Get Found Without Paying for Ads via @sejournal, @thryv

All businesses, large or small, must establish a level of authority for the products and/or services they offer in the minds and hearts of their target audience if they expect to convince them to engage and buy.

This universal marketing truth plays out daily for small businesses looking to capture the attention of local customers through a variety of local SEO strategies.

Authoritativeness is the “A” in the much-heralded E-E-A-T (experience, expertise, authoritativeness, and trustworthiness) found in Google’s Search Quality Rater Guidelines.

In short, a business or organization needs to prove its authority to Google, and all other search engines, to be considered worthy of visibility in search engine results.

The authority of a local business can be established in a few different ways, but most notably:

  • Via the helpful, high-quality, well-structured content it creates for its target audience/customers.
  • Through validation of its offerings via industry-specific backlinks it maintains to its primary product, service, or other relevant content.
  • Via the engagement of its content.
  • Through validation of its “localness” via its local existence, appearance, community participation, and engagement.

We are obviously going to focus here on the fourth, often underestimated and overlooked, aspect of local business authority.

However, you’ll see that experience, expertise, and trustworthiness are also prominently referenced here, as all can be boosted via solid partnerships.

It only stands to reason: If a business wants to be visible locally, it needs to truly be visible in the community, with the digital local community merely being an extension of the real world.

While traditional SEO techniques like keyword optimization, content marketing, and link building are still essential, savvy business owners and digital marketers will look beyond these tactics to stand out from the local competition.

Leveraging local business partnerships and collaborations to build your local online authority and extend your web presence will most certainly help increase your visibility.

In this post, we’ll explore the power of forging partnerships with other local businesses and organizations to extend reach, build trust, and drive growth.

Building Authority and Trust Through Partnerships

Authority in the digital realm refers to your brand’s credibility, trustworthiness, and expertise in your industry and/or your location.

For small, local businesses, all this matters.

A business needs to convince its customers and Google, by extension, that it is the definitive local source of answers to their questions about its products and services. In other words, it is not the only game in town, but the primary one.

Partnering with other reputable, authoritative businesses effectively gets those businesses to validate your existence, expertise, and authority.

Google and other search engines consider authoritative websites more relevant and rank them higher in organic search results and local map packs.

Here’s how forging reciprocal local business partnerships can help build authority:

Co-Branding And Trust-Building

Partnering with reputable local businesses and organizations can create a co-branding effect.

When consumers (or search engines) see your business/brand associated with other businesses they already trust, it naturally enhances credibility, trustworthiness, and authority.

Local business organizations like Chambers of Commerce, Business Network International (BNI), and many others have been established, at least in part, to help small local businesses extend their reach, build trust, and, thereby, earn authority.

Many of these organizations have categorized online directories, content distribution opportunities (e.g., email newsletters or blogs), and business awards. They also have staff responsible for helping local business partners take advantage of these programs.

All local businesses should inquire, sign up, and take advantage of what these important local groups offer.

Maintaining listings, content, or recognition here provides search engines with potentially powerful local and topical signals.

Basic membership is important, but the more a business owner can do to boost their local offline and online profile through active engagement, the better.

Expertise And Resource Sharing

Collaborating with local, like-minded businesses will enable you to demonstrate your experience and expertise, along with your partner’s, and then showcase it on each other’s platforms.

This can be accomplished through guest blog posts, joint webinars, offline events, or social media takeovers – all of which can enhance your reputation as a trusted local information contributor.

One of the challenges of content marketing, especially for small local businesses, is simply having the time to create the content.

Thoughtful partnering with other business owners provides a viable means to share this burden of feeding the content machine.

For example, a local tax lawyer may partner with a local bookkeeping service or tax preparation firm to create a monthly tax tips newsletter or annual tax prep checklist, to which both firms can contribute.

Content Syndication And Social Collaboration

Similarly, two businesses that choose to share each other’s content on their respective platforms expose each other’s brands to a wider audience and can establish each as a go-to source for local information.

The key is to identify topics and content that will be relevant and interesting to each other’s audience.

While social signals, such as likes and shares, are not Google ranking factors, having partners occasionally like, share, and effectively validate any of your content will certainly extend its potential audience, where it will perhaps again be read, liked, and shared.

Content will typically only be shared once it has been validated by trustworthy sources, which your partner becomes on your behalf.

An example here may be a local auto body shop sharing car maintenance tips from a local mechanic via a customer newsletter. Meanwhile, the mechanic shares paint and detailing information through a series of Google Business Profile or social media posts.

Content sharing, depending on where and how it’s done, may result in the creation of valuable local backlinks and citations.

Backlinks

Backlinks remain valuable in SEO because search engines interpret them as votes of confidence.

Where possible, these links should be put in the proper context relative to your partnership and the related products or services offered.

For example, a local auto body shop might establish a partnership with a local full-service mechanic. Each could link to the other’s respective service pages as a reference for those customers looking for a trusted referral.

However, even a non-service-specific link for a local partner can be beneficial, too – as it is at least a local, if not topical, validation.

And yes, Google’s algorithm is sophisticated enough to identify when one local business has linked to another.

All backlinks (except for those without any relevant value) contribute to authority.

Supporting Local Organizations And Events To Gain Citations

Another aspect of growing local trust and authority is becoming involved in local service organizations, sports teams, clubs, or local events.

Whether you provide monetary or volunteer support, most organizations have websites or social media presences where a logo, contact info, perhaps a short business overview, and preferably a link can be shared.

These types of mentions, with a link or not, are considered citations and can have significant value.

These types of relationships serve to bolster localness online and provide more evidence of your business’s role as a contributing, engaged member of the community.

Furthermore, if approved by the supported organization(s), who are no doubt also looking for any positive local exposure, content and links to their websites, programs, events, etc., should be published on yours.

Typically, this is done in the “About Us” section or perhaps on a page dedicated to your business’s community support initiatives.

Local Competition And Content Differentiation

Depending on your location and level of competition, establishing local partnerships and collaborations may simply be a way of differentiating your business from all others when competitors don’t have the time, resources, or foresight to leverage this important opportunity.

The introduction of generative AI used to produce content has raised fears in some circles around the potential for a lack of “unique” informational content, as some marketers, while not advisable, will post what AI has generated verbatim.

Local collaborations can be a great way to complement what AI has to offer by injecting local partner contributions into standard service-related blog posts and FAQs.

A Local Collaboration Case Study: Fitness Food

Here’s a quick example of a local business partnership scenario and some of the potential benefits to be realized.

The Collab

A local fitness studio partners with a healthy café, offering a stay-fit meal deal to gym members.

The café provides fitness class discount vouchers with qualifying fitness-focused meal purchases, which are prominently promoted on the homepage of their websites while linking to each other.

They also collaborate on a weekly Fitness Food blog post with reciprocal links, which they publish and share on their respective websites and social media platforms.

Lastly, they create a health challenge and contest on social media for their customers, where participants are asked to share their fitness and nutrition journeys – again, cross-promoted.

The Results

  • Combined, the businesses positioned themselves as leading community advocates for healthier lifestyles, reinforcing their authority as wellness experts.
  • Blogs linked to their offers and primary service pages, shared via each other’s Facebook and Instagram accounts, trigger a boost in each business’s service page rank in organic search and, subsequently, organic search traffic and conversions.
  • The program attracts local influencers who post user-generated content with links to their offers and blog posts, further enhancing their reach and authority.
  • The health challenge and contest become a trending topic on local social media platforms, leading to likes and shares and thereby attracting a broader audience.
  • The partnership created a mutually beneficial cycle – as more people joined the fitness studio, they frequented the café, and vice versa.

Practical Steps To Building Local Business Partnerships

With the potential benefits of local business partnerships outlined above, here are some practical steps to establishing and maintaining effective relationships:

Identify Compatible Businesses Or Organizations

Seek out local businesses and groups that ideally complement your products or services and share your target audience, as shown above with tax, automobile, and wellness-related businesses.

Ensure their values and marketing goals align with yours. This will form the foundation of a successful partnership.

You will naturally want to identify a business whose online presence reflects its understanding and commitment to this important marketing channel.

A few quick Google searches should quickly reveal solid prospective partners who can be easily found via organic search.

Develop A Clear Value Proposition

Clearly define what each party brings to the table and what outcomes are possible.

Consider how you can benefit each other, whether through collaborative content creation and distribution, co-promotion, shared events, or other tactics.

Create A Partnership Agreement

Consider putting a written agreement in place outlining the terms and responsibilities of each party.

This document should include details like the duration of the partnership, resource/time contributions, content ownership considerations, and any other mutual expectations.

Leverage Both Online And Offline Channels

Promote your partnership through various channels, both online and offline.

Depending on the promotion and budget, utilize your website, social media platforms, email marketing, or pay-per-click advertising, as well as in-store physical signage or offline documents, to showcase your collaborations.

Collaborate On Content

Partnering on content creation, such as blog or social media posts, is an excellent way to leverage each other’s expertise and resources.

If the plan is to create a joint blog post or email newsletter per week or month, alternate scheduling can be used to spread out the workload.

This will no doubt resonate with most local business owners who are generally taxed for time.

Monitor, Measure, And Adjust

Any good digital marketing campaign should be monitored and measured to see what’s working and what isn’t, i.e., messaging, channels, etc.

Part of your campaign planning should include a determination of what to measure and the goals you both hope to meet.

Start small with simple metrics both parties can easily obtain, such as newsletter signups, website traffic, or campaign-specific measurements.

Analyze organic search results, website traffic (and particularly referral traffic from your partners or other local sites), social media engagement, and sales at regular intervals to gauge impact.

Consider creating unique branded campaign URLs or QR codes to differentiate traffic or business received via the partnership.

With smaller businesses, it may be simple enough to measure new social media followers or shared content anecdotally.

Analytics is meant to be actionable, so be ready to suggest and adjust if something isn’t working as expected.

Ultimately, analytics will help you determine where to focus your attention, especially if one channel or source produces noticeable results.

Plan, Engage, Collaborate, Grow

Growing your business in your local community is all about extending your reach to the broadest audience possible.

Partnering with like-minded, non-competitive businesses and organizations is a quick and effective way to amplify your message – online and offline.

When done purposefully and properly online, the result is a boost in your all-important local and perhaps topical authority.

Consumers, particularly local consumers, buy from businesses they know and trust.

We all ask our friends, family, and those we do business with for advice or references when we need certain products or services.

Well-established partners can become trust proxies to bring in customers you might otherwise not have access to.

In short, building local online authority and trust boils down to being a highly visible and sincerely engaged member of your broad community that Google cannot ignore.

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Featured Image: SvetaZi/Shutterstock

From Line Item To Leverage: How Web Performance Impacts Shareholder Value via @sejournal, @billhunt

Despite years of digital transformation talk, too many CEOs and CFOs still treat the corporate website as a necessary marketing expense, a sunk cost with limited upside. I have far too many CEO’s of billion-dollar companies who view it simply as an expensive interactive brochure, setting the tone for the company and dooming the web as just that, a brochure without strategic value.

But the modern website is not just a cost center. It’s a capital asset. One that, when strategically managed, generates revenue, lowers acquisition costs, accelerates growth, and protects brand equity.

In my previous articles (“Closing the Digital Performance Gap” and “Who Owns Web Performance?“), I outlined how poor internal ownership and misaligned incentives drag down web effectiveness. Now it’s time to reframe the economic value of performance. Because digital visibility, findability, and functionality aren’t just tactical wins – they affect shareholder value.

Web Execution: Expense Or Asset?

Let’s speak the CFO’s language. If you build a new manufacturing line, you evaluate its contribution to output and margin. If you invest in a retail expansion, you track foot traffic, conversion, and revenue per square foot.

Why don’t we evaluate digital the same way?

Here’s how most companies currently think:

  • SEO: Free traffic driver.
  • Content: Sales and marketing copy.
  • UX: Design polish.
  • Analytics: Reporting tool.

Here’s how performance-minded leaders think:

  • SEO: Organic demand capture engine.
  • Content: Business development asset.
  • UX: Funnel velocity multiplier.
  • Analytics: Optimization flywheel.

When you stop viewing digital as overhead and start seeing it as infrastructure, the return on investment (ROI) math changes completely.

How Underperformance Drains Enterprise Value

If your digital infrastructure is fragmented, under-optimized, or reactive:

  • You spend more on paid channels to make up for poor organic performance.
  • You lose visibility to competitors in AI and search environments.
  • You deliver confusing or outdated experiences that erode brand trust.
  • You waste employee and agency hours chasing after misaligned key performance indicators (KPIs).

None of these are minor problems. They compound.

They show up in:

  • Lower customer lifetime value (CLV).
  • Higher customer acquisition cost (CAC).
  • Missed revenue from unindexed products or inaccessible content.
  • Declines in organic search traffic and authority that paid cannot make up for.

The Invisible ROI Leak: Misalignment

As explored in “Who Owns Web Performance?,” when multiple teams touch the website – but no one owns outcomes – you get:

  • Wasted spend on underperforming campaigns.
  • Lost traffic due to crawlability errors and excessive technical issues.
  • Duplicated content with no central taxonomy.
  • Security or compliance risks from unmanaged pages.

These are not theoretical. They show up on the balance sheet as missed revenue, higher CAC, and lower conversion rates.

The Capital Efficiency Of SEO And Organic Visibility

Capital efficiency is one of the most underappreciated components of shareholder value, but increasingly, it’s a critical factor in CEO evaluations. Boards and investors are looking beyond topline growth to assess how effectively a company turns investment into output to achieve growth. That means efficient, repeatable, high-margin systems like SEO and web performance become strategic levers, not support functions.

SEO is often dismissed as “free traffic,” but that’s misleading. It’s not free and has been rebranded into MBA-friendly buzzwords like “organic visibility” and “owned media.” But behind those terms is real effort. SEO teams must optimize content that was often created in a vacuum, retrofit pages with structured data, and resolve infrastructure gaps just to make that content accessible to search engines. These are real costs and costs that wouldn’t exist if SEO were embedded earlier in the workflow. When viewed holistically as a strategic function, SEO becomes a high-efficiency, compounding return channel. One that gets stronger with alignment and investment, and weaker with neglect.

Properly funded and governed SEO:

  • Reduces dependency on paid media.
  • Enables customer self-service and support at scale.
  • Increases discoverability across multiple intent stages.
  • Builds durable search equity and authority.
  • Fuels AI citations and rich result presence.

More importantly, it improves capital efficiency, the ability to turn inputs (budget, time, content) into outputs (qualified leads, revenue, brand trust) with minimal waste.

AI Search Just Raised The Stakes

Search is no longer about blue links – it’s about recommendation systems. AI Overviews, summary blocks, and generative results are now front and center. If your content isn’t:

…then you’re invisible. Or worse – you’re used as a data source without receiving attribution.

As I wrote in “The New Role of SEO in the Age of AI,” platforms now monetize the experience, not just the click. They extract content, retain the user, and collect behavioral data to improve their own models.

“If your content can’t be reused, monetized, or trained against – it’s less likely to be shown.”

Your site is not just competing with others – it’s competing with the platform itself.

Let’s Talk Shareholder Value

When SEO and digital performance are working:

  • You lower CAC.
  • You increase CLV through better segmentation and nurturing.
  • You strengthen brand equity via visibility and trust signals.
  • You improve operational efficiency through centralized platforms and reusable modules, and reduce customer support costs through effective self-service experiences.
  • You protect valuation by owning your digital demand footprint.

When they aren’t working, you erode those same advantages.

Let’s take a real-world example.

I worked with a public company preparing to spin off half its business into a new entity. The leadership’s attention was focused almost entirely on launching the new brand and website, yet there was no plan for preserving or migrating organic search performance. The new entity’s success depended on leveraging an existing client base, maintaining current sales momentum, and hitting aggressive growth targets. But SEO wasn’t even on the radar.

I was brought in to develop the business case for making organic search a strategic pillar of the post-divestiture digital platform. I argue that we would only get senior executive buy-in not by forecasting traffic loss, but by reframing SEO’s contribution across the three drivers of shareholder value:

  • Financial: Conservative modeling, based on current performance rates, showed that a poorly managed migration could result in $350 million in lost lead value. In addition, regaining that visibility via paid media would require tens of millions in unplanned ad spend.
  • Operational: The company continued operating in 45 countries across 10 languages. Without localized optimization and scalable global templates, international lead pipelines would suffer dramatically.
  • Strategic: To stand apart from the legacy business and support complex enterprise sales cycles, the new digital platform needed to rapidly establish authority, build trust signals, and differentiate itself not only in search but in ease of use and depth of information.

By speaking the language of shareholder value and showing how SEO impacted financial outcomes, operational continuity, and long-term strategic position, we secured executive alignment. SEO was integrated early into the platform roadmap, ensuring scalability, visibility, and global readiness from day one.

A Call To Action For Senior Leaders

If you’re a CEO, CMO, or CFO reading this, ask yourself:

  • Do we treat the website as a strategic asset or a sunk cost?
  • Is there executive ownership of performance or just distributed responsibility?
  • Are we capturing, measuring, and maximizing organic opportunity – or plugging gaps with paid media?
  • Is our content structured and usable by AI systems, or just accurate but invisible?

This is about mindset and governance, not just tactics.

Final Thought: Web Performance Is A Leverage Point

As digital channels drive more business outcomes, functions once considered tactical (like SEO or load speed optimization) can now contribute meaningfully to operational leverage, customer acquisition, and profitability turning them into strategic priorities.

Your website is where your brand, product, content, and promise converge. It’s your most visible, scalable, and measurable asset.

Treating it like a brochure is like owning an F1 race car and only polishing the paint.

When you design for performance, staff for cross-functional excellence, and govern for outcomes – you stop leaking value and start building leverage.

Because in today’s market, digital performance isn’t just good marketing. It’s good business.

And good business drives shareholder value.

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Featured Image: Master1305/Shutterstock

And The Truth? This Writing Style Screams AI via @sejournal, @cshel

Six months ago, you could spot AI-generated text by its polished grammar, rigid essay structure, suspicious fondness for em dashes – and, of course, the inevitable emoji bullets (🔥🚀✨). The real giveaway, at least to my eye and ear, isn’t the emojis or the punctuation. It’s the cadence.

AI writing has a rhythm problem. The sentences are clipped. Overly dramatic. Split into one-line paragraphs that feel more like infomercials than journalism.

“The truth? This wasn’t SEO causation. It was a stock market correction.”
“They were left behind. They were angry. They weren’t your people.”

On the page, this is nails-on-chalkboard grating. It doesn’t read as conversational. It reads as performative. In my opinion, this is, without a doubt, AI’s most recognizable stylistic fingerprint.

A Brief History Of The AI Cadence

This rhythm predates AI. It has been the language of speechwriters, preachers, and copywriters long before GPT entered the chat. Think Reagan’s addresses, Clinton’s campaign rallies, Obama’s campaign speeches, Churchill’s wartime broadcasts, and Blair’s conference speeches. Each leaned on rhythm and repetition to generate a great deal of emotion out of a speck of substance. Pair that with Captain Kirk’s famously staccato delivery, televangelists’ sermons, or TED Talks built around dramatic pauses, and you see how cadence can make small or mundane ideas feel powerful and deep.

That style used to stay in its lane. Where print valued density and clarity, speech valued brevity and rhythm. Readers could re-read; listeners could not. Editors enforced writing standards and styles and the economics of print rewarded information density over theatrics. As a result, this cadence lived solely in spoken word. It lived in speeches and sales copy, and not in essays and articles.

AI collapsed those boundaries. Because LLMs cannot (or chose to not) differentiate between a stump speech, a YouTube transcript, and a white paper, they overindex patterns designed to persuade aloud and repurpose them for the written page. Now, we are inundated with technical articles that read like motivational talks.

Why AIs Default To This Cadence

The AI cadence is not an accident – it’s a reflection of what models were most heavily trained on. Large language models have been fed a disproportionate amount of spoken-word material: transcripts of speeches, news reports, debates, interviews, webinars, podcasts, and video scripts. These aren’t “written texts” in the traditional sense; they are spoken performances converted into text.

Why so much spoken-word data? Because it’s cheap and plentiful. Back when I was running my ISP, I loved radio and TV for advertising and news mentions because it was far less expensive than buying or winning space in print. Broadcasters had 24 hours a day to fill, and local stations were always desperate for content. Print, on the other hand, is expensive. Every page of a newspaper, magazine, or book costs money to produce, and publishers limit content to what is necessary or affordable. As a result, far more hours of audio and video have been produced than carefully edited prose — and much of that material ends up transcribed. Those transcripts give the models a vast mountain of “written-down speech” compared to a relatively smaller body of curated, edited text.

The difference is subtle but important: a transcript is in a written medium, but it is not writing in a written style. It preserves the cadence of spoken delivery — short bursts, rhetorical pauses, fragments. Models overindex this rhythm because it dominates the dataset.

Even when prompted to avoid it, the models can’t resist drifting back into this rhythm. They might manage a few sentences of varied prose, but the gravitational pull of the AI cadence always drags them back. It’s now the default groove burned into their training.

The Em Dash Problem

That overindexing also explains a related AI tell: the sudden overuse of em dashes. In polished writing, dashes were historically used sparingly for emphasis or interruption. In speech, however, pauses are constant. Transcripts often mark those pauses with dashes. For a model swimming in transcripts, the dash becomes a default punctuation mark, because it functions as the written equivalent of a spoken pause. The result is copy littered with dashes – not because the ideas require them, but because the training data normalized them.

Punctuation As Breath

Punctuation has always been about more than grammar. Periods, commas, and dashes are signals for how we pause and where we breathe. They are like rests in music, telling the reader when to stop, inhale, and reset before continuing. Well-edited prose balances those pauses so the rhythm feels natural.

The AI cadence breaks this balance. When every thought is chopped into fragments, you’re effectively told to breathe after every line. Reading an article like this feels like hyperventilating: shallow breaths, constant interruptions, no sustained flow. It makes everything sound catastrophic, urgent, or world-shattering, even when the subject matter is mundane. Gentle readers, not every sentence or every idea warrants that level of drama.

Where this leaves us is that when models generate text, they parrot back the structures they’ve seen most often: speech rhythms and speech punctuation, presented as though they were the standard for written communication. They are not. They’re salesmanship with line breaks and pauses dressed up as prose.

Why Readers React To It

This cadence feels powerful at first. It mimics natural speech. It creates rhythm. It feels dramatic without requiring depth. That’s why it pops in feeds.

However, the longer it is stretched out, like in long-form content, or the more a reader is exposed to the same cadence over and over and over again, the power you once felt collapses into disdain. This breathy, short-sentence delivery leads to:

  • Oversimplification which flattens nuance.
  • Repetition that manipulates more than it informs.
  • Every line to demand attention ensuring none of them earn it.
  • Readers to suspect style is substituting for substance.

Here is the deeper problem: when everything is delivered as if it were earth-shattering, readers begin to doubt the authenticity of the message itself. It’s Syndrome’s hypothesis in The Incredibles: “When everyone is super, no one is.” If every sentence screams urgency, then nothing actually carries weight.

Historically, this kind of relentless, crisis-driven cadence has also been a manipulation tactic. Political demagogues, televangelists, and snake-oil salesmen leaned on hyperbole precisely because they lacked evidence. When AI reproduces that same rhythm on the page, it inherits the credibility problem too. Readers may not articulate it consciously, but they feel it: if you have to shout every line, maybe you don’t have enough substance to stand on quietly.

Just as keyword stuffing once became a hallmark of low-quality SEO, this cadence is already becoming the hallmark of low-quality AI. Readers recognize the rhythm before they absorb the message. When the medium distracts from the message, trust erodes.

A Tale Of Two Paragraphs

AI cadence in practice:

“The algorithm changed.
Sites lost traffic.
Panic spread.
And the industry?
It declared SEO dead – again.”

Now, the same idea written for readers:

“When the algorithm changed, many sites saw a drop in traffic. The panic was predictable. Within days, familiar headlines declared SEO dead once again. The cycle repeats every few years, and every few years it proves wrong.”

The difference here is obvious: one is an infomercial and the other is writing.

How To Spot It

Editors and readers can train themselves to notice:

  • Long runs of one-sentence paragraphs.
  • Rhetorical questions with no depth (often beginning with conjunctions like And or But…
  • Sentence fragments pretending to be profound.
  • Sermon-like pacing that seems to expect a chorus of ‘amens’ (or applause, if you’re lucky)…

Simply put, once you have seen it, you cannot unsee it: it is the literary equivalent of a laugh track.

How To Write Like A Human Again

How do we remedy this situation? Short of, I suppose, doing our own writing?

  • Vary sentence length instead of defaulting to extremes.
  • Use rhetorical questions sparingly – only when they genuinely add depth.
  • Group related ideas into paragraphs; readers can handle more than one sentence at a time. Unless you are writing FOR toddlers, do not treat your readers as though they ARE toddlers.
  • Prioritize clarity and voice over performative drama. Note here that the goal isn’t to sound casual at all costs, but to sound intentional, rational, and backed by data.

Why It Matters For SEOs And Marketers

AI writing tools are embedded in nearly every workflow. Left unchecked, they will flood the web with copy that reads like an endless sales pitch. Professionals must edit not just for facts but for voice.

That means:

  • Training teams to recognize and break the AI cadence.
  • Creating style guides that emphasize varied sentence and paragraph structure.
  • Editing AI drafts with rhythm in mind, not just keywords.
  • Writing for humans who read – not just platforms that skim.

Respecting the reader’s time and intelligence is, in the end, the real optimization.

Is There Ever A Place For This Style?

Yes, of course, but like most things, in moderation. Staccato writing is effective for:

  • Ad copy where space is limited.
  • Video scripts where pacing drives attention. (Your LinkedIn vertical videos and IG Reels? Have at it. This is where the staccato AI cadence shines.)
  • The occasional LinkedIn post engineered for scanning.

However, should this become the default writing style for articles, blogs, or essays? Abso-effing-lutely not. It cheapens the content and undermines credibility.

In Closing

AI has introduced more than just new tools. It has also normalized certain stylistic tics that don’t belong in most forms of writing. Among these, the AI cadence problem is the most recognizable and the most damaging when left unchecked.

Writers, editors, and marketers need to treat the presence of AI cadence in their writings the same way we treated keyword stuffing a decade ago: as a major red flag. The difference between human and AI writing isn’t just factual accuracy. It’s rhythm, intent, and voice.

The real divide isn’t human versus machine. It’s generic versus intentional. Intentional writing that is structured for clarity, rooted in substance, and respectful of the reader will always stand out.

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Featured Image: N Universe/Shutterstock

Are AI Search Summaries Making Evergreen Articles Obsolete? via @sejournal, @martinibuster

Ahrefs’ Tim Soulo recently posted that AI is making publishing evergreen content obsolete and no longer worth the investment because AI summaries leave fewer clicks for publishers.  He posits that it may be more profitable to focus on trending topics, calling it Fast SEO.  Is publishing evergreen content no longer a viable content strategy?

The Reason For Evergreen Content

Evergreen content can be a basic topic that generally doesn’t change much from year to year. For example, the answer to how to change a tire will generally always be the same.

The promise of evergreen content was that it represents a steady source of traffic. Once a web page is ranking for evergreen topics, publishers basically just have to make sure that it’s updated if the topic has changed in some way.

Does AI Break The Evergreen Content Promise?

Tim Soulo is suggesting that evergreen content, which can be easy to answer with a summary, is less likely to send a click because AI summarizes the answer and satisfies the user, who may not need to visit a website.

Soulo tweeted:

“The era of “evergreen SEO content” is over. We’re entering the era of “fast SEO.”

There’s little point in writing yet another “Ultimate Guide To ___.” Most evergreen topics have already been covered to death and turned into common knowledge. Google is therefore happy to give an AI answer, and searchers are fine with that.

Instead, the real opportunity lies in spotting and covering new trends — or even setting them yourself.”

Is Fast SEO The Future Of Publishing?

Fast SEO is another way of describing trending topics. Trending topics have always been around; it’s why Google invented the freshness algorithm, to satisfy users with up-to-date content when a “query deserves freshness.”

Soulo’s idea is that trending topics are not the kind of content that AI summarizes. Perplexity is the exception; it has an entire content discovery section called Perplexity Discover that’s dedicated to showing trending news articles.

Fast SEO is about spotting and seizing short-lived content opportunities. These can be new developments, shifts in the industry or perceptions, or cultural moments.

His tweet captures the current feeling within the SEO and publishing communities that AI is the reason for diminishing traffic from Google.

The Evergreen Content Situation Is Worse Than Imagined

A technical issue that Soulo didn’t mention but is relevant here is that it’s challenging to create an “Ultimate Guide To X, Y, Z” or the “Definitive Guide To Bla, Bla, Bla” and expect it to be fresh and different from what is already published.

The barrier to entry for evergreen content is higher now than it’s ever been for several reasons:

  • There are more people publishing content.
  • People are consuming multiple forms of content (text, audio, and video).
  • Search algorithms are focused on quality, which shuts out those who focus harder on SEO than they do on people.
  • User behavior signals are more reliable than traditional link signals, and SEOs still haven’t caught on to this, making it harder to rank.
  • Query Fan-Out is causing a huge disruption in SEO.

Why Query Fan-Out Is A Disruption

Evergreen content is an uphill struggle, compounded by the seeming inevitability that AI will summarize the content and, because of Query Fan-Out, possibly send the click to another website that is cited because it offers the answer to a follow-up question to the initial search query.

Query Fan-Out displays answers to the initial query and to follow-up questions to the initial search query. If the user is happy with the summary to the initial query, they may become interested in one of the follow-up queries, and one of those will get the click, not the initial query.

This completely changes what it means to target a search query. How does an SEO target a follow-up question? Maybe, instead of targeting the main high-traffic query, it may make sense to target the follow-up queries with evergreen content.

Evergreen Content Publishing Still Has Life

There is another side to this story, and it’s about user demand. Foundational questions stick around for a long time. People will always search “how to tie a bowtie” or “how to set up WordPress.” Many users prefer the stability of an established guide that has been reviewed and updated by a trusted brand. It’s not about being a brand; it’s about being the kind of site that is trusted, well-liked, and recommended.

A strong resource can become the canonical source for a topic, ranking for years and generating the kind of user behavior signals that reinforce its authority and signal the quality of being trusted.

Trend-driven content, by contrast, often delivers only a brief spike before fading. A newsroom model is difficult to maintain because it requires constant work to be first and be the best.

The Third Way: Do It All

The choice between producing evergreen content and trending topics doesn’t have to be binary; there’s a third option where you can do it all. Evergreen and trending topics can complement each other because each side provides opportunities for driving traffic to the other. Fresh, trend-driven content can link back to the evergreen, and this can be reversed to send readers to fresh content from the evergreen.

Trend-driven content sometimes becomes evergreen itself. But in general, creating evergreen content requires deep planning, quality execution, and marketing. Somebody’s going to get the click from evergreen content, it might as well be you.

Featured Image by Shutterstock/Stokkete

Ask an Expert: How to Start with GEO?

“Ask an Expert” is an occasional feature where we pose questions to seasoned ecommerce pros. For this installment, we’ve turned to Louis Camassa, the director of product at Rithum, a marketplace orchestration platform. He’s also a serial entrepreneur and an occasional contributor to Practical Ecommerce.

He addresses the essentials of generative engine optimization for ecommerce.

Practical Ecommerce: How can merchants optimize product visibility across ChatGPT, Perplexity, Gemini, and other generative AI platforms?

Louis Camassa: There’s no universal guide at present for product integration, but retailers can take proactive steps to prepare.

Louis Camassa

Louis Camassa

Begin by evaluating current genAI visibility. Merchants should search for their brand names to understand how the platforms present them. Experiment with shopper-like queries to observe how the systems rank and mention offerings in comparison to competitors. Consider searches such as “Find me running shoes with maximum cushioning for marathon training” or “What are the top-rated coffee makers that brew a single cup in under 2 minutes?”

Next, thoroughly review product info. Again, standardized genAI product formats do not yet exist, yet companies with existing product feeds have a solid foundation. Ensure your feed contains key details such as dimensions, color options, materials, weight specifications, and intended applications.

ChatGPT, Perplexity, and Gemini have not yet opened the gates to share product data directly, but small-to-midsize merchants can get ahead by preparing now.

Generative AI platforms thrive on structured, accurate, real-time data.

Here are optimization tips:

1. Keep product data clean and consistent
• Unique IDs that never change
• Plain text titles and descriptions

2. Write for people, not just machines
• Short, specific titles (brand + product + key attribute)
• Natural language benefits in descriptions

3. Use structured attributes
• Brand, price, size, color, and material
• Group product variants with a shared ID (e.g., parent-child relationship)

4. Optimize images
• Use a content delivery network
• Extra angles or lifestyle shots help

5. Update feeds often
• Refresh at least daily

6. Use custom fields
• Add category-specific details (battery life, fabric, eco-friendly)

7. Localize content
• Language and country codes
• Simple, clear native text

8. Be transparent on price
• Always list price in ISO format (e.g., 29.99 USD)
• Include sale price if available

9. Don’t skip the details
• Shipping, handling, promotions, and other data build trust and improve ranking

Making SEO Personas Actionable Across Teams via @sejournal, @Kevin_Indig

Here’s what I’m covering this week: How to get the most out of personas in your day-to-day work across SEO, content, and the broader org.

Because in the AI-search era, personas built from organic queries and prompts have value for every touchpoint: ad copy, sales scripts, support docs, product messaging.

They carry the unfiltered language of your audience (their fears, hesitations, and demands) straight into the hands of the teams shaping your funnel.

If you’re not operationalizing search-data-based personas across departments, you’re missing one of the few forms of market intelligence that scale across SEO, marketing, sales, and product.

Personas shouldn’t live stagnantly in a slide deck. I’ll show you how to make them pull their weight across the org.

Image Credit: Kevin Indig

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Last week, I showed you how to create search personas based on data you already have available, along with how to use an LLM-ready persona card to extract custom insights.

But the best persona in the world doesn’t help if it collects dust in your Google Drive.

This week, I’m digging into how to make these search persona insights actionable – not only across your SEO processes and production, but also across broader teams that SEO work touches.

However, before we dive in, I want to share a few notable perspectives on search personas that came up in conversation on this LinkedIn thread:

Malte Landwehr, CPO & CMO at Peec AI, gave this visual example in the thread (with additional context) that resonated strongly. From his own research and testing, he shared a visual detailing LLM visibility for various headphones based on prompts for personas and use cases.

The findings? LLMs recommended different brands/products based on different persona-based prompts.

Image Credit: Kevin Indig

And below, David Melamed brings up an interesting and important question below.

Image Credit: Kevin Indig

I agree with David: The more personalized search results are, the less you can segment or generalize across a group.

But if you check out our conversation in the comments, David absolutely gets it, and his concerns are valid.

He shares that “more long tail content and citations across more unique niches, scenarios and comparisons should beat out persona driven content” and that “looking at questions, related searches in search console, and Google and Microsoft ads search term reports… [along with] experience and other voice of customer research (listening to calls, analyzing reviews, reddit threads, complaints, etc..)” would be a helpful approach.

And that’s what I tackled last week in Personas are critical for AI search (part 1 on the persona topic): To succeed with user personas for SEO – and make them valuable and usable – the goal is to build custom, unique search personas from your actual in-house data and long-tail Google Search Console.

So, David brought up a valid point, one that’s aligned with how we should be building useful search personas for today.

Lastly, Elisa Daniela Montanari sums up how a lot of us feel about the shift toward qualitative research (along with mentioning her goals to upskill as an SEO by diving into user research tactics):

Image Credit: Kevin Indig

And with these conversations in mind…

I’d argue that high-quality, customer-centered SEO research captures unfiltered questions, painpoints, and intents at scale, across the entire journey – and that makes it one of the most versatile forms of market intelligence that you can use across your brand as a whole.

So if organic query and prompt research is so valuable and versatile, how do you ensure they’re actually used?

Because all strategists everywhere have had that stupidly challenging moment: After doing all the labor-intensive data-gathering of building user personas for SEO, it’s time to get your team or clients to use those insights regularly across SEO production.

You need to prep your findings so they’re not left gathering cobwebs in the dark corners of the cloud.

1. Create An Internal Knowledge Hub For Core Search Personas

Not another slide deck or spreadsheet that gathers dust. A simple, easily-accessible hub that is a living, breathing document.

Translate data into the formats your team and stakeholders already use: dashboards, one-page briefs, funnel visualizations.

Think Notion, Airtable, Asana, Google Sheets, Slack Canvas – wherever your team is already working and discussing production.

Key contributors need to have access to fluidly comment and update as organic questions and pain points surface across your audience.

2. Build A Clear Narrative Around How And Why Using These Personas Is Valuable

Position SEO research/persona use as a “horizontal competency” that makes every department smarter.

Kick off persona use with a short session showing:

  • Real queries from your personas.
  • How those queries reveal pain points, objections, or jobs-to-be-done.
  • Where competitors are (or aren’t) meeting those needs.
  • Inform the team on how users are interacting with AI-based search results (see Trust Still Lives in Blue Links for details on the four AIO intent patterns).

A three-minute Loom video can do wonders.

Use the data you have (Google Search Console, Semrush, Ahrefs, LLM prompt monitoring tools) to back up the importance of use.

At the end of this memo, I have a slide deck template for premium subscribers that will help you build this narrative and guide effective persona implementation across teams.

3. Train Contributors On How Personas Will Be Used Across Production – And Follow Through

Train your SEO/content contributors that personas don’t just shape blog posts – they inform all communication touchpoints in the customer journey.

If you’re also using search personas to inform your sales and customer care team interactions (and you should – more on that below), create examples of how to use personas across all communication channels.

Highlight missed opportunities (e.g., ad copy vs. organic messaging mismatch, customer support docs hidden from search, sales scripts that could benefit).

And although this means extra work for leaders, managers, or editors, this part is crucial: Let your team know that briefs that don’t specify personas will be rejected or sent back for revision. That also goes for drafts that don’t speak directly to defined personas and their search behaviors/needs.

Yes, it’s an added step on an often-already-overloaded plate of a marketer, but this is how you ensure they’re successfully implemented across your work over time.

Image Credit: Kevin Indig

Here’s where your personas stop being a strategy deck or training session and start shaping what users experience.

1. Incorporate Persona Data Into Every Content Brief

Your search persona data is there to help you direct every brief beyond target queries and products/services features to mention.

Use it to inform your content producers of the following:

  • Unique, data-backed pain points.
  • Real customer/lead questions that need answering.
  • Proof points needed to reduce hesitation.
  • What authority signals resonate with your target reader.
  • Behaviors that impact interactions with the page.
  • Copy on the page.

In every content brief, flag actual language from queries, call transcripts, or reviews that should be used on the page. Create a copy bank that’s tagged into your content briefs that your writers, editors, and LLMs can pull from.

For example, if your persona says “integration headaches,” don’t water it down to “implementation challenges.” Use their words.

2. Use Search Persona Data To Inform Page Structure

Match the flow of the page to how specific personas are likely to consume information.

Some personas need trust-driven validation upfront (editorial quality signals, branded logos, stats, testimonials). Others need efficiency first, then a CTA.

Here’s a practical way to estimate what each of your search personas needs on the page:

  • Follow guidance (and use the regex) provided in Personas are critical for AI search to extract GSC long-tail queries that can contain indicators of specific search personas.
  • Select a specific URL or page that comes up for multiple long-tails for a consistent search persona type.
  • Examine on-page user scrolling and clicking behavior via your heatmap tool.
  • Look for places users pause, scroll past, or toggle back and forth between information. Strong behavioral patterns (skips, hesitations, long-tread times) point to places to better optimize page structure based on search persona type.

Once you’re done gathering information based on user behavioral patterns, audit your on-page modules, formats, and design capabilities to ensure you have all pieces needed to create pages that fulfill those specific needs.

Enlist your product and/or web design team to create what’s needed to serve a better on-page experience.

Then, include direction in each brief of what sort of modules and information structuring is needed based on search persona type.

3. Map To Topic Clusters In The Brief

Specific search personas naturally gravitate toward certain topics or proof points.

A searcher who uses technical language for their queries may cluster around integrations and APIs and need to see clear documentation is available for how to use them, while a user with economic or decision-making intent may cluster around ROI topics.

Build semantically related internal linking paths that explicitly connect those journeys for your SEO personas. Use your topic map (if you’ve built one) and revisit your keyword universe as needed.

4. Personas Should Inform Your AI-Assisted Workflows

Use search persona details as inputs to LLM prompts and/or incorporate them into your AI-assisted content generation, like AirOps workflows.

Instead of “write an article about X with the search intent of Y,” frame it as “write for a skeptical buyer evaluating vendors – include comparisons and third-party validation.”

Or better yet? Use your persona cards (see Personas Are Crucial for AI Search for a detailed guide) to help guide additional prompts personas might use in LLMs when attempting to solve queries related to your brand.

Below, take a look at how this could work in practice, using the four distinct AIO intent patterns from the additional analysis of the UX study of AIOs found in Trust Still Lives in Blue Links:

  1. Efficiency-first validations that reward clean, extractable facts (accepting of AIOs).
  2. Trust-driven validations that convert only with credibility (validate AIOs).
  3. Comparative validations that use AIOs but compare with multiple sources.
  4. Skeptical rejections that automatically distrust AIOs for high-stakes queries.

Let’s say you work for a fintech startup that provides easy-to-use business insurance for small to midsize businesses.

Here’s how you might use personas to inform content production for efficiency-first and trust-driven search behaviors:

Example 1: Junior operations coordinator at a 20-person marketing agency → accepting of AIOs (efficiency-first) → queries “What’s the average cost of business insurance for a 20-person company?” → Likely to validate range via the AIO → Takeaway for your brand: Create content geared to businesses with small teams and/or junior learners that includes straightforward facts and ranges that are easily extractable, so it’s cited in AIOs. Make your pricing explanations scannable and structured. Internally link to other knowledge guides for project managers or operations leads at small to midsize businesses.

Example 2: Small business owner in healthcare services → validate AIOs with second-clicks (trust-driven) → queries “Do I need business insurance for HIPAA compliance?” → Likely to read the AIO but won’t act until they see credible signals → citations from legal/insurance authorities → Takeaway for your brand: Position your content with authoritative references (link to .gov or .org sources) and highlight compliance expertise so your page is validated by trust; include case studies and/or social proof of authority; Internally link to other guides for healthcare service businesses.

How To Know Search Persona Implementation Is Working

Watch for these signals:

  • Higher engagement time and more downstream actions on the page.
  • Lower bounce rates on persona-driven pages.
  • More citations and visibility in AIOs and LLM outputs (your copy matches how users ask questions).
  • Increased assisted conversions: Pages designed for a specific persona show up more often in multi-touch journeys or are incorporated strategically and/or organically into follow-up communications by sales/customer teams.
  • Sales/Customer service team feedback loop: Fewer “this didn’t answer my question” moments.

Amanda jumping in here: In March of this last year, I led one of my clients to pivot hard to persona-focused content. Not only have we seen an increase in AIO inclusion, AI Mode citations, and LLM visibility for these niche terms, but we’ve also experienced a boost in visits to our core guides that were geared toward our broader audience. After this pivot, we’re seeing anywhere between a 20-60% month-over-month increase in organic visits from ChatGPT, and a ~40% increase month-over-month in visible AIO inclusion, to include our older core content as well. Although some of this growth is likely due to increased overall ChatGPT adoption and increase in Google’s use of AIOs across queries, here’s the takeaway (and my hypothesis): As you create niche content for personas, it’s possible you could also see a lift in your core content as it’s served to these specific groups of searchers – based on what these tools know about (1) the end user and (2) who your brand serves best. But only time (and more experiments) will truly tell.

The reality is, no matter how well you implement search personas into your SEO and content production, SEO and growth marketing teams can’t win on their own.

Search personas have the real opportunity to contribute to results when the rest of the org picks them up and runs with them throughout lead and customer touchpoints.

The trick is to make it dead-simple for every team to see why personas matter for their work and how to apply them.

Plus, a big advantage of bringing other teams on board is that SEO-driven personas – built from real search queries, prompts, social chatter, and call transcripts – arm everyone with the exact language customers use.

That means you can reduce hesitations, preemptively answer questions, and build trust across every channel of communication.

Below, here’s a quick list of guidance to help you collaborate with other teams on how to use search persona data.

And in the next section, I’ll jump into how to create intentional feedback loops so your personas stay fresh, useful, and relevant.

Email Marketing

  • Work with email teams to trigger sequences based on persona signals (query intent by pages visited, topics visited).
  • Example: If someone hits three pricing-related pages, route them into a nurture path designed for a search-data-informed persona that includes supportive content often visited by those users.
  • Benefit: Aligns your SEO insights with lifecycle marketing, reducing drop-off between discovery and conversion.

Paid Media And Advertising

  • Lift search-persona informed language directly into ad copy → track if it increases CTR because you’re speaking the way customers search.
  • Map objections to creatives: For example, run ads that emphasize compliance and audits if you have search data illustrating a segment of users who have detailed questions about security of your software.
  • Test messaging by persona to learn faster which angles convert.
  • Benefit: SEO persona research de-risks your paid spend by validating copy before it goes live.

Social And Community

  • Translate persona pain points into campaign themes and engagement prompts.
  • Highlight UGC that shows peers solving the same persona pain point = social proof!
  • Build Reddit or forum campaigns where you provide helpful answers framed through persona lenses.
  • Benefit: Social teams stop guessing what will resonate – they get ready-made hooks from organic customer query data and in-house transcript research.

Sales

  • Use personas to shape sales scripts to reduce organic hesitations, along with your follow-up email templates.
  • Provide a list of key characteristics or organic phrases discovered in your SEO user persona research for sales to easily pick up on what scripts or content to use.
  • Equip reps with content “proof kits” (case studies, calculators, benchmarks) that map to persona objections.
  • Example: Lead comes in from organic content around “integration headaches.” Sales can immediately address hesitations with comparison docs + customer proof.
  • Benefit: SEO insights close the loop. Your leads feel heard because the same language follows them from organic query to sales call.

Customer Support

  • Build FAQs, hub pages, and documentation around persona pain points and natural language so customers can self-serve faster.
  • Train reps on marketing and educational language developed for personas to keep communication consistent across the lifecycle.
  • Feed recurring support questions back to SEO/content as new opportunities.
  • Benefit: Less friction for customers, more organic opportunities uncovered for SEO.

Product And/Or Product Marketing

  • Tie persona insights to feature positioning: “Which persona is this release for?”
  • Test messaging against persona objections to see what sticks before launch.
  • Document frameworks: “For Persona A, highlight speed. For Persona B, highlight compliance.”
  • Benefit: SEO personas become market intelligence, not just marketing intel. This helps product teams ship smarter. Unanswered questions or unsolved organic problems are great opportunities for new features.

One of the biggest pitfalls with doing the work to create search personas is then treating them like static, lifeless relics afterward.

2015 B2B study conducted by Cintell found that 71% of companies who exceeded revenue goals had documented personas – and nearly two-thirds of those orgs had updated them within the last six months.

(Listen, I am well aware 2015 is approximately 47 internet years ago – but I’d argue core human decision-making behavior takes much longer to change than a decade.)

No matter the study’s age, the message rings true today: Marketing and user personas win when they’re kept alive.

SEO personas make this easier than traditional personas because they’re rooted in fluid signals, like real search queries, prompts, and customer language that evolve as quickly as the market and trends do.

If you’re closely monitoring GSC data, Semrush, or AIO/LLM interactions, you’ll see shifts in questions and pain points before most competitors.

Image Credit: Kevin Indig

How to operationalize a persona freshness feedback loop across your team:

  • Employ direct communication channels: Create dedicated Slack channels, a shared CRM note hub, or monthly syncs where Sales, Customers, and Marketing can drop fresh objections, questions, or hesitations they’re hearing. If you’ve got power users or partners who can drop in routine feedback and thoughts, even better.
  • Develop a regular review cadence: Run a quarterly refresh of persona pain points, objections, and query patterns. Layer in branded search trends, referral data, and AIO/LLM interactions to validate updates.
  • Create an escalation path: Set up a clear process for when a “new pain point” surfaces. Sales hears it first → SEO/content teams get it next → new content or updates ship fast → implement/inform across marketing channels. How do you make room for organic escalations in your SEO/content production systems?
  • Do hesitation check-ins: Bi-weekly or monthly cross-team reviews (Support + Sales + SEO) where you identify the top organic customer/lead hesitations and assign assets to resolve them: case studies, how-to videos, tools and calculators, testimonials/reviews, community feedback on social channels.
  • Hold a regular retro: Tie shipped assets back to KPIs. Which persona-driven pages moved the needle? Which didn’t? Prune or upgrade pages that aren’t solving the problem.

The big takeaway here is search personas are never one-and-done.

They’re a dynamic, qualitative and quantitative data-based operating system for your marketing, sales, and product teams … and if you keep the feedback loop tight, they’ll keep paying dividends.


Featured Image: Paulo Bobita/Search Engine Journal

LLMs.txt For AI SEO: Is It A Boost Or A Waste Of Time? via @sejournal, @martinibuster

Many popular WordPress SEO plugins and content management platforms offer the ability to generate LLMs.txt for the purpose of improving visibility in AI search platforms. With so many popular SEO plugins and CMS platforms offering LLMs.txt functionality, one might come away with the impression that it is the new frontier of SEO. The fact, however, is that LLMs.txt is just a proposal, and no AI platform has signed on to use it.

So why are so many companies rushing to support a standard that no one actually uses? Some SEO tools offer it because their users are asking for it, while many users feel they need to adopt LLMs.txt simply because their favorite tools provide it. A recent Reddit discussion on this very topic is a good place to look for answers.

Third Party SEO Tool And LLMs.txt

Google’s John Mueller addressed the LLMs.txt confusion in a recent Reddit discussion.  The person asking the question was concerned because an SEO tool flagged it as 404, missing. The user had the impression that the tool implied it was needed.

Their question was:

“Why is SEMRush showing that the /llm.txt is a 404? Yes, I. know I don’t have one for the website, but, I’ve heard it’s useless and not needed. Is that true?

If i need it, how do i build it?

Thanks”

The Redditor seems to be confused by the Semrush audit that appears to imply that they need an LLMs.txt. I don’t know what they saw in the audit but this is what the official Semrush audit documentation shares about the usefulness of LLMs.txt:

“If your site lacks a clear llms.txt file it risks being misrepresented by AI systems.

…This new check makes it easy to quickly identify any issues that may limit your exposure in AI search results.”

Their documentation says that it’s a “risk” to not have an LLMs.txt but the fact is that there is absolutely no risk because no AI platform uses it. And that may be why the Redditor was asking the question, “If i need it, how do I build it?”

LLMs.txt Is Unnecessary

Google’s John Mueller confirmed that LLMs.txt is unnecessary.

He explained:

“Good catch! Especially in SEO, it’s important to catch misleading & bad information early, before you invest time into doing something unnecessary. Question everything.”

Why AI Platforms May Choose To Not Use LLMs.txt

Aside from John Mueller’s many informal statements about the uselessness of LLMs.txt, I don’t think there are any formal statements from AI platforms as to why they don’t use LLMs.txt and their associated .md markdown texts. There are, however, many good reasons why an AI platform would choose not to use it.

The biggest reason not to use LLMs.txt is that it is inherently untrustworthy. On-page content is relatively trustworthy because it is the same for users as it is for an AI bot.

A sneaky SEO could add things to structured data and markdown texts that don’t exist in the regular HTML content in order to get their content to rank better. It is naive to think that an SEO or publisher would not use .md files to trick AI platforms.

For example, unscrupulous SEOs add hidden text and AI prompts within HTML content. A research paper from 2024 (Adversarial Search Engine Optimization for Large Language Models) showed that manipulation of LLMs was possible using a technique they called Preference Manipulation Attacks.

Here’s a quote from that research paper (PDF):

“…an attacker can trick an LLM into promoting their content over competitors. Preference Manipulation Attacks are a new threat that combines elements from prompt injection attacks… Search Engine Optimization (SEO)… and LLM ‘persuasion.’

We demonstrate the effectiveness of Preference Manipulation Attacks on production LLM search engines (Bing and Perplexity) and plugin APIs (for GPT-4 and Claude). Our attacks are black-box, stealthy, and reliably manipulate the LLM to promote the attacker’s content. For example, when asking Bing to search for a camera to recommend, a Preference Manipulation Attack makes the targeted camera 2.5× more likely to be recommended by the LLM.”

The point is that if there’s a loophole to be exploited, someone will think it’s a good idea to take advantage of it, and that’s the problem with creating a separate file for AI chatbots: people will see it as the ideal place to spam LLMs.

It’s safer to rely on on-page content than on a markdown file that can be altered exclusively for AI. This is why I say that LLMs.txt is inherently untrustworthy.

What SEO Plugins Say About LLMs.txt

The makers of Squirrly WordPress SEO plugin acknowledge that they provided the feature only because their users asked for it, and they assert that it has no influence on AI search visibility.

They write:

“I know that many of you love using Squirrly SEO and want to keep using it. Which is why you’ve asked us to bring this feature.

So we brought it.

But, because I care about you:

– know that LLMs txt will not help you magically appear in AI search. There is currently zero proof that it helps with being promoted by AI search engines.”

They strike a good balance between giving users what they want while also letting them know it’s not actually needed.

While Squirrly is at one end saying (correctly) that LLMs.txt doesn’t boost AI search visibility, Rank Math is on the opposite end saying that AI chatbots actually use the curated version of the content presented in the markdown files.

Rank Math is generally correct in its description of what an LLMs.txt is and how it works, but it overstates the usefulness by suggesting that AI chatbots use the curated LLMs.txt and the associated markdown files.

They write:

“So when an AI chatbot tries to summarize or answer questions based on your site, it doesn’t guess—it refers to the curated version you’ve given it. This increases your chances of being cited properly, represented accurately, and discovered by users in AI-powered results.”

We know for a fact that AI chatbots do not use a curated version of the content. They don’t even use structured data; they just use the regular HTML content.

Yoast SEO is a little more conservative, occupying a position in the center between Squirrly and Rank Math, explaining the purpose of LLMs.txt but not overstating the benefits by hedging with words like “can” and “could.” That is a fair way to describe LLMs.txt, although I like Squirrly’s approach that says, you asked for it, here it is, but don’t expect a boost in search performance.

The LLMs.txt Misinformation Loop

The conversation around LLMs.txt has become a self-reinforcing loop: business owners and SEOs feel anxiety over AI visibility and feel they must do something, viewing LLMs.txt as the something they can do.

SEO tool providers are compelled to provide the LLMs.txt option, reinforcing the belief that it’s a necessity, unintentionally perpetuating the cycle of misunderstanding.

Concern over AI visibility has led to the adoption of LLMs.txt which at this stage is only a proposal for a standard that no AI platform currently uses.

Featured Image by Shutterstock/James Delia

Recover ChatGPT 404 Traffic with GA4

ChatGPT often links to sources when answering prompts. Traffic from those clicks is typically high-converting in my testing. Unfortunately, ChatGPT frequently hallucinates URLs and sends visitors to nonexistent pages.

A study released this month by Ahrefs found ChatGPT 5 links to error pages nearly three times more than does Google Search.

To be sure, traffic thus far from ChatGPT is less than 5% for most sites. But it’s still a good idea to monitor ChatGPT-generated 404 errors and adjust the pages accordingly. With declining Google Search traffic, “saving” visits is paramount.

Address the problem in three steps:

  1. Track 404 “page not found” URLs in Google Analytics 4.
  2. Create helpful 404 pages for visitors from hallucinated URLs.
  3. Set up 301 redirects only for broken URLs that generate traffic.

I’ll explain the first step in this article.

Track in Google Analytics

Filter Google Analytics reports to URLs with traffic from ChatGPT:

  • Go to “Engagement” > “Pages and screens” to view all pages with traffic for the designated period.
  • Select “Page titles and screen class” above the list of pages.
  • Click “Add filter” above the graph.
  • Select “Session source/medium” as the dimension.
  • Select “Contains” and type “ChatGPT.”
  • Click “Apply.”
Screenshot of the Dimension interface in Google Analytics

Filter Google Analytics reports to URLs with traffic from ChatGPT. Click image to enlarge.

Now your list is filtered to pages with traffic from ChatGPT.

Next, narrow the list to error pages:

  • Go to your site and open all the ChatGPT-filtered pages above.
  • Note the title of pages with 404 errors (Ctrl+D on Windows; Command+D on Mac). In my case, the title was “404 Response Error Page.”

Then return to Google Analytics:

  • Type the error page title in the search bar above the list of pages with traffic from ChatGPT. Add “Page path and screen” class as a secondary dimension to view the hallucinated URLs.
  • Bookmark the URL of this report and check from time to time.

Type the error page title in the search bar above the list of pages with traffic from ChatGPT. Add “Page path and screen” class as a secondary dimension. Click image to enlarge.

Agentic AI In SEO: AI Agents & The Future Of Content Strategy (Part 3) via @sejournal, @VincentTerrasi

For years, the SEO equation appeared to be a fixed and unchanging landscape: optimizing for Googlebot on one side, and creating content for human users on the other. This outdated binary vision is now a thing of the past.

In the current business environment, a new generation of actors is causing significant changes to the online visibility landscape. AI agents such as ChatGPT, Perplexity, Claude, and Gemini are no longer merely processing information; they are exploring, synthesizing, choosing sources to cite, and significantly influencing traffic flows.

For those who are skeptical about the impact of AI agents, I would invite you to consider the concept of Zero Moment of Truth (ZMOT), which was developed by Google over 10 years ago. The principle is straightforward: Prior to any purchase, consumers undertake an extensive research phase. They consult customer reviews, compare across different sites, scrutinize social networks, accumulate information sources, and now use their favorite AIs for final validation.

A New Paradigm

We are currently experiencing a fundamental reconfiguration of the digital ecosystem. In the past, we have identified two or three main engines. However, a new paradigm is emerging.

Google continues to be a leading search engine, utilizing sophisticated algorithms to index and rank content. Humans act as a virality engine, sharing and amplifying information via their social networks and interactions.

It is becoming increasingly apparent that AI agents are assuming the role of an autonomous traffic engine. These intelligent systems are capable of navigating information independently, establishing their own selection criteria, and directing users to sources they deem relevant.

This transformation necessitates a wholly new approach to content creation, which I will be sharing imminently. I will be sharing concepts and case studies that have been successfully implemented with several major accounts.

Agentic SEO

Quick reminder following my two previous articles on the subject: “Agentic AI In SEO: AI Agents & Workflows For Ideation (Part 1)” and “Agentic AI In SEO: AI Agents & Workflows For Audit (Part 2).”

Agentic SEO involves the creation of structured and dynamic content that is designed to appeal not only to Google, but also to conversational AIs.

The approach to content generation is founded on three key pillars:

1. Data Enrichment: Schema.org data, microformats, and semantic tags are becoming important as, when grounding data, they can facilitate understanding and information extraction by language models.

2. Content Modularity: Concise and “chunkable” responses are perfectly suited to Retrieval-Augmented Generation (RAG) ingestion processes utilized by these agents. Content should be designed using autonomous and reusable blocks.

3. Polymorphism: Each page can offer variants adapted according to the type of agent consulting it. It is essential to recognize that the needs of a shopping agent differ from those of a medical agent, and content must adapt accordingly.

Image from author, September 2025

If your content isn’t optimized for AI agents, you’re already experiencing considerable strategic lag.

However, if your site is optimized for SEO, you’ve already taken a significant step forward.

The Foundations: Generative SEO And Edge SEO

To understand this evolution, it is important to consider the concepts that have prepared the ground: generative SEO and Edge SEO.

Generative SEO

Generative SEO facilitates the creation of substantial and insightful content through the utilization of language models. This approach automates the process of creating content while ensuring its relevance and quality.

Generative SEO has always existed in primitive forms, such as content spinning and all derived techniques. In today’s digital landscape, we are witnessing a paradigm shift towards unparalleled quality, as evidenced by the preponderance of AI-generated or co-written content across various social networks, including LinkedIn.

Edge SEO

Edge SEO leverages CDN or proxy-side deployment capabilities to reduce deployment latency and enable large-scale content testing from both content and performance perspectives.

These two approaches are naturally complementary, but they still represent a 1.0 vision of automated SEO. It is important to note that traditional A/B testing and content freezing, once generation is complete, limit the potential of the project.

The true revolution lies in the adoption of dynamic and adaptive systems that surpass these limitations.

Agentic Edge SEO

Edge SEO had already revolutionized the very notion of static content. The system now has the capability to modify content in real-time according to the following three variables:

  • Firstly, user intention is detected and used to guide content adaptation. The system is able to analyze behavioral signals in order to adjust the message in real-time.
  • Next, let us consider the impact of SERP seasonality on modifications. When Google prioritizes certain trends on a given query, content automatically adapts to capitalize on these evolutions.
  • Finally, the instant technical optimizations triggered by Core Web Vitals signals ensure that performance is maintained.
Image from author, September 2025

Let us consider a product page as a case study. If Google highlights “sustainable” or “economical” trends for a particular search, this page automatically adapts its titles, metadata, and visuals to align with these market signals.

At Draft&Goal, we have developed connectors with the Fasterize tool to facilitate the deployment of AI workflows. These workflows are compatible with all the most recent proprietary or open-source LLMs.

We anticipate that in the future, the system will continuously test these variants with search engines and users, collecting performance data in near real-time.

The most effective version is then selected by the algorithm, in terms of click-through rate (CTR), positioning, and conversion, with results continually being optimized.

For example, imagine a “Running Shoes” landing page, existing in seven distinct versions, each oriented towards a specific angle: price, performance, comfort, ecology, style, durability, or innovation. The polymorphic system automatically highlights the most effective variant according to signals sent by Google and user behaviors.

Three Concrete Applications

These concepts are immediately applicable to several strategic sectors. Allow me to provide three examples of the products currently under active testing.

In ecommerce, product pages are self-evolving. These systems adapt to search trends, available stock, and detected behavioral preferences.

1. To illustrate this point, consider a peer-to-peer car rental platform that manages 20,000 city pages.

Each page automatically adapts according to Google signals and local user patterns. During the summer months, the “Car rental Nice” page automatically prioritizes convertibles and highlights family testimonials. During the winter season, the fleet is transitioned to 4×4 vehicles, with a focus on optimizing the “mountain car rental” service.

2. Another example of technological innovation in the media industry is the ability of major news outlets to deploy “living” articles.

These articles are automatically updated to include the latest breaking news, ensuring that content remains fresh and relevant without the need for human editorial intervention. We continue to prioritize content creation by human professionals, with AI playing a supportive role in maintaining currency.

3. Finally, the promo codes website has successfully managed 3,000 merchant pages, which adapt in real-time to commercial cycles and breaking deals.

Amazon’s Prime Days announcement is met with the automatic enrichment of contextual banners and temporal counters on all related pages. The system is designed to monitor partner APIs in order to detect new offers and instantly generate optimized content. Three weeks before Black Friday, “Zalando promo codes” pages automatically integrate dedicated sections and restructure their keywords.

Toward A New Era Of SEO

The future of SEO lies in publishing dynamic content that can adapt to the ever-changing algorithms of Google’s index. This transformation requires a fundamental paradigm shift, and many SEO agencies we support have already made the switch.

Marketing experts must abandon the “page” logic to adopt that of “adaptive systems.” This transition necessitates the acquisition of new tools and skills, as well as a re-evaluation of our strategic vision.

It is important to note that Agentic SEO is not merely a passing trend; it is the necessary response to an ecosystem undergoing profound mutation. Organizations that master these concepts will gain a significant competitive advantage in tomorrow’s attention economy.

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Featured Image: Collagery/Shutterstock

Google Answers SEO Question About Keyword Cannibalization via @sejournal, @martinibuster

Google’s John Mueller answered a question about a situation where multiple pages were ranking for the same search queries. Mueller affirmed the importance of reducing unnecessary duplication but also downplayed keyword cannibalization.

What Is Keyword/Content Cannibalization?

There is an idea that web pages will have trouble ranking if multiple pages are competing for the same keyword phrases. This is related to the SEO fear of duplicate content. Keyword cannibalization is just a catchall phrase that is applied to low-ranking pages that are on similar topics.

The problem with saying that something is keyword cannibalization is that it does not identify something specific about the content that is wrong. That is why there are people asking John Mueller about it, simply because it is an ill-defined and unhelpful SEO concept.

SEO Confusion

The SEO was confused about the recent &num=100 change, where Google is blocking rank trackers from scraping the search results (SERPs) at the rate of 100 results at a time. Some rank trackers are floating the idea of only showing ranking data for the top 20 search results. This affects rank trackers’ ability to scrape the SERPs and has no effect on Google Search Console other than to show more accurate results.

The SEO was under the wrong impression that Search Console was no longer showing impressions from results beyond the top twenty. This is false.

Mueller didn’t address that question; it is just a misunderstanding on the part of the SEO.

Here is the question that was asked:

“If now we are not seeing data from GSC from positions 20 and over, does that mean in fact there are no pages ranking above those places?

If I want to avoid cannibalization, how would I know which pages are being considered for a query, if I can only see URLs in the top 20 or so positions?”

Different Pages Ranking For Same Query

Mueller said that different pages ranking for the same search query is not a problem. I agree: multiple web pages ranking for the same keyword phrases is not a problem; it’s a good thing.

Mueller explained:

“Search Console shows data for when pages were actually shown, it’s not a theoretical measurement. Assuming you’re looking for pages ranking for the same query, you’d see that only if they were actually shown. (IMO it’s not really “cannibalization” if it’s theoretical.)

All that said, I don’t know if this is actually a good use of time. If you have 3 different pages appearing in the same search result, that doesn’t seem problematic to me just because it’s “more than 1″. You need to look at the details, you need to know your site, and your potential users.

Reduce unnecessary duplication and spend your energy on a fantastic page, sure. But pages aren’t duplicates just because they happen to appear in the same search results page. I like cheese, and many pages could appear without being duplicates: shops, recipes, suggestions, knives, pineapple, etc.”

Actual SEO Problems

Multiple pages ranking for the same keyword phrases is not a problem; it’s a good thing and not a reason for concern. Multiple pages not ranking for keywords is a problem.

Here are some real reasons why pages on the same topic may fail to rank:

  • The pages are too long and consequently are unfocused.
  • The pages contain off-topic passages.
  • The pages are insufficiently linked internally.
  • The pages are thin.
  • The pages are virtually duplicates of the other pages in the group.

The above are just a few real reasons why multiple pages on the same topic may not be ranking. Pointing at the pages and declaring they are cannibalizing each other is not real. It’s not something to worry about because keyword cannibalization is just a catchall phrase that masks all the actual reasons I just listed.

Takeaway

The debate over keyword cannibalization says less about Google’s algorithm and more about how the SEO community is willing to accept ideas without really questioning whether the underlying basis makes sense. The question about keyword cannibalization is frequently discussed, and I think that’s because many SEOs have the intuition that it’s somehow not right.

Maybe the habit of diagnosing ranking issues with convenient labels mirrors the human tendency to prefer simple explanations over complex answers. But, as Mueller reminds us, the real story is not that two or three pages happen to surface for the same query. The real story is whether those pages are useful, well linked, and focused enough to meet a reader’s information needs.

What is diagnosed as “content cannibalization” is more likely something else. So, rather than chasing shadows, it may be better to look at the web pages with the eyes of a user and really dig into what’s wrong with the page or the interlinking patterns of the entire section that is proving problematic. Keyword cannibalization disappears the moment you look closer, and other real reasons become evident.

Featured Image by Shutterstock/Roman Samborskyi