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Free GEO Playbook: a step-by-step method for getting named in AI answers

A free, open method for any industry, built on 110 Singapore buyer questions and open citation data.

Publisher
Canlah AI
Version
1.0
Published
Updated
Licence
CC BY 4.0

Want the five steps before the detail? Start with the 11-section quick guide below. Go to the quick guide ↓

Free to read and reuse · No ranking promises · Not legal advice

The numbers behind this edition

  • 22 / 307

    ChatGPT citations that were also in the same question’s Google top 10

    Round 1 · 60 questions · 23 Sep 2026

  • 19 / 507

    cited URLs that ChatGPT and Google AI Mode shared for the same question

    Round 1 · 60 questions · 23 Sep 2026

  • 917

    AI citation records, all published as open data

    110 questions · 23 Sep 2026

GEO Playbook (v1.0, September 2026) is Canlah AI’s free, CC BY 4.0 GEO (generative engine optimization) method for becoming more likely to be named when buyers ask ChatGPT and Google AI Mode. It is built on 110 Singapore buyer questions asked on 23 September 2026 and published as open data: 917 citation records and 141 ChatGPT answers. Two findings shape it. In the first round of 60 questions, only 22 of 307 ChatGPT citations (7.2%) were in the same question’s Google top 10, against 89 of 219 for AI Mode; and for the same question, the two engines shared just 19 of 507 cited URLs (3.7%). Ranking on Google and being cited by AI are different jobs.

All from one measurement on 23 September 2026, so this is a snapshot; answers in the ChatGPT and Google apps can differ. The data is open (DOI 10.5281/zenodo.23005020) →

The quick guide in 11 sections

One conclusion and one diagram per section. Each ends with a link to the matching section of the full playbook.

01 / 11

ChatGPT cites the source; Google AI Mode cites the summary

Dental and aesthetics
ChatGPT · government and public bodies76%38/50
AI Mode · clinics and other commercial sites75%39/52
Family law
ChatGPT · .gov.sg77%46/60
AI Mode · law firms and other commercial sites69%36/52
E-commerce
ChatGPT · product pages54%of 68 citations
AI Mode · Google Shopping cards44%12/27; zero shared URLs
Figure: Same questions: ChatGPT leans on government and official pages, AI Mode on peers and platforms

Of 54 questions both engines answered, 36 shared not one URL. Work each engine separately. Only about 1% of AI Overview visits click a link (Pew, 2025, US sample): the prize is being named. Snapshot via model APIs, 23 Sep 2026.

Read this in the full playbook →

02 / 11

A Google top-ten spot covers about 40% of AI Mode, under 10% of ChatGPT

Cited URL in Google's top ten for the same question
AI Mode41%89/219
ChatGPT7%22/307
Cited URL from forums, social or video
AI Mode14%30/219; YouTube 13, Reddit 10
ChatGPT0%0/307, round one
Figure: Google's top ten covers about four in ten AI Mode citations but under one in ten for ChatGPT; in round one ChatGPT cited no forums, social or video

Baseline: Google's organic top ten for the same question, same day, Singapore. By registered domain: AI Mode 53%, ChatGPT 25%. ChatGPT cited no forum or social pages in round one; asked whether one tuition centre was good, it cited a local parents' forum twice. Model APIs, 23 Sep 2026; the app may differ.

Read this in the full playbook →

03 / 11

Three things you already do: baseline, access, identity

What you already doThe extra AI check
BaselineAsk 30 real questions; save answers as-is
Access: robots.txtIs OAI-SearchBot (ChatGPT search) blocked?
Access: nosnippet, firewallTurn off nosnippet and "Block AI bots"
Access: JavaScriptNo JS-only prices; AI crawlers skip JS
Identity: NAPGoogle, Bing, Apple, Yelp, Foursquare match exactly
Identity: facts pagePlain web table: name, UEN, address, phone
Figure: Technical and local SEO habits carry over; add one AI-specific check to each

These are pass or fail: a firewall blocking AI, prices in images or mismatched addresses, and every page scores zero. Save answers before changing anything. Don't just append an allow block to robots.txt; it can cancel existing rules. Major AI crawlers skip JavaScript (Vercel & MERJ, 500M+ fetches).

Read this in the full playbook →

04 / 11

Before you write: how tightly is your advertising regulated?

If this is youYou're in
No licence needed, no health, results or earnings claimsNo specific rules
Licensed; no price ranges, or testimonials or comparisons bannedStrictly regulated
Licensed; testimonials or comparisons allowed with conditionsPartly restricted
Licensed, but no specific advertising rulesNo specific rules
Figure: Three questions tell you how tightly your sector is regulated

Unsure? Go stricter: too loose can mean a fine, too strict only costs a few tactics. No licence but selling regulated products like supplements or devices? Your copy is still regulated. Strict-sector red lines: no "from" prices or ranges, no testimonials or before-and-after photos, no competitor comparisons, no asking for reviews, no paid Best or Top list spots.

Read this in the full playbook →

05 / 11

Write down 30 questions buyers really ask, and keep them all quarter

With a location (e.g. in Singapore)18 questionsat least 60%
With price or cost9 questionsat least 30%
Category word only3 questionsat most 10%
Figure: The mix of 30 questions: floors for location and price, a cap on bare category words

Source questions from customers' words before buying, ad keywords, autocomplete and Search Console, and competitor pages. Never let AI invent them. Asking just "divorce lawyer", AI Mode listed 0 firms in 10 cities; adding "near me" restored every one (PRWeb, overseas). Our 6 Chinese questions drew 64 citations; fewer than 5 were Chinese pages, all in AI Mode.

Read this in the full playbook →

06 / 11

AI copies first sentences, mostly from the top 30% of the page

Between H1 and the first H232 citations43%
First line or first table under H2 one or two23 citations31%
Middle and later sections17 citations23%
Figure: Of the 75 citations we could trace to a sentence on the page, about seven in ten sit in the top 30%

On 15 of 18 law pages, the copied line opened a paragraph. Counter-example: an H2 opening "is a complicated matter" was skipped; a direct answer in the same page's FAQ was copied. Tables go whole, headers included. Positions are estimated by eye; answers were stored to 600 characters.

Read this in the full playbook →

07 / 11

Price guide pages: build them like the ones AI cites

Title<Category> Cost in Singapore (2026), with year
H1A statement, not a question
Summary40–130 words: your price + what drives itAI quotes thisRegulated
First subheadingHow Much Does <Category> Cost?
First lineAt <Brand>, <Category> costs S$X (incl. GST)Regulated
Price tableEverything you sell: type / price / best forAI quotes thisRegulated
Price factors3–5, one sentence each
FAQOnly restates the page's answers
Price list as an imageAI can't read it; prices go in the first-screen HTMLDon't
RequiredOptionalAI quotes thisRegulatedDon't
Figure: How a price guide page runs top to bottom; cited pages are copied most at the opening summary and first price table

8 of 8 cited dental price blogs put the year in the title; 10 of 11 cited clinic pages used a statement H1. Exact numbers beat tidy layout: one tutor agency's card said $35–$55, its table $25–$35; AI used the table. Supporting data: price queries trigger AI Overviews 92%–97% of the time (Whitespark, 540 US queries).

Read this in the full playbook →

08 / 11

The SEO extras you know are rare on cited pages

Common SEO extraCited pages that had it
1,800–3,000 wordsLaw 2/18, tuition 2/8, e-commerce 3/11
Authoritative outbound linksDental 1/16, law 2/18
Named individual authorLaw 2/18; medical pages the exception, 6/12
3+ question-style H2sLaw 3/18, SaaS 4/13
FAQDental 11/16 had one; about 6 copied lines came from FAQs
llms.txt, blocking GPTBotGoogle says llms.txt isn't needed; GPTBot is for training
Figure: Things often treated as must-dos turn up on few cited pages

These are counts on cited pages, not experiments: they aren't what gets a page cited, but that doesn't prove they're useless. Cited pages ran as short as 40 words; the median was about 1,300–1,500. On medical pages, do name the doctor. 88.2% of sites blocking GPTBot still get cited (BuzzStream).

Read this in the full playbook →

09 / 11

"Who's best?" isn't won by writing a page

What ChatGPT citesWhat AI Mode cites
Tuition (5 questions): ~35 of 44 URLs centres' own sites; lists 0Tuition: mostly ranking lists
Family law (1): Doyle's, Legal500, ChambersFamily law: firm sites, directories, map cards
best CRM (1): official pricing pages, 4/4best CRM: Reddit, YouTube, trade media
Figure: Asked "who's best", neither engine cites a business's own "best" article

Pool the sources across your 30 answers; the 20 most frequent are your targets. Correct what's wrong; if you're missing, start with free official directories and association profiles. Supporting data: 84% of AI citations come from others writing about you, 0.3% from paid placements (Muck Rack). Law and CRM rest on one question each.

Read this in the full playbook →

10 / 11

Same questions monthly, three numbers

Monthly numberWhat counts as a win
Times AI names youBeyond normal swing, same direction two months running
Top-20 cited pages that mention you and were cited this monthOne more a month; at least 3 more in 90 days
Facts AI gets wrong about youDown to 0, with before-and-after screenshots
Figure: Read the three numbers separately; each has its own win, never combine them into one score

Re-ask your questions three times in one week to see how much results swing on their own; only bigger moves are real. Switch questions or tools and you can't compare. Put a number only you have on your price page, then search next month's answers for it. Nothing moving? Recheck access and identity. Watch just one? Make it errors.

Read this in the full playbook →

11 / 11

46 cited page types, counted one by one

  1. 9Both engines60 buying-decision questions, both engines
  2. +33New wording"What is X", "how do I", ChatGPT only
  3. +5Outside teardownsPage types from public teardowns
  4. −1MergedData-report pages folded into statistics sources
  5. 46TotalOne blueprint each, in the full playbook
Figure: Question wording decides page types: ask only about price and "who's best" and you see just 9

The full playbook, in English and Chinese: 17 chapters including 4 appendices, a blueprint for each of 46 page types, sources and sample sizes for key numbers, plus a Dental & Aesthetics Edition and a Law Firms Edition. The open-source version on GitHub is in English, ready for your AI assistant to check your site.

Want help with round one? admin@canlah.ai · WhatsApp +65 8110 0234

Read this in the full playbook →

Contents · General Edition 17 chapters

Read it online, one page per chapter.

  1. Chapter 0

    1. Start here: how to read this book, and how tightly your advertising is regulated

      The 90-day reading order, how strict your industry's rules are, and which pages you can't build

      4 sections
      1. 0.1 The book in one sentence, and the 90-day reading order
      2. 0.2 Decide which side you are on first
      3. 0.3 Which page types are limited for you, and what to build instead
      4. 0.4 The three labels for compliance sentences, and the stop-and-escalate rule
  2. Chapter 1

    1. How AI picks its answers: what buyers ask, and which pages ChatGPT and Google's AI cite

      AI reads pages live, the two engines cite different pages, and three things decide whether you get named

      4 sections
      1. 1.1 How buyers ask, and what AI reads
      2. 1.2 Two legs: ChatGPT looks for the source, AI Mode for second-hand summaries
      3. 1.3 Three gates and three paths
      4. 1.4 Three kinds of things not to do
  3. Chapter 2

    1. Let AI read your website: check first, then fix the settings

      Access logs, robots.txt, firewalls and nosnippet; save how things stand before you change anything

      9 sections
      1. 2.1 The five gates at a glance, and gate 0: access logs (read-only)
      2. 2.2 Gate 1 read-only audit: what to check in nosnippet, robots and the WAF
      3. 2.3 Gate 2: four identities, fetched live (read-only)
      4. 2.4 What each crawler is for, and judging the door leg by leg (read-only)
      5. 2.5 Gate 3, read-only: connect the two free AI reports
      6. 2.6 Fixing the door: nosnippet, the four-step robots merge, the WAF allowlist
      7. 2.7 Gates 3 and 4: indexing paths, and JSON-LD sealed once
      8. 2.8 The launch gate for every page
      9. 2.9 Door-layer troubleshooting and this chapter's acceptance checks
  4. Chapter 3

    1. Get AI to recognise your business: the same facts everywhere

      Name, address, phone, licences and other facts, word for word the same on your site and every profile

      6 sections
      1. 3.1 Why this comes before writing pages · The two-hour checklist
      2. 3.2 The fact table and the organisation facts page
      3. 3.3 Person pages and six-trace alignment
      4. 3.4 Third-party credential tiers, Wikidata and the five business profiles
      5. 3.5 The brand six questions, and what to do when you find an error
      6. 3.6 The positioning-statement myth, and the exits from this chapter
  5. Chapter 4

    1. Which questions to go after: pick 30 buyer questions and record how AI answers them today

      Where the questions come from, which are worth winning, and saving today's answers as your starting point

      8 sections
      1. 4.1 The full target-picking process and the twelve pre-start questions
      2. 4.2 The question pool: where the 30 questions come from, how they are balanced, how they are signed
      3. 4.3 Coarse screen and piles, full rounds, and the brand-six baseline
      4. 4.4 The web control leg and the frozen baseline (the book's only full spec)
      5. 4.5 Buyer types, annual opportunity value and the three checks
      6. 4.6 Four states, two denominators and the abstain line
      7. 4.7 Actions by state, the ten question types and this quarter's slots
      8. 4.8 Two shortcuts and this chapter's checklist
  6. Chapter 5

    1. Writing pages (1): the 46 page types AI cites, and the rules for every page

      The page-type map, the limits by how tightly you are regulated, and the rules every page follows

      10 sections
      1. 5.1 The page-type map: 46 types, six families, three evidence tiers, availability by side
      2. 5.2 Quick reference by side (1): identify the advertiser first; prices, promotions and freebies, result numbers
      3. 5.3 Quick reference by side (2): testimonials and reviews, comparisons, lists, titles, outbound links, FAQ and captions
      4. 5.4 The 30-day writing order and the three mechanical gates
      5. 5.5 The page unit: one intent cluster, one page
      6. 5.6 Two legs, two kinds of sentence
      7. 5.7 Seven rules that hold for every page type
      8. 5.8 The conclusion block, the density gate and the source gate
      9. 5.9 Content form, FAQ, Chinese pages and other-language pages
      10. 5.10 Shared parts for all page types: six checks for numbers, no public price, billing units, dates and schema
    2. Writing pages (2): the 9 most-cited page types, block by block

      Full blueprints for price pages, price guides, comparisons, lists, one-question pages and more

      10 sections
      1. 5.11 Single-service price page (pt01)
      2. 5.12 Price guide page (1): why it is always the first page (pt02)
      3. 5.13 Price guide page (2): blueprint, column headers, sentences (pt02)
      4. 5.14 Official pricing page (pt03)
      5. 5.15 Comparison page (pt04)
      6. 5.16 List page (pt05)
      7. 5.17 One question, one page (pt06)
      8. 5.18 Eligibility and process page (pt07)
      9. 5.19 Remedy and second-opinion page (pt08)
      10. 5.20 Entity anchor pages: three subtypes, and the product detail page (pt09)
    3. Writing pages (3): quick cards for 33 more page types

      Subsidies, reviews, FAQs, step-by-step guides, branch pages, legislation and more

      9 sections
      1. 5.21 Tier-B price types: subsidy limits, parameter basis, category lists, calculators, time-limited promotions
      2. 5.22 Tier-B selection and reputation types: third-party reviews, sentiment and forums, review aggregates, self-built reputation, verdict-first
      3. 5.23 Tier-B questions and rules types (1): regulatory obligations, definitions
      4. 5.24 Tier-B questions and rules types (2): procedure steps, preparation lists
      5. 5.25 Tier-B questions and rules types (3): schedules, collected FAQ, policy hubs, change notices, misconceptions
      6. 5.26 Tier-B entity and product facts types (1): branches, verification pages, directory listings
      7. 5.27 Tier-B entity and product facts types (2): compliance proof, terms, how-to docs and integrations
      8. 5.28 Tier-B primary sources (1): legislation, regulator guidance, official replies, device documents, case law
      9. 5.29 Tier-B primary sources (2): statistics sources, registers
    4. Writing pages (4): 4 unverified page types, and checks before you publish

      Five steps before each page goes live, the red line on lying, and common mistakes

      3 sections
      1. 5.30 The four tier-C types: unverified page types
      2. 5.31 Handing over: five steps per page, the red line on lying, and self-checks
      3. 5.32 Master table of common mistakes
    5. Writing pages (extra): producing hundreds of pages, from studying a competitor to launching in batches

      Picking who to learn from, choosing topics, the writing pipeline, checking the numbers, launch and review

      10 sections
      1. 5.D1 The seven steps at a glance, and what to tell clients
      2. 5.D2 Pick the right study target: the competitor that wins on on-site form
      3. 5.D3 Take the architecture apart until you can write from it
      4. 5.D4 Correct with measurement: the competitor sets the skeleton, measurement sets the details
      5. 5.D5 Topic selection: turn every head and long-tail keyword into a list with one main query per page
      6. 5.D6 The production pipeline: three agent passes per article, plus automated lint gates
      7. 5.D7 Six traps we hit: build the safeguards in before you start
      8. 5.D8 Source audit: trace every number in data reports to its source
      9. 5.D9 Launch in batches: from launch day to the keep-or-cut decision on day 45
      10. 5.D10 Add new keywords every month: new keywords come in, a person reviews before anything goes out
  7. Chapter 6

    1. Beyond your website: get onto the 20 pages AI already cites

      Directories, media, associations, reviews and lists, checked every month

      8 sections
      1. 6.1 Where the effort goes, and two numbers that must not sit side by side
      2. 6.2 The send gate, paid listings and the citation-slot table
      3. 6.3 Six dispositions, bylined contributions and outreach letters
      4. 6.4 Three source groups, and the Group B actions
      5. 6.5 Reviews: how to ask, how to reply, how to fill the empty slot
      6. 6.6 Annual rankings and off-site asset decay
      7. 6.7 Long videos narrated by the named expert
      8. 6.8 Off-site verdicts, common mistakes and rituals to cut
  8. Chapter 7

    1. Monthly retest: how to tell whether it's working and what to do next month

      Ask the same questions every month, and tell real change from random noise

      5 sections
      1. 7.1 What a retest produces, and the rulers
      2. 7.2 The noise band, the page-level signal and the ten monthly steps
      3. 7.3 Not-moved triage and next month's three points
      4. 7.4 Holding position and the 90-day settlement
      5. 7.5 Ruler discipline: change the ruler and nothing is comparable
  9. Chapter 8

    1. Using this in a new industry: four steps to work out your approach

      Ten questions, how tightly you are regulated, ten factors and one decision table

      9 sections
      1. 8.1 Four steps for a new industry: ten questions → side check → ten axes → decision table
      2. 8.2 Five steps to decide the side, and three criteria
      3. 8.3 The ten axes (1): page types, containers, anchors, regulation, question shapes
      4. 8.4 The ten axes (2): decision-makers, capacity, attribution, half-life, language
      5. 8.5 The decision table and rulings
      6. 8.6 Seven tactics: how regulated and unregulated sides differ, and why each moves rankings
      7. 8.7 Cheap tactics on the unregulated side, and substitutes on the regulated sides
      8. 8.8 Unregulated ≠ easy: admission criteria J0–J7
      9. 8.9 Cross-border: whose law applies
  10. Appendix A

    1. The evidence: the numbers and sources behind every conclusion

      Conclusions, sample sizes, and what you can say publicly

      5 sections
      1. A.1 Evidence for mechanics, the door and identity
      2. A.2 Evidence for picking targets, writing pages, off-site and retests
      3. A.3 Page-type measurements (1): two legs, seven rules, the nine tier-A types
      4. A.4 Page-type measurements (2): tier B and C samples, and the AI Mode retest list
      5. A.5 List of sources
  11. Appendix B

    1. Templates: robots.txt, wording, outreach letters and tables

      Copy-ready masters, what to tell clients, outreach and review replies, and work-order headers

      5 sections
      1. B.1 Door templates
      2. B.2 Approved wording and scripts
      3. B.3 Outreach emails and review replies
      4. B.4 Headers for work orders, ledgers and monthly reports
      5. B.5 Blueprints for unverified page types (for industry editions to include)
  12. Appendix C

    1. Five industries side by side

      Dental and aesthetics, family law, tuition, B2B software and e-commerce across ten factors

      1 sections
      1. C.1 Ten-axis values for the five industries covered, and three things for week one
  13. Appendix D

    1. How to write numbers, and the glossary

      Rules for labelling numbers, and the book's terms

      2 sections
      1. D.1 Number discipline: how to label numbers, and what stays internal
      2. D.2 Glossary

Industry editions

Each industry edition covers only what differs from the General Edition and links back to the sections it builds on.

Your industry isn’t here? General Edition Chapter 8 shows how to judge a new industry yourself →

Downloads

The Chinese original, with its own PDFs and PPTX, is on the Chinese page.

Version for AI assistants

On GitHub the same method is written as instructions an AI assistant can follow to check your site step by step, each step linking back to the matching chapter here. Every chapter of the full playbook also has a Markdown file an AI assistant can read on demand; the contents are at /playbook/index.md.

GitHub: Canlah-AI/geo-playbook

The measurements behind every number are public too: 110 questions, 917 citation rows, 141 ChatGPT answers, CC BY 4.0. Dataset (DOI 10.5281/zenodo.23005020) · Cite the playbook: doi:10.5281/zenodo.23005022

CC BY 4.0 · Content is licensed CC BY 4.0, code MIT · © Canlah AI. When you reuse or adapt it, credit “Canlah AI · GEO Playbook” and link the original page.

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