SEO Informatica Labs

Findings from real sites, and the tools to check yours.

Labs is where the method gets tested. Each experiment is written down before it runs, read against the data, and published whichever way it went: the findings, the experiments now running, the tools, and the guides, with the method next to them.

Every record dated, with its method and its limits.

The method is public. This is where it gets tested.

Every page on this site says how we work: a business has to be understood twice, by the machines that decide who gets found and by the buyer who arrives. Labs is where we check that it holds. Each test is written down before it runs, read against the data, and published whichever way it went.

Nothing here is a promise about your site. It is what we have seen on real ones, with the method next to it, so you can inspect the evidence, assess the reasoning or disagree with it.

How a finding gets here

  1. A question worth testing, from a client site, an Outside View or our own pages.
  2. The test, written before it runs: what we change or measure, what we expect to move, and when we read it.
  3. The reading. 14 days to settle, then 28 days of data against the 28 days before. Confirmed, refuted or unclear.
  4. The write-up: what we saw, what it means, what we would do next. Dated, with the method.

The same loop runs on every client site. How we work

Published findings.

What we have measured on real service websites and written up, with the sample, the method and the limits. Cite the edition and the date.

The AI Visibility Benchmark, edition 2026.06.

Our June 2026 review of 50 service-business websites records public-page features under the DUCR model: Discoverable, Understandable, Citable, Routable, scored out of 100. Inspect the recorded findings, recalculate the published figures and see what additional evidence a recommendation needs. The corrected public export retains observations and scores while removing direct identifying fields.

Edition 2026.06, in four lines

  • 50 service-business websites, reviewed in June 2026.
  • Median score: 52.5 of 100.
  • Weakest layer: Citable, at a median of 4 of 30.
  • The 50 records store allowed flags for the five named search crawlers. These are collector flags, not observed platform visits or citations.

Open experiments.

Written before they run, with the date each one is read. The verdict goes here whichever way it goes.

Experiment 001: this site.

The first site the method runs on is our own. The hypothesis: a site built this way gets understood by Google and the AI assistants, found for what it sells rather than only for its name, and named when someone asks an assistant who to use. United States first.

The baseline is the 28 days before the rebuilt site went live on 2 October 2026, from Search Console; new pages kept shipping until 13 October. The first look comes 14 days after the last change, on 27 October; the 28-day comparison completes on 13 November 2026. The decision rules are written down on the experiment's page.

Experiment 001, as written

  1. Hypothesis. Built on the method, this site is found for AI SEO and the searches around it, not only for its name, and the assistants name it.
  2. The change. The whole site, rebuilt to the method: one job per page, the decision pages in the buyer's words, every claim with its source.
  3. What we watch. In Search Console: the searches that are not our name, and the pages they land on. In ChatGPT and Claude: whether we are named for the questions a buyer would ask.
  4. When we read. 27 October 2026, after the settling period. 13 November 2026: 28 days of data against the 28 days before the rebuild went live.
  5. Verdict. Pending.

The baseline, the decision rules and each reading are on the experiment's own page. Read the record

Experiment 002: what the checker finds.

The AI Crawler Checker went live on 13 October 2026. Every check records its outcome and how many Fix, Review, Fine and Your choice labels it produced, never the address, so the checks add up to a picture of how often real pages block, refuse or starve the crawlers behind ChatGPT, Claude and Perplexity.

The first count is published here after 28 days, with the sample size and the limit that comes with it: people check the pages they already worry about.

Experiment 002, as written

  1. Hypothesis. At least one page in five that people check blocks or refuses a search crawler, and more of those blocks sit at the server than in robots.txt.
  2. The change. None to anyone's pages. The instrument is the checker: free, public, one page at a time.
  3. What we count. For each check, the page outcome and the number of each label. No addresses, no results kept.
  4. When we read. 10 November 2026, 28 days after launch; then monthly.
  5. Verdict. Pending.

Run the check on your own page first. AI Crawler Checker

The tools.

The instruments the findings are made with. Free, in your browser, nothing stored. Start with the one that sends a request: the checker.

Start here

AI Crawler Checker

Check whether the crawlers behind ChatGPT, Claude, Perplexity, Google and Bing can reach and read one page.

Check a pageLive result with a copyable text record

  • Calculate the additional clients needed to cover your modeled spend, with assumptions and limits attached.

    Output: CSV or JSON scenario record

    Open tool
  • Separate shared requirements from repeated collection work across brands, markets and teams.

    Output: CSV or JSON scope packet

    Open tool
  • Write one useful answer with its evidence, qualifications and optional next action.

    Output: Working draft as Markdown or TXT

    Open tool
  • Record and review AI assistant citations for your own searches.

    Output: CSV or JSON export

    Open tool
  • Assess keyword candidates with evidence and page decisions.

    Output: CSV or JSON review record

    Open tool
  • Check statements, compare sources and note your editorial decision.

    Output: CSV or JSON review record

    Open tool
  • Inspect pasted llms.txt content, then compare source passages.

    Output: CSV or JSON review record

    Open tool
  • Explore eight sourced findings about AI search, with clear limits.

    Output: Selected findings as CSV

    Open tool
  • Compare documented work and evidence, then keep the questions to ask your shortlist.

    Output: Shortlist brief as TXT

    Open tool
  • Compare tools for monitoring, content and publishing, then prepare an evaluation brief.

    Output: Evaluation brief as TXT

    Open tool
  • Inspect dated subscription prices and limits, size a monitoring workload and retain the questions still to ask.

    Output: Plan CSV or JSON and a requirement record

    Open tool

Working files.

The templates and records behind the guides: blank and worked, as CSV, Markdown, spreadsheets or PDF.

Guides, by the question they answer.

73 write-ups. Every one stands on its own, carries its date, and says what to do about it. Search them, or pick a question.

27 guides

Understood by Google and AI.

The semantics: how Google and the AI assistants work out what a page and a business are about, and why a site can be crawlable and still invisible. Pages with one job, structure that makes sense, the technical basics, and what makes a page worth citing in an AI answer.

  1. Understand AI SEO, AEO and GEO, then identify the work and evidence your situation needs.

  2. Read eight AI search findings with their sources, study dates and limits before using a statistic.

  3. Check indexing, snippets and Google AI inclusion settings, then decide whether the page needs a change.

  4. What Google says you can skip: llms.txt, chunking, AI rewrites, fake mentions, AI schema.

  5. Inspect our live-file audit, check pasted llms.txt text and decide who will use and maintain the file.

  6. What AI visibility actually needs from a service business: access, clear service pages, proof, local signals and routes.

  7. Find which pages and measures changed, separate confirmed faults from update hypotheses and prepare a diagnostic handoff.

  8. Compare crawler policies, verify a reported block and retain the evidence for a narrow configuration decision.

  9. Separate ChatGPT search access, training preferences and user visits, with a clear check for your web team.

  10. The DUCR model: four areas to inspect when deciding what a page needs, with evidence before a fix.

  11. Turn checked material into a useful answer section, with three worked examples and a draft composer.

  12. Investigate an apparently wrong business fact, compare its sources and prepare a correction packet.

  13. Map buyer questions to useful page roles, then investigate overlap before changing what already exists.

  14. When a service, a place or an industry deserves its own page, and the rules that stop them duplicating each other.

  15. Four before-and-after cases of giving each page one job.

  16. Keep, reposition or combine: compare the buyer decisions and evidence before changing two overlapping pages.

  17. Publishing about AI search without splitting your own pages: ownership, borders, redirects.

  18. Where a search term belongs: the service page or the post.

  19. Choose where the next effort belongs: an existing page, a missing buyer answer or a problem content cannot solve.

  20. The complete checklist for a service page, without turning it into generic SEO copy.

  21. One service, and the questions buyers ask before they contact you, mapped to the pages that answer them.

  22. Choose a useful next step from one article, with link wording and destinations that answer the reader's remaining question.

  23. Plan the connections around one service: what buyers need, where the answers exist and which links deserve attention.

  24. Separate a missing-index problem from an indexed page that is not reaching the searches you care about.

  25. Location pages that serve real local visitors, and the doorway patterns Google treats as spam.

  26. City pages, area pages or one coverage page: how to choose without building dozens of thin pages that compete.

  27. How the Google Business Profile, the service pages and reviews work together for local searches.

4 guides

Chosen by buyers.

How buyers choose: understanding the service, checking relevant proof and taking the next step. Investigate visitor fit, page clarity and enquiry handling before deciding what to change.

  1. Find the first enquiry gap to investigate: contact delivery, relevant visitors, service fit or the next step.

  2. Help a suitable buyer understand the service, assess the work and decide whether to contact you.

  3. Choose evidence that answers the buyer's concern, including relevant cases, samples and confidential work.

  4. Seven business questions for one priority service page, with a worked example and a matching printable brief.

9 guides

Using AI to grow.

The AI systems: what AI changes in how buyers search and decide, and what a small team can do with it: check how the assistants describe you, and read your own numbers. This group is the newest, and it is where most new write-ups will land.

  1. Read the dedicated AI report, compare the same scopes and keep unavailable export values out of the calculation.

  2. Inventory main-site, campaign and booking events before validating a hostname Include filter.

  3. Group bot requests by page role, retain coverage limits and distinguish repeated visits from pages reached.

  4. Compare monitoring, content and publishing tools by task, documented capabilities and practical limits.

  5. Inspect 30 candidate phrases, their evidence and page decisions, then keep your own research record.

  6. Review a teaching draft claim by claim, including sources, qualifications and metadata.

  7. Find recorded ChatGPT visits in the current GA4 reports, then check entry pages, completed actions and received enquiries.

  8. A working scorecard and enquiry log for deciding whether visibility is reaching suitable buyers and what to improve next.

  9. What changed in Google's AI search and ChatGPT search in the second quarter of 2026, what stayed stable, and what to do.

13 guides

Before you hire anyone, including us.

The questions owners ask before they spend on SEO or a website, answered the way we would answer them on a call: what it costs, how long it takes, what should change and when, and what to have ready before you talk to anyone. These are this site's own support content, built the way we build it for clients.

  1. Check readiness and model the contribution needed to cover a defined commitment before buying.

  2. What does AI visibility work cost?

    14 min read

    Software, advice or implementation, what changes the scope and what the fee covers.

  3. What ships, what changes and what to review: delivery dates and the 42-day reading.

  4. Launch checks, relevant enquiries and the next investment: practical 30, 60 and 90-day reviews with clear responsibilities.

  5. Repair or rebuild: compare the actual constraint, what can be retained and the work each route requires.

  6. Keep useful pages, map changed URLs and review launch evidence with blank and fictional worked records.

  7. Plan a first website with a whole-project brief, page responsibilities and a fictional worked example.

  8. Compare seven providers' scope, delivery responsibilities and evidence, including our disclosed own offer.

  9. Compare providers on work, evidence and responsibilities, with a worksheet to record their answers.

  10. Choose a public review, a focused investigation or a conversation by the decision it should help you make.

  11. Who researches, writes, implements and approves: practical answers about working with us and your existing team.

  12. An optional one-page note for the business question you want to work through. Rough notes are enough.

  13. For agencies: when white-label delivery beats hiring, and what a healthy partner model looks like.

20 guides

SEO for your industry.

Practical page plans for service firms: start with your actual offer, inspect the search task and give each useful page a clear job.

  1. SEO for HR consultants and advisory firms

    6 min read

    Plan employer-facing HR pages, distinguish advisory work from recruitment and inspect a published service-navigation example.

  2. Clarify managed IT, helpdesk and specialist support, then use a worked page map to evaluate SEO work.

  3. Separate employer discovery from candidate reach, with a staffing page map and vacancy lifecycle guidance.

  4. Map the actual work of an accounting or bookkeeping practice to useful pages and relevant business searches.

  5. Map modernization, integration and development-team engagements to distinct pages, with evidence of the work.

  6. Turn an accurately scoped project record into useful discipline-page evidence and clear publication decisions.

  7. SEO for contract manufacturers

    6 min read

    Use a capability inventory to choose process pages, combine material variants and hold unsupported sector claims.

  8. SEO for virtual office providers

    6 min read

    Separate address plans, workspace offers and location details, with distinct checks for operator and tenant eligibility.

  9. Check proposed searches against testing and advisory services, then write an accurate explanation of an accepted opportunity.

  10. Turn an unsupported operational claim into useful reasoning, with evidence to examine, alternatives and explicit limits.

  11. Sort shipper discovery from tracking, jobs and software searches, then define one accurate service-page improvement.

  12. SEO for corporate training companies

    5 min read

    Turn a program brief into useful public copy and distinguish completion, satisfaction, assessed skills and later outcomes.

  13. Audit maintenance, replacement and repair pages, then complete a clearer commercial HVAC service explanation.

  14. Turn an equipment list into a useful installation and integration page, with clear handover and support.

  15. Connect a testing capability and its accreditation scope to a useful service page and a clear search task.

  16. SEO for industrial maintenance companies

    6 min read

    Turn a production-equipment maintenance brief into relevant search targets and a concrete service-page improvement.

  17. Turn an assessment deliverable into useful service-page content, with a completed dependency-record example.

  18. Connect a finished portfolio example, its visual and the studio's contribution to a useful service explanation.

  19. Turn a defined business-contract engagement into a clear service page, supporting article and discovery check.

  20. Complete a membership-information audit, correct access claims and publish a useful comparison of physical workspace plans.

What the method produced.

Results live on the Proof page, each with its period and its source: the Xporate case study, with figures from the client's own Search Console; an HR advisory firm's rebuild; and a manufacturer in Wales, unnamed by agreement. When a client agrees to be named, they are named. When they don't, the result is still shown, in the words we can stand behind.

Questions about Labs

What is Labs?

Where the method gets tested. The published findings, the experiments running now with their reading dates, free tools that run in your browser, and guides by the question they answer. Every record carries its date, method and limits; teaching examples are labelled.

Can I use the research?

You can inspect and download the AI Visibility Benchmark's dataset, codebook and rubric. Cite the edition and export date when referring to a finding. Contact us about reuse permissions; the dataset page explains the public files.

Do these findings apply to my business?

They are observations from real sites, not a forecast for yours. If you want to know where your own site stands, the Outside View says so, in writing, free.

How often does Labs change?

When an experiment finishes. Each write-up carries its date, and we update the ones that stop being true rather than leaving them up.

Where did Insights go?

Here. Insights became Labs in October 2026, and every article kept its address.

Can I suggest a test, or a market to benchmark?

Yes. Write to us with the question or the market, and say why it matters to you.

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