot’s site.

As I wrote on LinkedIn, this matters because Trustpilot is a public company acknowledging “on the record” that AI search engines are driving its business.

Trustpilot’s verified, user-generated review data is becoming a truth layer for AI.

Moving forward, structured, third-party data that AI engines can verify and cross-reference may be worth more than self-promotional listicles.

The Legal Dimension: FTC Rules and Comparative Advertising Law

This is the part that most content marketing teams haven’t been paying attention to, and they should be.

In October 2024, the FTC’s Consumer Review Rule (16 CFR Part 465) took effect.

Then, on December 22, 2025, the FTC sent warning letters to 10 companies for practices believed to violate the rule.

These were the first public enforcement actions under the regulation.

Lily Ray broke down the implications for SEOs in a LinkedIn post that got a lot of attention.

The rule explicitly prohibits several practices that are common in self-promotional listicles:

• Creating a company-controlled site that presents itself as providing independent reviews (Section 465.6)

• Publishing reviews of products or services you’ve never actually used (Section 465.2)

• Attributing reviews to people who didn’t write them (Section 465.2(a))

The penalties: up to $53,088 per violation. And each page could constitute a separate violation.

Ray drew the line clearly:

If your client (or agency) is publishing ‘best of’ listicles that rank themselves #1 based on scores they made up, about products or competitors they never used, on a site that looks like an independent review authority... that’s not just a Google quality guidelines issue anymore. It’s a potential legal liability.

Alekh Shah, Head of SEO and AI Search at BrowserStack, captured the new reality in a comment on Ray’s post:

Ranking yourself #1 isn’t the problem. Pretending you’re unbiased while doing it is.

That distinction is critical:

The FTC’s guidance makes it relatively straightforward: you can publish comparison content that includes your own product. Just be honest about who you are and don’t fabricate reviews of products or competitors you’ve never used.

Beyond the U.S.: International Restrictions

The legal risk extends beyond American borders.

The European Union’s Directive 2006/114/EC on Misleading and Comparative Advertising sets minimum protections across all member states and fully harmonizes rules on comparative advertising.

Companies publishing listicles that make comparative claims about competitors must ensure those comparisons are objectively verifiable and not misleading.

And let’s not forget that each country has its own comparative laws and regulations.

This matters for any SaaS company operating internationally.

A listicle published in English on a .com domain that ranks competitors using fabricated scores may violate advertising regulations in multiple jurisdictions simultaneously.

Most content teams don’t consult legal before publishing a “Best [Category] Tools” blog post.

Given the current regulatory environment, that’s a risk most companies can’t afford to take, especially publicly traded ones or those in regulated industries.

Listicles Are Not Inherently Bad

I want to be careful here because I think there’s a risk of overcorrection.

The problem is not listicles as a format. The problem is how the format has been abused.

A well-constructed comparison post that includes your own product, discloses your bias, provides genuine analysis, and offers useful information to buyers is perfectly fine.

In many cases, it can be valuable. Buyers want to know how products compare. They want perspective from people who work in the space. They want informed opinions backed by experience.

Ahrefs, to their credit, addressed this directly in their research.

They publish comparison posts, but those posts represent less than 0.5% of their blog content. They don’t always rank themselves first. And they don’t manufacture scores or fake review data.

That’s the model:

Comparison content as a small, honest component of a broader content strategy. Not comparison content as the strategy.

So what does it look like to publish listicles responsibly? Let me lay out the guardrails.

The Guardrails: How to Do This Right

I want this to be practical, so I couldn’t let you leave empty-handed.

Which is why I’m sharing the exact framework I recommend to our clients at Minuttia

1. Disclose your bias upfront

Every comparison post should include a clear, visible disclaimer at the top of the page.

Your disclaimer should include elements like:

• A statement that the publishing company is included in the comparison

• The name of the publishing company and what it sells

• The date the piece was last reviewed or updated

• A note that the analysis reflects the author’s perspective, not independent editorial review

• If applicable, whether affiliate relationships or commercial partnerships exist with any listed product

This isn’t optional anymore.

Under the FTC’s Consumer Review Rule, presenting company-controlled content as independent review is a violation.

A clear disclosure eliminates that risk.

2. Use first-person plural, not third-person

Write about your own product in first person.

“We built [Product] to solve X” is honest.

“[Product] is the industry-leading solution that experts recommend” is misleading when written by the company that makes the product.

Third-person language creates the illusion of independent editorial review.

First-person signals transparency.

3. No proprietary rating systems

If you can’t explain exactly how a score was calculated and reproduce the methodology independently, don’t publish it.

Fabricated scoring systems are the single biggest red flag in self-promotional listicles.

They’re what triggered the FTC’s attention.

They’re what Google’s algorithm appears to be targeting.

My suggestion would be to drop them entirely.

4. No fake schema markup

Don’t implement Review, Rating, or AggregateRating schema on self-promotional content.

Google’s guidelines are explicit about this.

Using structured data to generate rich snippet stars based on self-serving reviews violates their policies.

The March 2026 spam update already stripped rich results from pages abusing these markup types.

5. No absolute claims

“Best,” “top,” and “#1” are defensible only when backed by specific, verifiable data.

If you can’t point to an independent source (a Gartner report, a G2 ranking, a publicly available dataset) that supports your claim, don’t make it.

Vague superlatives without substantiation are both a search quality signal and a legal risk under comparative advertising rules.

6. Align with your core offering

Comparison content should focus on categories where you actually compete.

A CRM company writing “Best CRM Tools” is relevant.

That same CRM company writing “Best Email Marketing Platforms” to capture adjacent traffic, when they don’t sell email marketing, is a stretch that weakens credibility and attracts algorithmic scrutiny.

7. Give competitors fair treatment

This is where most companies trip up.

If every competitor section is two sentences and your product’s section is six paragraphs with screenshots, the asymmetry signals bias regardless of any disclaimer. Keep section lengths roughly comparable.

Mention genuine strengths of competing products.

Readers and search engines both recognize when a “comparison” is actually a thinly disguised sales page.

8. Know the legal environment in your markets

If your company operates in the EU, you need to understand Directive 2006/114/EC on comparative advertising.

If you operate in specific member states, there might be additional local restrictions.

Publicly traded companies face extra scrutiny. Companies in regulated industries (financial services, healthcare, insurance) face even more.

The default should be: legal reviews any comparison content before publication.

If your content team is publishing “best of” posts without legal sign-off, that process needs to change.

9. Share your research methodology

As I mentioned earlier, Ahrefs keeps comparison content below 0.5% of their total blog output. That’s the right order of magnitude.

10. Don’t make this your content strategy

As I mentioned earlier, Ahrefs keeps comparison content below 0.5% of their total blog output. That’s the right order of magnitude.

If self-promotional listicles represent more than a small fraction of your content, you’ve built a dependency on a tactic that’s being devalued by search engines, targeted by regulators, and undermined by AI search.

Diversify.

Invest in original research, thought leadership, product documentation, and use-case content that demonstrates expertise without the legal and algorithmic risks.

Final Thoughts

The correction happening around self-promotional listicles is not a single event. It’s a convergence.

None of what you read in this note means listicles will disappear.

Comparison content serves a real buyer need.

What is disappearing is the window for companies to publish hundreds of self-promotional listicles with fabricated ratings, fake schema, and AI-generated copy while facing no consequences. That window is closed.

For companies that have built significant traffic and pipeline on this tactic, the transition will be uncomfortable.

Those who invested in defensible content (e.g., original research, genuine expertise, transparent comparison) will find the correction creates a competitive advantage.

If you follow the best practices I shared above, comparison content can remain as a legitimate part of your strategy.

If you don’t, the risks are higher than they’ve ever been.

Thank you for reading today’s note, and see you again next week.

Research Disclaimers and Limitations

GrowthWaves and its author are not sponsored by or compensated by any company mentioned in this note. This is independent editorial analysis and does not constitute investment, financial, or legal advice. The author may have relationships with, work with, or hold equity in companies referenced; however, no content in this piece was influenced, commissioned, or incentivized by any such relationship. AI tools were used as a research assistant in the preparation of this piece. All claims are sourced and linked throughout.

Sources

• Lily Ray’s Substack

• https://ahrefs.com/blog/best-lists-research/

• https://dejan.ai/blog/ai-search-filter/

• https://www.seerinteractive.com/insights/geo-experiment-how-ai-highlighted-the-1-bad-review-we-got-in-24-years

• https://www.linkedin.com/posts/lily-ray-44755615_wow-something-interesting-was-just-brought-share-7444766280148004864-0P42/

• https://www.linkedin.com/posts/cyrusshepard_google-spent-20-years-fighting-spam-refining-share-7430404003697500160-8qhf/

• https://www.linkedin.com/posts/georgioschasiotis_two-weeks-ago-trustpilot-reported-that-annual-ugcPost-7443230620119486464-O5IF/

• https://www.ftc.gov/business-guidance/blog/2025/12/warning-letter-or-ten-businesses-comply-ftcs-consumer-review-rule

• https://www.ftc.gov/legal-library/browse/federal-register-notices/16-cfr-part-465-trade-regulation-rule-use-consumer-reviews-testimonials-final-rule

• https://finance.yahoo.com/news/trustpilot-profit-quadruples-review-platform-083531145.html

• https://solutions.trustradius.com/vendor-blog/hg-insights-acquires-trustradius/

• https://company.g2.com/news/g2-acquires-capterra-software-advice-getapp

• https://eur-lex.europa.eu/EN/legal-content/summary/misleading-and-comparative-advertising.html

• https://developers.google.com/search/docs/appearance/structured-data/sd-policies

• https://www.seroundtable.com/googleself-promotional-listicles-update-40873.html

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