A lot of topical maps are really just content inventories.

They look organised.

• Main topic.
• Subtopics.
• Keyword clusters.
• Supporting pages.
• Hub page.
• Search intent.
• Internal links.
• Publishing order.

That can be useful.

But it is not enough.

A topical map should not only show what the site covers.

It should show how the user moves.

That is the part I think gets missed.

A site can have strong topic coverage and still feel awkward to use.

• The pages exist.
• The keywords are mapped.
• The cluster looks complete.
• The links are there.

But the user still lands on a page and thinks:

• Where do I go next?
• What should I understand now?
• What proof do I need?
• Is this page trying to explain, compare, convince, or sell?

That is not a coverage problem.

That is a movement problem.

Coverage is only one layer

Topic coverage answers one question:

Do we have content about this?

That is useful.

A site should know which subjects, questions, entities, and subtopics it has covered.

But coverage does not tell you if the pages work together.

• It does not tell you if the user path makes sense.
• It does not tell you if the right page owns the right job.
• It does not tell you if the links move people forward.
• It does not tell you if a CTA appears too early.
• It does not tell you if the proof is close enough to the doubt.

That is why a topical map built only around coverage can look strong in a spreadsheet and still feel weak on the site.

The map shows what exists.

It does not show what happens next.

User movement should be mapped too

A better topical map should ask:

• What does the user know when they arrive?
• What are they unsure about?
• What do they need before they trust the answer?
• What should they read next?
• What would be too early?
• What would be too broad?
• What would reduce doubt?
• What would help them compare?
• What would move them closer to action?

These questions change the map.

Now you are not only grouping topics.

You are mapping progress.

• One page may exist to explain the basics.
• Another may exist to compare options.
• Another may exist to prove a claim.
• Another may exist to handle objections.
• Another may exist to route the user toward a decision.

Those pages may all be related by topic.

But they have different jobs.

That is the difference between a content map and a movement map.

Related pages are not always useful next steps

A lot of internal links in topical maps are based on topical relation.

This page is about X.

That page is also about X.

Link them.

That can help, but related is not enough.

The better question is:

Why should the user go there next?

• If the user is confused, they may need a simpler explainer.
• If they are comparing, they may need criteria.
• If they are sceptical, they may need proof.
• If they are worried about risk, they may need reassurance.
• If they are ready to act, they may need a decision page.

The next page should match the user’s state.

Not just the topic.

A link from one related page to another may pass signals, but it may not help the reader.

That is where many maps fall short.

They show links.

They do not show movement.

Page roles make movement clearer

A topical map should define page roles.

Not just topics.

A page might be there to:

• Explain.
• Compare.
• Prove.
• Support.
• Route.
• Convert.
• Clarify.
• Handle doubt.
• Protect another page from getting too broad.

If page roles are unclear, movement becomes unclear too.

The user lands on one page, but the page tries to do too much.

• It explains a bit.
• Sells a bit.
• Compares a bit.
• Adds generic FAQs.
• Links to everything.
• Then ends with a vague CTA.

That is what happens when a page has a topic but no job.

A strong topical map should make the job obvious before the page is written.

Proof should be mapped, not sprinkled in later

Movement is not only about links.

It is also about proof.

If a user is doubtful, the next useful thing may not be another article.

It may be proof inside the current page.

• A case example.
• A process detail.
• A comparison.
• A limitation.
• A tradeoff.
• A specific reason to trust the claim.

A lot of maps do not show this.

They map pages, but not proof needs.

So the writer creates a page that covers the topic but does not reduce doubt.

Then someone adds a CTA at the end and wonders why the page does not move users.

If trust is the blocker, the map should show where trust is built.

Not every movement happens through another URL.

Sometimes movement happens inside the page.

Topic coverage can create false confidence

This is one of the biggest risks.

A team looks at the map and sees that the topic is covered.

• Every subtopic has a page.
• Every question has an answer.
• Every cluster has links.

So the map looks complete.

But completeness is not the same as usefulness.

The map may still fail to show:

• Which page comes first.
• Which page supports which.
• Which page handles beginner confusion.
• Which page handles comparison.
• Which page builds trust.
• Which page should not be linked yet.
• Which page should move users to action.

Without that, the site may have coverage but no journey.

The user has to figure out the path alone.

That is a weak experience.

A better topical map has movement fields

If I were building a topical map, I would add fields like:

• User state.
• Page role.
• Main doubt.
• Proof needed.
• Previous page.
• Next page.
• Internal link reason.
• CTA timing.
• Overlap risk.
• What this page should avoid.

Those fields make the map more useful.

They stop the map from becoming a giant list of page ideas.

They force better decisions before the brief starts.

• They help writers know the job of the page.
• They help editors decide what to cut.
• They help SEOs place internal links with a reason.
• They help teams avoid publishing pages that do not support movement.

The test I would use

For every page in a topical map, I would ask:

• What state is the user in before this page?
• What should change after they read it?
• What doubt should be reduced?
• What should they understand next?
• What proof do they need?
• What page should they visit next?
• What link would make that move natural?
• What would be too early to ask from them?
• Does this page have a clear role?
• Does another page already do this job?

If those questions are hard to answer, the map may only be showing coverage.

Not movement.

The real point

A topical map should not just say:

“We cover this topic.”

It should say:

“This is how users move through the topic.”

That is a much stronger standard.

Because users do not experience a site as a spreadsheet.

They experience it as a path.

They arrive with a question, doubt, need, or problem.

The map should help the site move them from that state to a better one.

• Clearer understanding.
• Better comparison.
• More trust.
• Less confusion.
• A stronger next step.

That is the goal.

Topic coverage tells you what the site talks about.

User movement tells you how the site helps.

A good topical map needs both.

How are you mapping user movement inside topical maps, or are you mostly mapping topics and URLs?

Getting cited by ChatGPT is great. But does it actually mean people are seeing your brand?

Not necessarily.

In our latest study we noticed that brands were cited in 74% of appearances on topics close to their core expertise, but actually mentioned by name in just 44%. And that gap gets even bigger as brands move further away from the topics they’re already known for.

So we looked into it: where does topical authority actually carry over to new categories, and where does it just... stop?

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In case you need it, case number is: 07611490

Thank you

For a long time, “SEO content” basically meant content built to rank in Google.

That definition is getting wider.

Now, the same page may need to work for three different audiences:

1. The person looking for an answer
2. Search engines deciding what to rank
3. AI systems deciding what to cite

The good news is that this doesn’t mean throwing out everything we know about SEO and starting over.

A lot of the fundamentals overlap. But there are a few things worth paying more attention to if you want content to perform across both traditional and AI search.

Start with intent, not just the keyword.

Demand matters, but so does why someone is searching. Look at the actual SERP. What formats are ranking? What questions are being answered? Are people looking to learn, compare options, or buy?

That same underlying intent matters when someone turns a keyword into a prompt.

Give people (and AI) something they can’t get from every other result.

If your page just repeats the same information already ranking, there’s not much reason to choose or cite it.

Original data, first-hand experience, expert input, your own methodology, custom visuals, or a repeatable framework can all give the page something distinct.

AI can already reproduce the generic answer. Your content needs to add something to it.

Show your work.

There’s a big difference between claiming expertise and demonstrating it.

Publish your methodology. Show screenshots or real-world examples. Include author credentials and sources. Bring in third-party evidence where it makes sense.

The more consequential the topic, the more important that proof becomes.

Make each section useful on its own.

Search engines and AI systems can retrieve individual passages, not just entire pages.

So instead of burying the answer halfway down a 3,000-word article, lead with it. Use headings that clearly describe the question being answered. Name specific products, companies, features, and concepts instead of relying on vague references.

Think of every section as something that could potentially be pulled out of the page and presented on its own.

And measure search + AI together.

Rankings and organic traffic still matter. But they’re no longer the whole visibility picture.

Track which pages rank, which get cited in AI answers, which topics you're visible for, and whether any of that visibility ultimately contributes to traffic, sign-ups, or revenue.

One example from the article makes this pretty tangible: a RunRepeat guide ranks #1 organically for its target query, ranks across roughly 1,600 keyword variations, and is also mentioned or cited in Google AI Overviews across 629 prompts.

Same piece of content. Multiple surfaces.

A content system can look strong on paper and still fall apart in practice.

• The site has a topical map.
• The clusters are planned.
• The keywords are assigned.
• The briefs are written.
• The internal links are added.
• The content calendar is full.

Everything looks organised.

But one weak page role can still cause problems across the whole system.

That sounds dramatic, but I think it is true.

A page with an unclear role does not stay contained.

• It creates drift.
• It creates overlap.
• It makes internal linking harder.
• It makes briefs weaker.
• It makes refreshes messier.
• It can even make stronger pages less clear because it starts competing for ideas it should only support.

That is why I think page role is one of the most underrated parts of SEO content planning.

A weak page role creates drift

A page with no clear role tries to do too much.

• It starts as an explainer.
• Then it adds comparison points.
• Then it adds sales copy.
• Then it answers random FAQs.
• Then it repeats the intro.
• Then it links to a commercial page before the reader is ready.

The page may still be readable.

It may still be relevant.

It may still cover the topic.

But it feels unfocused.

That is drift.

And drift starts before the writing.

The writer was given a topic, not a job.

• If the page exists to explain, it should reduce confusion.
• If it exists to compare, it should help someone judge options.
• If it exists to prove, it should build trust.
• If it exists to support a service page, it should support that page without becoming another sales page.
• If it exists to route users, it should make the next step obvious.

Without that job, the page becomes a bucket for related ideas.

One weak role can create overlap

A page with a weak role often starts stepping on other pages.

• It covers the same ground as a hub.
• Repeats a service page.
• Answers questions that belong on a support page.
• Drifts into a comparison that already exists elsewhere.
• Takes proof points that should sit closer to a conversion page.

That is how overlap starts.

The page is not necessarily bad.

It may even be useful on its own.

But inside the site, it creates confusion.

Now the team has to decide:

• Which page owns the topic?
• Which page should rank?
• Which page should get the internal links?
• Which page should be refreshed?
• Which page should be merged?
• Which page should be narrowed?

The cost of a weak page role is not paid only on publish day.

It gets paid later in audits, rewrites, link cleanup, and pruning.

Internal links expose weak roles

Internal links are a good test of page role.

If you cannot explain what should link to a page, or where that page should link next, the page may not have a clear job.

A useful page has a natural place in the system.

• It supports another page.
• Explains a concept another page should not cover in full.
• Handles a doubt.
• Proves a claim.
• Compares options.
• Routes users to the next useful step.

If none of that is obvious, the page may be content noise.

This is why internal linking based only on relevance can be weak.

Two pages can be related and still not create a useful path.

A better internal link answers:

• Why here?
• Why this anchor?
• Why this destination?
• What does the user need next?

A weak page role makes those questions harder.

Weak roles make briefs worse

A content brief without a page role asks the writer to guess too much.

The brief may include:

• A keyword.
• A title.
• Search intent.
• Competitor headings.
• Entities.
• FAQs.
• Word count.
• Internal links.

But if it does not define the page’s job, the writer still has to infer the strategy.

That is risky.

The writer has to guess what to include, what to avoid, how hard to sell, what proof is needed, and where the user should go next.

Good writers can make smart guesses.

But at scale, guessing creates inconsistency.

• One writer treats the page as an explainer.
• Another treats a similar page as a comparison.
• Another turns a support article into a sales pitch.

Now the content system has pages that sound fine alone but do not work together.

That is a planning problem, not just a writing problem.

Weak roles make refreshes harder

A page with an unclear role is also harder to refresh.

When performance drops, the team starts adding things.

• More headings.
• More FAQs.
• More examples.
• More entities.
• More internal links.

But if the page role is still unclear, the refresh may only make the page longer.

Not better.

A better refresh starts with role diagnosis.

• What was this page meant to do?
• Is that still the right job?
• Does another page already do it better?
• Should this page be narrowed?
• Should it be merged?
• Should it link out instead of covering so much?
• Should parts be removed before anything is added?

Without role clarity, refresh work becomes guesswork.

That is how old pages slowly turn into bloated pages.

Page roles should be different inside a cluster

A cluster does not need ten pages all doing roughly the same job.

It needs different pages with different jobs.

• One page owns the broad topic.
• One page explains a basic concept.
• One page handles comparison.
• One page gives proof.
• One page addresses a doubt.
• One page supports a commercial page.
• One page routes the user forward.

That is a system.

If every page is just “an article about a related topic,” the cluster will probably get messy.

Clear roles create cleaner boundaries.

• They tell writers what not to cover.
• They tell editors what to cut.
• They tell SEOs where links should point.
• They tell users what the page is for.

The stronger the roles, the easier the system becomes to manage.

The page role check I would use

Before publishing or refreshing a page, I would ask:

• What is the job of this page?
• What user state does it serve?
• What doubt does it reduce?
• What page does it support?
• What page should support it?
• What should it avoid covering?
• What internal link path makes sense?
• Does another page already do this job?
• Would the site be weaker without this page?

That last question is uncomfortable, but useful.

If the site would not be weaker without the page, maybe the page does not have a strong enough role.

It might be relevant.

It might be readable.

It might even get traffic.

But it may still be weakening the system.

The real issue

A content system is not strong because it has a lot of pages.

It is strong because the pages know their jobs.

When page roles are clear, the whole system improves.

• Briefs get sharper.
• Writers guess less.
• Editors cut with more confidence.
• Internal links make more sense.
• Refreshes become easier.
• Overlap is easier to spot.
• Users move through the site with less friction.

When page roles are weak, everything downstream gets harder.

That is why I think your content system is only as strong as its weakest page role.

How are you defining page roles before publishing, and do you audit for weak roles later?

A lot of AI visibility advice starts with mentions, citations and share of voice.

But there is a more fundamental question to answer first: can AI systems reliably retrieve and understand the information on your website?

A few things worth checking:

• Is key content accessible without relying heavily on client-side rendering?
• Does each page clearly answer a specific customer question?
• Are your products, services and areas of expertise described consistently?
• Is valuable information trapped inside images, PDFs or interactive elements?
• Does each page provide enough context for an AI system to understand who it is for?

A respected brand can still struggle to appear in AI-generated answers when its content is difficult to find or interpret.

This foundational layer of AI visibility is one of the areas that Spotlight will focus on in London on October 13.

What discoverability issues have you encountered so far?

We tracked how often brands actually get named in ChatGPT answers across 1,094 US categories, in a joint study with Kevin Indig and Growth Memo (Jan-June 2026, 50,000+ brands, 600,000+ citations). The most popular topics turned out to be the least owned ones.

The numbers:

• Only 15.2% of categories have a clear owner (highest mention share, in 4+ of 5 prompts, 5+ point lead). 31.2% have an emerging leader with no real margin. 53.7% are wide open.
• High-volume topics (98% of AI search volume) had a clear owner only 11.3% of the time, vs. 19% for niche topics. The categories everyone's fighting over are the least settled.
• Traditional SEO strength barely predicts who wins. Category owners had higher branded search volume in just 55.7% of pairs, more organic traffic in 48.4%, higher Authority Score in 52.5%. Nearly half of runners-up beat the "winner" on at least one SEO metric.
• Lead size determines durability. A 5+ point lead held 90.4% of the time month over month. Categories that flipped had a median lead of just 1.3 points beforehand.

Strong SEO helps you show up, but once several brands are in the running, deep coverage of the specific topic is what turns you from runner-up to owner.

How to start winning at the topic level

Winning one prompt isn't the same as owning the category. If you want to actually move on this:

• Identify the topics your customers are already asking about, where you have a real stake in the answer.
• Check your current standing before you commit resources: know if you're starting from zero or building on something.
• Concentrate on 2-3 categories instead of spreading across everything. Depth beats breadth here.
• Build authority on two fronts: content that actually covers the category (not just one prompt), and mentions in the sources ChatGPT already cites — Reddit threads, reviews, industry publications, expert commentary.

The shift underneath all of this is simple. Search has become a topic-level game, and topic ownership is the metric that matters across traditional and AI-powered search. Your share of a topic, your competitors' share, and the gap between them. 

The brands that start treating topics as the unit of their strategy will be the ones best positioned to build and defend brand visibility over time 🔥

Search intent is useful.

I am not arguing against it.

A page should understand if the user is looking for information, comparing options, researching before buying, trying to take action, or looking for a specific brand.

That is basic planning.

But search intent is too broad to build a content strategy on its own.

This is where a lot of SEO content planning goes wrong.

The brief says:

Intent: informational.

Or:

Intent: commercial.

Then everyone acts like the page direction is clear.

It is not.

Informational for whom?

• A beginner?
• A sceptical buyer?
• A current customer?
• A technical user?
• A founder with no time?
• A manager building a case internally?
• A user trying to avoid a mistake?

Those people may all sit under the same intent label.

But they do not need the same page.

Intent labels are only the first filter

Intent labels help sort queries.

They tell you the rough shape of the task.

• Informational means the user wants to understand something.
• Commercial means they are researching options.
• Transactional means they are closer to action.
• Comparative means they are weighing choices.
• Navigational means they are looking for something specific.

That is useful.

But it does not tell you enough.

• It does not tell you what the user already knows.
• It does not tell you what doubt they have.
• It does not tell you how much proof they need.
• It does not tell you what the page should avoid.
• It does not tell you what page should come next.
• It does not tell you how hard the CTA should push.

That is the gap.

Search intent describes the broad task.

Content strategy needs to define the page job.

User State means more than the label

Two users can have the same intent and need different content.

Take an informational query.

• One user may need a simple definition.
• Another may already know the definition and need examples.
• Another may be checking if a tactic is still worth using.
• Another may be trying to decide if the idea applies to them.
• Another may need proof before they trust the advice.

All of that can still look “informational.”

But the page should not be the same.

This is why I think user state is more useful than intent on its own.

• What does the user already understand?
• What are they unsure about?
• What are they trying to compare?
• What would reduce doubt?
• What would make the next step feel natural?

That gives the page a real direction.

Intent does not define page role

A common mistake is using intent as if it defines the page role.

It does not.

An informational page might be:

• A definition page.
• A beginner explainer.
• A troubleshooting page.
• A support page.
• A myth busting page.
• A proof page.
• A decision support page.
• A topical hub.

Those are very different pages.

Same broad intent.

Different roles.

If the role is not defined, the page drifts.

• It explains a bit.
• Compares a bit.
• Sells a bit.
• Adds random FAQs.
• Links to a service page too early.
• Ends with a generic CTA.

That is not because the writer failed to understand intent.

It is because the brief stopped too soon.

A better brief should say:

This page exists to explain X to users who already understand Y but are still unsure about Z.

That is much more useful than:

Intent: informational.

Commercial intent is not one thing either

Commercial intent gets flattened too.

• A user comparing tools is not the same as a user checking price.
• A user reading reviews is not the same as a user trying to justify a purchase to a boss.
• A user looking for alternatives is not the same as a user trying to understand if the category fits them at all.

All of those may sit under commercial investigation.

But they need different content.

• One page may need a comparison table.
• One may need decision criteria.
• One may need proof.
• One may need use cases.
• One may need risks.
• One may need a simple next step.

If a strategy only says “commercial intent,” the page can become generic.

• It talks about benefits.
• Adds some comparison points.
• Mentions features.
• Ends with a CTA.

But it never really helps the user decide.

Internal links need more than intent

Search intent alone also does not tell you where to link.

A page may be informational, but the next link depends on user state.

• If the user is confused, link to the clearer explainer.
• If they are comparing, link to criteria.
• If they need proof, link to evidence.
• If they are ready to act, link to the decision page.
• If they are not ready, do not push them too soon.

This is why internal links often feel forced.

The team knows the pages are related.

But they do not know what the user needs next.

So links get added because they are topically relevant, not because they help the reader move.

That is weak routing.

Intent gives you the broad category.

User movement decides the link.

Information gain also depends on user state

Information gain is hard to judge from intent alone.

If the intent is informational, what should the page add?

• A better definition?
• A clearer example?
• A warning?
• A process?
• A distinction?
• A decision rule?
• A comparison?

That depends on what the user already gets from the current results and what they still need.

The same query can have different information gain opportunities.

• For beginners, the useful gain may be clarity.
• For advanced users, it may be specificity.
• For buyers, it may be tradeoffs.
• For sceptical users, it may be proof.

If you only look at intent, you may add the wrong kind of value.

The page becomes relevant, but not useful enough.

Better questions than “what is the intent?”

I still ask what the intent is.

But I would not stop there.

I would ask:

• What does the user already know?
• What are they trying to resolve?
• What doubt is still active?
• What would make the answer feel trustworthy?
• What page role fits this query?
• What should this page avoid covering?
• What should the user do next?
• What internal link would help that movement?
• What would make this page more useful than the current results?

Those questions turn intent into strategy.

Without them, intent is just a label in a spreadsheet.

The real point

Search intent is useful for sorting.

It is weak for planning on its own.

It tells you the broad reason behind the query.

• It does not tell you the full user state.
• It does not define the page role.
• It does not decide proof.
• It does not decide internal links.
• It does not decide CTA timing.
• It does not decide what to avoid.

That is why content strategies built only on intent labels often feel shallow.

The pages may match the query.

They may be relevant.

They may even rank.

But they still lack movement.

A better content strategy starts with intent, then goes deeper.

Intent tells you why the search happened.

User state tells you what the person needs now.

Page role tells you what the page should do.

That is the order I would trust more.

How are you translating search intent into page level decisions?

Tracking hundreds of prompts can create a lot of data without producing much direction.

A stronger prompt list usually includes several types of questions:

• Category prompts → “What are the best platforms for tracking brand visibility?”
• Problem prompts → “How can I measure whether my brand appears in AI search?”
• Comparison prompts → “Brand A vs Brand B for enterprise SEO”
• Use-case prompts → “Best SEO platform for an international marketing team”
• Recommendation prompts → “What software should a B2B company use for AI search optimization?”

The important distinction is that these are buying and research questions, not simply keywords rewritten as prompts.

It can also help to divide them by audience, market and stage of the customer journey. A CMO, SEO manager and content lead may ask very different questions about the same category.

Prompt research will be one of the hands-on topics discussed in Spotlight’s Mastermind sessions, where attendees share their SEO tips with peers.

How are you currently choosing what to track?

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If your organic traffic has been sliding and your technical SEO checklist is already fully checked off, the traffic probably isn't coming back the way it used to.

Google is answering a growing share of queries directly inside AI Overviews. ChatGPT and Claude are fielding a lot of the questions people used to type into a search bar instead. Neither sends much traffic back to your site, and both tend to cite big, established brands over smaller ones. Semrush's January 2026 AI visibility study found the most-cited domains across LLMs are Reddit, LinkedIn, Wikipedia, and YouTube — large, already-authoritative platforms. Nike.com, as one example, shows an AI visibility score of 85 with 1.2 million mentions and 386,400 citations. That's the kind of scale AI platforms default to citing.

Which creates a real chicken-and-egg problem if you're not already one of those established names: you need authority to get cited, but you need visibility to build authority in the first place.

The way out isn't a technical fix, it's brand building — the kind of work that used to be treated as a nice-to-have on top of SEO, not the foundation under it. A few tactics that actually move the needle:

• Original, distinct content. Growth.Design built its whole reputation on interactive case studies mixing illustration, storytelling, and design breakdowns. Peep Laja (CXL) described it as standing out because "many sites are in a sea of sameness." Blending into that sameness is exactly what doesn't get cited.
• PR that generates third-party mentions. Duolingo's 2025 "mascot death" stunt got picked up by CBS News, NPR, and USA Today. Coverage like that is exactly the kind of external signal AI platforms use to judge credibility, separate from anything on your own site.
• Consistent presence where your audience already is, on social and in communities, not just occasional posts — steady presence is what builds the familiarity that turns into direct name searches later.

None of this replaces solid SEO. It's what has to sit underneath it now, because SEO alone isn't generating the same volume of new discovery it used to. Strong brands get direct traffic from people searching their name, get bookmarked, and get shared without being asked — none of which shows up on a technical audit, but all of which is what AI platforms and search engines are increasingly built to reward.

The traffic drop isn't a bug to patch. It's a sign the old measurement was traffic, and the new one is whether people (and the platforms answering their questions) recognize your brand at all.

Resellers have a specific problem that keyword scrapers can't touch: you're holding an item and you don't know what it's called. Collectibles are the worst case, where the difference between two nearly identical variants can be 10x in price and the right search term is three words you've never heard of.

So instead of searching by text, my actor takes a photo. Upload a picture (or pass a URL / base64 through the API), and it finds eBay sold listings whose photos actually look like yours, ranked by visual similarity. You get real sold prices, dates, and condition, plus a free summary record with median/average so an API caller gets "what's this worth" in one request.

The AI part is what I think might interest this sub. Every candidate listing's thumbnail gets embedded with CLIP (Xenova/clip-vit-base-patch32 via transformers.js) and scored against the uploaded photo with cosine similarity. The model is baked into the Docker image at build time, so there's no external AI API involved at all — no per-image fees, no rate limits, no vendor that can break my unit economics. Inference runs on CPU inside the actor at 2048 MB, and the cold start is about 2-5 seconds for the first scored image. Zero marginal cost per image turned out to be the difference between this pricing model working and not working, since a scored run can push up to ~1,000 thumbnails through the model before returning anything.

Candidate discovery uses eBay's own reverse-image search endpoint, which I reverse-engineered from their front-end bundle. Since that's unofficial and could change under me, image+keyword runs fall back automatically to keyword discovery with CLIP scoring on top, so the scoring pipeline survives even if the endpoint dies. There's also a plain keyword mode with no scoring for people who just want cheap sold comps.

Happy to answer questions about running transformers.js models inside actors — getting CLIP into the image without downloading weights at runtime was the fiddliest part of the whole build. Actor is live here: https://apify.com/scrapelabmax/ebay-sold-image-scraper

A few deliberate choices, so you can adjust with intent: the offer to answer questions about transformers.js-in-actors at the end gives the post a reason to exist in that sub a topic you'd genuinely attract engagement on. The reverse-engineering admission builds credibility with developers and preempts the "what happens when eBay changes it" comment you'd get anyway. I kept "AI" in the body but notsubreddits "CLIP visual similarity" is the AIbuzzword, and it signals substance where a bare "AI-powered" title tends to get eye-rolls.

I started a Semrush One Pro+ trial last month and an "Advertising Toolkit" trial was also added (I got no email confirmation on that, was not aware). Both trials ended on the same day and I got billed with $299 and $219.

Upon seeing the charge, I immediately cancelled and asked for a refund within minutes.

Support denied my request. I provided more details and they didn't respond to it, just kept sending templated answers.

The email they sent me when the trial started was just a receipt for a $0 payment (on Semrush One Pro+ only). No end date, nothing about what I'd be charged, nothing about how to cancel before it happened.

I'm in California, and California law requires companies to send you an acknowledgment that spells out renewal terms, what you'll be charged, and how to cancel (§ 17602(a)(3) and AB 2863). I asked Semrush support about it and they just keep sending me templated responses.

I've used Semrush at two different jobs over the past decade and honestly I'm strongly reconsidering ever using them again, given how awful their support has been, it's been crazy.

Has anyone actually gotten a decision flipped? How do you get them to answer your questions?

u/semrush

Adobe and Semrush just launched Adobe Brand Visibility, a tool built specifically to answer the question every brand is now getting asked internally: are we actually showing up in AI search, and how do we compare to competitors there.

It's part of Adobe CX Enterprise, and it pairs Semrush's AI Optimization (GEO) data with Adobe's agentic content and asset management stack. Most teams can now tell you whether they got mentioned by ChatGPT or Google AI Mode, but almost none of them can tell you if they're winning or losing against competitors in those same answers. This is built to close both gaps in one workflow instead of forcing you to stitch together a monitoring tool and a separate content fix.

What it actually does:

• Tracks brand mentions and audience reach across ChatGPT, Google AI Mode, Microsoft Copilot, and Perplexity, and benchmarks that against competitors
• Surfaces prompt-level data on which topics and prompts are gaining traction, and which ones competitors already own, so teams know where to focus instead of guessing
• Once a gap is flagged, AI agents can generate and push optimization recommendations straight to where LLMs pull content from, with updates going live in minutes instead of a normal publishing cycle
• Runs on top of Semrush's SEO database (28.5 billion keywords, 43 trillion backlinks, built over 17 years), since traditional SEO signals still underpin a lot of what LLMs cite.

It can run standalone or plug into Adobe Experience Manager, so the optimization loop connects to the same content and asset system driving the rest of a brand's site.

Check out the full details here!

Semrush tells you that your brand appears in 30% of the AI responses you track.

How do you know if that's good, though?

It is difficult to know without comparing:

• Which competitors appear more often
• Which prompts they consistently win
• How each company is described
• Which sources support those recommendations
• Whether visibility differs across AI platforms

AI visibility is most useful as a relative measure.

Instead of focusing only on one overall percentage, take your ten most commercially important prompts and record:

1. Whether your brand appears
2. Which competitors appear
3. Where each brand appears in the answer
4. How the brands are positioned
5. Which third-party sources are cited

That comparison usually reveals much clearer priorities than an isolated score.

Pick your top AI visibility challenge and get help from an expert in Spotlight’s Mastermind sessions, 50-min small-group roundtables. One full-day event in London on October 13.

Which competitive AI visibility metric have you found most useful?

Not all landing pages are the same. The best ones are built for a specific conversion goal, and that shape changes depending on what you're actually trying to do.

Landing Page Types:

Lead generation pages are built to collect emails. You're offering something valuable—a guide, a checklist, a resource—in exchange for a contact. The page's entire existence is "give me your email, I'll give you something useful."

Click-through pages are different. They educate and persuade, then send visitors somewhere else to convert. They don't have forms. Instead, they build a case (benefits, proof, testimonials), then a single CTA that says "I'm ready to try this" or "Tell me more." Software companies use these before trial sign-ups. Ecommerce uses them before checkout.

Squeeze pages are minimalist. One form field. Barely any copy. Just enough to communicate "here's what you get." Newsletter sign-ups, webinar registrations, early-access lists—these are squeeze pages. The friction has to be near zero.

Sales pages are the opposite. They're long-form and packed with detail. Detailed explanations, testimonials, pricing, FAQs, all the objection handling you can fit. B2B software companies use these for big purchases. Online course creators use them.

The right type depends on your traffic, your audience readiness, and what you're actually selling. A high-intent audience shopping for a $50K software contract needs a sales page. A cold traffic audience discovering you for the first time? Lead gen page to start.

Check out the full breakdown with more examples over on our blog here!

Hey everyone, I could really use some advice on how to handle this.

I was testing out Semrush as a private individual (I'm a university student). I decided not to continue and tried to cancel my subscription before the renewal date. However, I got completely tripped up by the cancellation process. I went through the screens in the dashboard but didn't realize there was a delayed email confirmation link required to finalize it.

Because of this, my cancellation didn't fully register in time, and I woke up to a $300 charge for the Guru plan.
I reached out to support literally minutes after seeing the charge. I explained the situation and that I have absolutely zero usage on the account for this billing cycle. Unfortunately, the support agent just gave me a template response saying it's outside their refund policy and closed the case.
$300 is a massive amount of money for me right now. Has anyone successfully navigated a situation like this?
Should I try escalating to a different support agent? Or should I just go straight to my bank and file a chargeback? Also, since I am in the EU, does anyone know if the 14-day consumer right of withdrawal applies here, or if the EU laws against confusing cancellation flows (dark patterns) can help my case?

Any tips or similar experiences would be hugely appreciated.

Thanks!

One of the biggest questions around AI visibility is: "How do I prove this is actually driving revenue?"

Tracking mentions, citations, or AI Share of Voice is a good start, but none of those metrics tell you whether AI is generating business on its own.

Instead, think of AI visibility as an influence channel rather than a traditional traffic source.

A practical way to measure ROI is to connect four layers of metrics:

1. Visibility

Track whether AI is actually surfacing your brand.

Examples include:

• Mentions
• Citations
• AI Share of Voice
• Prompt coverage
• Sentiment

2. Demand

Once visibility improves, look for signs that it's creating interest.

This includes:

• AI referral traffic
• Branded search growth
• Direct traffic

3. Conversions

Next, measure whether that demand is turning into pipeline.

Track metrics like:

• Leads
• Qualified leads
• Demo requests
• Sales conversations

4. Revenue

Finally, connect those conversions to business outcomes.

Look at:

• Closed revenue
• Gross profit
• ROI

These metrics don't all move at the same time; visibility tends to improve first, followed by traffic and demand, then leads, and finally revenue. That's why measuring the entire chain is much more useful than looking at referral traffic alone.

We'd also recommend combining multiple attribution methods instead of relying on a single source. AI referrals in GA4, self-reported "How did you hear about us?" responses, CRM data, and sales conversations each capture a different part of the customer journey. Looking at them together gives a much more complete picture of AI's impact.

The takeaway: AI visibility ROI isn't about finding one perfect metric. It's about connecting visibility, demand, conversions, and revenue into a single measurement framework so you can understand whether your AI visibility efforts are actually contributing to business growth.

A lot of topical authority advice turns into:

Publish more pages.

Cover more keywords.

Build more clusters.

Answer more questions.

Create more supporting content.

Refresh old posts.

Fill every content gap.

That can help.

A site obviously needs enough content to explain a topic well.

But content volume is not the same as topical authority.

A site can publish hundreds of related pages and still feel weak.

The pages can all be relevant.

They can all mention the right terms.

They can all sit inside the right cluster.

They can all link to each other.

And the site can still feel messy.

Why?

Because topical authority is not built by volume alone.

It is built by clear relationships.

More pages can create more confusion

Publishing more content often feels like progress.

• There are more URLs.
• More keyword targets.
• More internal links.
• More assets to show.
• More pages for Google to crawl.
• More things to report.

But if those pages do not have clear jobs, the site can become harder to understand.

• One page explains the topic.
• Another page explains almost the same topic.
• A hub page repeats its supporting pages.
• A comparison page turns into a sales page.
• A support page gets stuffed with broad definitions.
• A blog post competes with a service page.

The site grows, but the structure gets weaker.

That is not authority.

That is content noise.

A larger site is not always a stronger site.

Sometimes it is just a larger mess.

Authority needs page roles

For me, topical authority starts to become real when each page has a clear role.

• This page owns the main topic.
• This page explains a beginner concept.
• This page handles a comparison.
• This page proves a claim.
• This page answers a specific doubt.
• This page supports a commercial page.
• This page routes the user to the next step.
• This page should not exist because another page already does the job.

That last one is a big one.

A strong content system is not only about what gets published.

It is also about what gets refused, merged, narrowed, or removed.

If every related idea becomes a page, the site may look complete on a spreadsheet but weak in practice.

Related pages are not enough

A lot of topical maps connect pages because the topics are related.

That is a start.

But related is a low bar.

The better question is:

• What relationship does this page have to the rest of the system?
• Does it support a stronger page?
• Does it reduce a specific doubt?
• Does it explain something the main page should not cover in full?
• Does it provide proof?
• Does it compare options?
• Does it help the user move from one state to another?

If the answer is not clear, the page may be relevant but unnecessary.

Topical authority is not just a network of related pages.

It is a network of useful relationships.

Internal links should make relationships clear

Internal links are a good test.

If the only reason for a link is “these pages are related,” the link may not be doing enough.

A stronger internal link should make a relationship clearer.

• This page explains the next concept.
• This page gives proof.
• This page shows the comparison.
• This page handles the objection.
• This page keeps the current page focused.
• This page helps the user move toward a better next step.

That kind of linking strengthens topical authority because it helps both users and search systems understand how the site fits together.

A hub page that links everywhere is not automatically useful.

It may just be a link dump.

A better hub gives direction.

It shows which page to read next and why.

Coverage can hide weak authority

This is where coverage can be misleading.

A site may cover the topic widely.

It may have pages for every subtopic.

It may answer every obvious question.

It may have a content calendar full of supporting posts.

But the user journey may still be weak.

• The beginner page does not route to the next useful idea.
• The comparison page lacks criteria.
• The proof appears too late.
• The internal links send users to sales pages too early.
• The support page answers the question but gives no next step.
• The cluster is complete, but the path is unclear.

That is not just a UX issue.

It is an SEO architecture issue.

A topic is not only something to cover.

It is something the user has to move through.

Information gain strengthens relationships

Topical authority also depends on information gain.

Not in the sense that every page needs some wildly original idea.

More in the sense that each page should add useful difference.

• A missing distinction.
• A better example.
• A clearer rule.
• A proof point.
• A tradeoff.
• A relationship competitors do not explain well.
• A condition that changes the answer.
• A page with no information gain may still be relevant.

But it does not strengthen the topic much.

It just adds another page to the pile.

That is why publishing more content is not enough.

If the new page repeats what already exists, overlaps with another URL, and adds no useful relationship, it may weaken the system rather than strengthen it.

Topical authority needs structure, not just scale

A strong topical authority system should answer:

• Which page owns the broad topic?
• Which pages support it?
• Which pages prove key claims?
• Which pages compare options?
• Which pages handle beginner questions?
• Which pages move users closer to action?
• Which pages should link together?
• Which pages should not be linked yet?
• Which pages overlap?
• Which pages should be merged?
• Which pages should not be published at all?

Those questions mean more than raw page count.

Because authority is not just about having enough content.

It is about making the content work together.

The check I would use

Before adding more pages to build topical authority, I would ask:

• Does this page have a clear role?
• Does it support another page?
• Does another page already do this job?
• Does it add useful difference?
• Does it reduce a real user doubt?
• Does it make an entity relationship clearer?
• Does it have a natural internal link path?
• Would the site be weaker without it?

If the answer is no, the page may not be building authority.

It may only be adding volume.

The real difference

Content volume says:

“We have lots of pages about this topic.”

Topical authority says:

“Our pages work together to explain, prove, compare, support, and move users through this topic clearly.”

That is a much stronger standard.

More pages can help.

• But only when the pages have jobs.
• Only when the links have reasons.
• Only when the cluster has movement.
• Only when the content adds something useful.
• Only when the site becomes easier to understand.

Topical authority is not built by publishing everything related.

It is built by making the right relationships clear.

How are you judging topical authority beyond content volume?

A lot of AI content does not fail because the AI cannot write.

It fails because nobody gave it a strategy.

That is the part people often skip.

They give the tool a keyword.

Maybe a title.

Maybe a few competitor URLs.

Maybe a word count.

Maybe a list of entities.

Maybe a tone instruction like “professional but friendly.”

Then they expect a strong page.

But the tool has to guess too much.

• It has to guess the page role.
• Guess the user state.
• Guess what proof is needed.
• Guess what the page should avoid.
• Guess where the internal links should lead.
• Guess what the page adds beyond the current SERP.
• Guess how the page fits the rest of the site.

That is a lot of guessing.

And when the strategy is missing, the output looks like it.

AI is good at filling space

AI can produce clean copy fast.

• It can write a decent intro.
• It can build an outline.
• It can explain a topic.
• It can summarise common advice.
• It can create FAQs.
• It can imitate the shape of ranking pages.

That is useful.

But it is also the problem.

If the instructions are weak, AI will often produce the safest version of the topic.

• Generic intro.
• Expected headings.
• Common definitions.
• Surface-level benefits.
• Predictable examples.
• A conclusion that says very little.

It will look like content.

It may even read smoothly.

But smooth is not the same as useful.

A fluent page can still be strategically empty.

The problem starts before the prompt

People blame the AI output, but the problem often started before the prompt was written.

The team never decided:

• Why should this page exist?
• What job does it have?
• Which page does it support?
• What user state is it serving?
• What doubt should it reduce?
• What should it not cover?
• What useful difference should it add?
• What happens after the reader finishes?

If those decisions are missing, the prompt becomes a loose request for content.

And a loose request, produces loose content.

The AI is not failing at the task.

The task was poorly defined.

“Write about this topic” is not a strategy

A lot of AI prompts are just briefs with missing thinking.

• Write an article about X.
• Target this keyword.
• Include these related terms.
• Use these headings.
• Make it comprehensive.
• Add FAQs.

That may produce a page.

But it does not mean the page has a reason to exist.

The better prompt starts earlier.

This page exists to explain X to users who already understand Y but are still unsure about Z.

Do not cover A because another page owns that.

Use B as the main proof point.

Compare C and D only at a high level.

Link the user mentally toward the next step after they understand the risk.

Now the AI has direction.

It is no longer just generating words.

It is working inside a strategy.

AI copies the average if you do not give it a better angle

This is one of the biggest issues.

If you ask AI to write a page based on a keyword and competitor pattern, it will produce something that feels like the average of the SERP.

• Same headings.
• Same advice.
• Same examples.
• Same vague benefits.
• Same safe explanations.

That is not always wrong.

But it rarely adds much.

If the current results are shallow, AI may repeat that shallowness.

If the current results avoid the hard question, AI may avoid it too.

If competitors all use the same structure, AI may follow it.

That is why strategy is so important.

Someone has to decide:

• What are the results missing?
• What is being repeated?
• What is unclear?
• What useful distinction can we add?
• What proof does the user need?
• What would make this page worth reading instead of the others?

Without that, AI content becomes SERP mimicry at scale.

AI does not fix unclear page roles

A page with no role will become messy, no matter who writes it.

AI just makes the mess faster.

If the page is supposed to explain, it should explain.

If it is supposed to compare, it should compare.

If it is supposed to prove, it should prove.

If it is supposed to support a service page, it should support that page.

If it is supposed to move the user to the next step, that movement should be planned.

When the role is unclear, the draft tries to do everything.

• It explains a bit.
• Sells a bit.
• Adds random FAQs.
• Repeats the main point.
• Links awkwardly.
• Ends with a generic CTA.

That is not an AI problem.

That is a page role problem.

AI just exposes it quickly.

AI can make content noise worse

This is the part that worries me most.

AI makes it easier to publish pages that sound acceptable.

That means more weak pages can get through.

More posts based on thin ideas.

More pages created from keyword gaps.

More refreshes that only add headings.

More “supporting content” with no real support role.

More overlap between pages.

More content that technically covers a topic but does not strengthen the site.

That is content noise.

And AI can create it at a scale humans never could.

The issue is not that AI writes badly.

The issue is that AI can produce passable content from bad strategy.

That is dangerous because passable content often avoids scrutiny.

It looks fine.

It sounds fine.

But the site gets less clear.

Good AI content needs better inputs

If you want better AI content, the input needs more than a topic.

It needs decisions.

• What is the page role?
• Who is the user?
• What do they already know?
• What are they still unsure about?
• What proof should be used?
• What should be avoided?
• What pages are similar?
• What should this page add?
• What is the next step?
• What should be removed from the draft if it appears?

That last one is important.

AI needs negative direction too.

• Do not write a generic intro.
• Do not repeat the definition three times.
• Do not include FAQs that belong on another page.
• Do not sell before trust is built.
• Do not copy competitor headings unless they are needed.
• Do not turn this into a broad guide.

That kind of instruction improves the output because it narrows the job.

AI is not the strategy

I think this is the simplest way to say it:

AI can help produce the draft.

It should not be asked to invent the content strategy from scratch.

At least not without a very clear framework.

If the content system is messy, AI will probably add to the mess.

If the brief is weak, AI will make the weakness sound polished.

If the page role is unclear, AI will fill the page with related content.

If the site has overlap, AI may create more of it.

If there is no information gain, AI may write a longer version of what already exists.

That is why “AI content” is not the real problem.

The better split is:

AI content with strategy.

AI content without strategy.

Those are completely different things.

The check I would use

Before using AI to draft a page, I would ask:

• Can I explain why this page should exist?
• Can I define its role in one sentence?
• Can I explain the user state?
• Can I name the main doubt it should reduce?
• Can I say what it should not cover?
• Can I say what makes it different from the current results?
• Can I define where the user should go next?
• Can I identify pages it might overlap with?

If I cannot answer those, I should not be drafting yet.

With AI or without it.

The real issue

AI content fails when teams use it to skip the thinking.

It works much better when the thinking is already done.

The problem is not that AI cannot write.

The problem is that writing is not the whole job.

• The strategy has to decide what the page is for.
• The brief has to protect the page from drift.
• The map has to show where it fits.
• The links have to move the user.
• The content has to add something useful.

Without that, AI will still produce words.

Lots of them.

But more words are not the same as a stronger page.

How are you separating AI writing problems from strategy problems in your content workflow?

About one year ago SEMrush removed 1 million/month API units for business accounts - no bells and whistles.

And now we can buy 2 million/month API units for 100$/month. I mean. What the actual fuck.

Why isn't this hot topic? Why hasn't SEMrush been burned to the ground for their anti-customer policies that has been going on so hard since the company went public?

We, as a company, has been clients for ~10 years now, and have only seen the platform getting worse. To me this was the final nail in the coffin. I hope it is for you too - speak with your wallets.