Identity: https://thegeolab.net/identity.jsonld

Generated by Rank Math SEO, this is an llms.txt file designed to help LLMs better understand and index this website.

# The GEO Lab: Generative Engine Optimisation Research

## Sitemaps
[XML Sitemap](https://thegeolab.net/sitemap_index.xml): Includes all crawlable and indexable pages.

## Posts
- [Fan-out Query Length and Citation Rate: 225 Queries, Inverted Result](https://thegeolab.net/e030-fan-out-length-citation-rate-results/): Pre-registered experiment measuring Perplexity citation rate across three fan-out query length tiers — short queries cited at 61%, long queries at 13%, with H1 falsified and namespace drift confirmed as the mechanism.
- [The SEO Floor: Why GEO Without SEO Is a Strategy Built on Air](https://thegeolab.net/seo-floor-geo/): GEO without SEO is mechanically incoherent. AI search retrieves from organic indexes before generating responses — remove the SEO floor, and there is no retrieval pool for GEO to operate on.
- [10 Things the Four AI Visibility States Don’t Tell You](https://thegeolab.net/four-states-caveats/): Ten edge cases, transitions, and measurement boundaries that sit beneath the four AI visibility states framework — essential caveats for anyone using the model in practice.
- [GEO vs AEO vs LLM SEO: What’s the Difference?](https://thegeolab.net/geo-vs-aeo-vs-llm-seo/): GEO, AEO, and LLM SEO compared. AEO is a subset of GEO, not a synonym. LLM SEO is a misnomer. The terminology matters for scope.
- [Perplexity Cites the Same Pages Every Day: A 14-Day Zero-Variance Replication](https://thegeolab.net/e027-perplexity-zero-variance-replication/): 14-day Perplexity measurement confirms zero inter-day citation variance. Q02/Q05/Q06 stable across all runs. T2 rate 0/70. T1 grew from 60% to 82% average days 6–14.
- [Citation Rate and Query Length — E030 Pre-Registration | The GEO Lab](https://thegeolab.net/e030-fan-out-length-citation-rate/): E030 pre-registers the hypothesis that Perplexity citation rate increases with query length. A frozen 45-query set across 3 length tiers, 3 stably-cited pages, 5-day measurement window starting 2026-05-19.
- [Claude Leads Perplexity. Ahrefs Shifts to AI Memory Brand. The May 2026 GEO Brand Citation Index Is Out.](https://thegeolab.net/claude-leads-perplexity-ahrefs-ai-memory-brand-may-2026-geo-brand-citation-index/): May 2026 GEO Brand Citation Index: Ahrefs returns to AI Memory Brand with −39.13 delta. Claude hits +60.87 — highest in three runs. SEO vertical has three simultaneous AI Memory Brands.
- [Zero-Click AI Overviews: GEO as the Answer](https://thegeolab.net/zero-click-ai-overviews/): AI Overviews reduce organic CTR by up to 58% on uncited pages. GEO is not optional — it is the structural answer to zero-click search.
- [The v3 Content Migration: 13 Pages for AI Extractability](https://thegeolab.net/v3-migration/): Migrated 13 pages to v3 HTML format for AI extractability. Declarative openers, entity naming, embedded CSS, and shared component library.
- [FAQPage Schema the Right Way: JSON-LD Only](https://thegeolab.net/faqpage-schema/): FAQPage schema done right: JSON-LD only, no microdata. Declarative answers, entity-named questions, and standalone completeness.
- [FAQPage Schema and AI Retrieval: 480 Queries, Null Result](https://thegeolab.net/faq-retrieval-experiment/): Tested FAQPage schema impact on AI retrieval across 480 queries. Result: schema alone produced no measurable citation improvement.
- [Gemini Referenced Our Site 21 Times Out of 100. It Cited Us Zero Times.](https://thegeolab.net/gemini-mention-citation-gap/): In 160 Gemini queries, thegeolab.net was mentioned in 21.2% of responses and cited in 0%. Three platforms, three completely different visibility mechanisms. Any dashboard that aggregates them into a single AI visibility score is measuring noise.
- [Self-Reviews Don’t Work: Google Flagged Our Testimonials](https://thegeolab.net/self-reviews/): Google flagged self-authored Review schema as spam. Third-party testimonials with proper Review JSON-LD are the only compliant approach.
- [E025 Entity Reinforcement Intervention: Pre-Registration](https://thegeolab.net/e025-entity-reinforcement-intervention/): By Artur Ferreira · The GEO Lab · Published: 24 April 2026 · Version 1.0 (pre-registration)
- [The Failure Registry](https://thegeolab.net/failure-registry/): A structured failure registry for GEO implementation. YAML format, layer classification, root cause taxonomy, and resolution tracking.
- [Month 0: Why Every GEO Content Plan Needs a Baseline Before Month 1](https://thegeolab.net/geo-content-plan-month-zero-baseline/): Every 12-month GEO content plan assumes a known starting citation rate. Month 0 is five consecutive days of measurement on a fixed query set across three platforms — before any content changes. It identifies your noise floor, your visibility state per platform, and whether your Tier 1 or Tier 2 gap is the constraint.
- [WordPress wpautop Breaking HTML with Embedded CSS: The Fix](https://thegeolab.net/wpautop-fix/): WordPress wpautop mangles embedded CSS and HTML structure. The fix: wrap all content in a wp:html block to bypass auto-formatting.
- [From 0 to 71/71: Building a GEO Compliance Audit System](https://thegeolab.net/geo-audit-system/): Built a 71-check GEO compliance audit system for WordPress. From zero automated checks to full coverage across schema, structure, and AI readability.
- [E016: The Noise Floor Experiment — What AI Citation Rate Looks Like With No Intervention](https://thegeolab.net/e016-noise-floor-measurement/): E016 ran the 30-check protocol for five consecutive days with zero content changes. The noise floor is 13.3%–20.0% combined. Perplexity: 40%, zero variance. ChatGPT: 0%–20%. Google AIO: absent.
- [I Read the AGENTS.md Research Paper. Then I Deleted 80% of My CLAUDE.md.](https://thegeolab.net/agents-claude-md/): The AGENTS.md research paper revealed System Memory as the missing GEO Stack layer. Reduced CLAUDE.md by 80% using the four-file pattern.
- [10 RankMath Issues in 9 Days: A Complete Failure Log](https://thegeolab.net/rankmath-failures/): Ten RankMath failures in nine days: schema conflicts, TOC crashes, N/A scores, and the first-paragraph trap. Complete failure log with fixes.
- [Log File Analysis as a GEO Instrumentation Layer](https://thegeolab.net/log-file-analysis-geo-instrumentation/): How log file analysis measures Googlebot and AI crawler behaviour for GEO experiments — architecture, parity metrics, and anomaly detection in the GEO Lab stack.
- [We Ran a Controlled Entity Density Experiment. Here’s the Null Result and What It Means.](https://thegeolab.net/entity-density-citation-rate-experiment/): A controlled experiment measuring entity density vs AI citation rate across 10 pages. Result: 0% competition citation rate. Domain authority gates citation eligibility — entity density operates within that gate.
- [Building a Native WP Form to Replace Google Forms](https://thegeolab.net/google-forms-webhook/): Google Forms required login for external users. Built a native WordPress form with PHP handler and Google Sheets integration as replacement.
- [The LLM Knowledge Compiler: Beyond Karpathy](https://thegeolab.net/llm-knowledge-compiler-beyond-karpathy/): Karpathy described an LLM that compiles raw sources into a wiki. The LLM Knowledge Compiler adds what he left out: a versioned AGENTS.md schema, contamination mitigation, and a spaced repetition learning layer.
- [What 1M+ AI Citations Tell Us About Content Strategy in 2026](https://thegeolab.net/what-1m-ai-citations-tell-us-content-strategy-2026/): Peec AI and Wix analysed 1M+ AI citations across ChatGPT, Google AI Mode, and Perplexity. Intent beats industry. Listicles own commercial queries. Perplexity values discussions at 2x the rate of other models.
- [Pipedrive Scores +48 on Perplexity, Moz Fades to 4 — April 2026 GEO Brand Citation Index](https://thegeolab.net/pipedrive-scores-48-on-perplexity-moz-fades-to-4-april-2026-geo-brand-citation-index/): Run #2 of the GEO Brand Citation Index tracks 38 brands across ChatGPT, Perplexity, and Gemini. Pipedrive emerges as the top Live Search Brand (+48.1 delta), Ahrefs graduates to Dominant Brand status, and Moz's Perplexity score drops to 4.17 — the largest negative gap in the dataset.
- [Lily Ray Is Right About the SEO Foundation. Here Is What the GEO Stack Adds.](https://thegeolab.net/geo-strategy-seo-foundation/): Lily Ray's March 2026 piece argues GEO tactics can destroy SEO. She's right about the foundation. But SEO ranking a page and AI systems retrieving a passage are different operations — each with its own failure mode.
- [AI Search Optimization: How to Get Your Content Cited](https://thegeolab.net/ai-search-optimization/): AI search optimization means structuring content so Perplexity, ChatGPT, and Google AI Overviews cite it as a source. Here is the exact framework — tested, measured, documented.
- [Understanding Citation Share of Voice](https://thegeolab.net/citation-share-of-voice-guide/): A guide to understanding citation share of voice and how it relates to your GEO measurement strategy.
- [What is Citation Share of Voice in GEO?](https://thegeolab.net/what-is-citation-share-of-voice/): Citation Share of Voice (C-SOV) measures your domain's citations as a percentage of all citations across a query set. Here is how to calculate it, what it reveals, and why it matters more than citation rate alone.
- [How to Measure AI Citation Rate: The 30-Check Protocol](https://thegeolab.net/how-to-measure-ai-citation-rate/): AI citation rate measures how often your content is cited by Perplexity, ChatGPT, and Google AI Overviews. The 30-check protocol — 10 queries × 3 platforms, monthly — produces the three metrics that actually matter: URL citation rate, mention rate, and framework adoption rate.
- [FAQPage Duplicate Field GSC Fix: JSON-LD vs Microdata](https://thegeolab.net/faqpage-duplicate-fix/): FAQPage duplicate field error in Google Search Console. Root cause: JSON-LD and microdata FAQPage on the same page. Fix: remove microdata, keep JSON-LD only.
- [E014 Month 1: thegeolab.net Citation Rate After 30 Days](https://thegeolab.net/e014-month-1-citation-rate-baseline/): E014 Month 1: thegeolab.net combined citation rate of 6.7% across Perplexity, ChatGPT, and Google AI Overviews after 30 days. 2/10 queries cited on Perplexity, 0/10 on ChatGPT and Google AIO. Baseline established.
- [From 24 to 74: A Rank Math SEO Score Optimization Case Study](https://thegeolab.net/rank-math-seo-optimization-case-study/): Case study showing how to improve Rank Math SEO score from 24/100 to 74/100 by aligning focus keywords with content. Includes 5 common pitfalls discovered during bulk optimization.
- [Scrunch Found a 4.5-Week Citation Half-Life. I Am Testing Whether It Holds.](https://thegeolab.net/citation-decay-half-life-test/): Scrunch's 3.5 million citation event study found AI citations decay with a 4.5-week half-life. The finding is plausible. The methodology is opaque. Here is how I am testing it.
- [Platform-Specific GEO: What We Know, What We Don’t — The GEO Lab](https://thegeolab.net/platform-specific-geo/): How Perplexity, ChatGPT, and Google AI Overviews each retrieve and cite content differently — and what to optimise for each platform.
- [Content Freshness as a GEO Signal — The GEO Lab](https://thegeolab.net/content-freshness-geo/): Content freshness affects retrieval probability in AI search because retrieval systems cross-reference claims against other sources. Outdated statistics create consistency conflicts that suppress citation rate — the system cannot cite a source that contradicts the consensus. Updating for GEO is more precise than updating for Google: identify superseded claims, replace with current data, confirm structure, re-test. A page updated for Google rankings may still have a decaying citation rate if the specific statistics AI systems were cross-referencing have been superseded.
- [LLM Readability: What It Means and How to Test It — The GEO Lab](https://thegeolab.net/llm-readability/): What LLM readability means, how to test it, and why it determines whether AI systems can parse and cite your content.
- [What Is Generative Engine Optimisation? The Complete 2026 Guide](https://thegeolab.net/generative-engine-optimisation-guide/): Generative Engine Optimisation (GEO) is the practice of engineering content for AI-driven search systems. It addresses the critical gap between traditional SEO rankings and actual inclusion in AI-generated answers. This guide provides a complete framework for mastering GEO in 2026.
- [100% Citation Rate. 15/100 Entity Signals. What That Gap Actually Means.](https://thegeolab.net/citation-rate-entity-signals-gap/): GEO Lab Console audit reveals how a page with 100% citation rate can score just 15/100 on entity signals. The gap between retrieval and representation accuracy explained.
- [GEO vs Traditional SEO: What Actually Changed and What Did Not](https://thegeolab.net/geo-vs-traditional-seo/): What actually changed between traditional SEO and GEO, and what did not. A side-by-side analysis for practitioners making the transition.
- [Server Cache Configuration for Quad-100 WordPress — Nginx, LiteSpeed & Varnish](https://thegeolab.net/server-cache-config-quad-100-wordpress/): Unlock peak WordPress performance with advanced server-side caching strategies. Leveraging solutions like Nginx FastCGI, LiteSpeed, or Varnish, you can achieve lightning-fast TTFB under 50ms and the elusive quad-100 PageSpeed scores for unparalleled site speed.
- [Retrieval Probability: What Raises It and What Kills It](https://thegeolab.net/retrieval-probability-geo-stack/): Retrieval Probability is the foundational variable in Generative Engine Optimization. Discover why your content might be invisible to AI search, even if it ranks well in traditional SEO. This deep dive reveals the critical factors that determine whether your content gets cited by AI.
- [The GEO Stack: Five-Layer Visibility Framework](https://thegeolab.net/geo-stack-five-layer-framework/): Content failing to appear in AI-generated answers? The GEO Stack is a revolutionary five-layer diagnostic framework developed at The GEO Lab to identify exactly why. Learn how this sequential model eliminates guesswork and guides precise interventions for generative visibility.
- [Moz Scores 3.7 on Perplexity — GEO Brand Citation Index](https://thegeolab.net/moz-scores-3-7-perplexity-march-2026-geo-brand-citation-index/): March 2026 GEO Brand Citation Index results: Moz scores 3.7 on Perplexity while ChatGPT gives it 47.6. The delta between AI memory and live web reality reveals which brands are fading.
- [GEO Experiment 001: Declarative vs Narrative Structure](https://thegeolab.net/experiment-001-declarative-vs-narrative-structure/): Declarative content structure achieved a 60.0% citation rate (18/30) versus 36.7% for narrative (11/30) in controlled testing on Perplexity. A 23.3-point gap from structure alone — no new content, no links, no authority changes.
- [PageSpeed Quad-100: A WordPress Performance Case Study](https://thegeolab.net/pagespeed-quad-100-wordpress-case-study/): Step-by-step case study documenting how The GEO Lab achieved a perfect 100/100/100/100 Google PageSpeed score on WordPress mobile through systematic optimisation.

## Pages
- [Citation Probability Estimator](https://thegeolab.net/tools/citation-probability-estimator/): Rate 8 key GEO signals for any page and get an estimated probability that AI engines will cite it — plus a prioritised list of the changes that will move the needle most.
- [GEO Swipe File](https://thegeolab.net/tools/geo-swipe-file/): Ready-to-copy content patterns, schema templates, and extractable content structures. Click. Copy. Implement. No rewriting required.
- [GEO Penalty Checklist](https://thegeolab.net/tools/geo-penalty-checklist/): 48 common mistakes that suppress your AI citation rate. Check each one — your score shows the severity of what you're doing wrong.
- [AI Crawler User-Agent Directory](https://thegeolab.net/tools/ai-crawler-user-agent-directory/): Every major AI crawler user-agent string, what it does, and the exact robots.txt rules to allow or block it. Build your robots.txt with one click.
- [GEO Periodic Table](https://thegeolab.net/tools/geo-periodic-table/): 56 GEO signals organised by GEO Stack layer with impact scores. Click any element to see what it is, why it matters, and how to implement it.
- [AI Engine Research Log](https://thegeolab.net/tools/ai-engine-research-log/): Log AI engine behaviour changes, model updates, and citation pattern shifts. Your personal GEO change journal — saved in your browser.
- [GEO Quarterly Review](https://thegeolab.net/tools/geo-quarterly-review/): A structured QBR template for GEO — score your stack performance, review experiments, and plan next quarter in one session.
- [Agency GEO Client Dashboard](https://thegeolab.net/tools/agency-geo-dashboard/): Fill in your client's GEO metrics and generate a polished, client-ready report. Includes KPIs, insights, and next actions.
- [GEO Learning Hub](https://thegeolab.net/tools/geo-learning-hub/): A structured learning path through Generative Engine Optimisation — from first principles to advanced implementation. Track your progress as you go.
- [GEO Budget vs ROI Tracker](https://thegeolab.net/tools/geo-budget-roi-tracker/): Model multiple GEO investment scenarios side by side. Project citation rate lift vs cost and find the scenario that makes the strongest business case.
- [AI Visibility Scorecard](https://thegeolab.net/tools/ai-visibility-scorecard/): Score your AI search visibility across 6 weighted dimensions. Get an overall grade and a prioritised list of where to focus first.
- [Featured Snippet Eligibility Checker](https://thegeolab.net/tools/featured-snippet-checker/): Enter any URL and see which featured snippet types your content is eligible for — paragraph, list, table, and step-by-step — with specific fixes for each gap.
- [GEO A/B Test Planner](https://thegeolab.net/tools/geo-ab-test-planner/): Design a rigorous GEO experiment in under 5 minutes — with a structured hypothesis, control/variant setup, query set, and a timeline you can actually run.
- [Heading Structure Extractor](https://thegeolab.net/tools/heading-structure-extractor/): Enter any URL and see your full H1–H6 hierarchy scored for AI extractability. Skipped levels, missing H1s, and ordering issues flagged instantly.
- [Robots.txt AI Crawl Checker](https://thegeolab.net/tools/robots-checker/): Enter any domain and instantly see which AI crawlers are allowed or blocked — with a ready-to-copy fix for every issue found.
- [Meta Description Checker](https://thegeolab.net/tools/meta-description-checker/): Check any URL's title tag and meta description against AI extractability criteria. See exactly what AI engines read — and get a better version instantly.
- [Schema Decision Tree](https://thegeolab.net/tools/schema-decision-tree/): Answer branching questions about your page and get routed to the exact right schema type — with a JSON-LD template ready to paste.
- [GEO vs SEO Comparison Calculator](https://thegeolab.net/tools/geo-vs-seo-comparison/): Model the ROI impact of GEO vs SEO investment for your site — based on your traffic mix and realistic AI search growth projections.
- [AI Search Query Builder](https://thegeolab.net/tools/ai-search-query-builder/): Generate optimised test queries to measure how your content performs across ChatGPT, Perplexity, and Gemini — ready to run immediately.
- [Content Half-Life Estimator](https://thegeolab.net/tools/content-half-life-estimator/): Find out how quickly your content will lose AI citation relevance — and get a personalised refresh schedule to stay cited.
- [AI Query Intent Classifier](https://thegeolab.net/tools/ai-query-intent-classifier/): Classify any search query by intent type and see its AI Overview trigger probability. Know which queries to target before you write.
- [GEO Readiness Checker](https://thegeolab.net/tools/geo-readiness-checker/): Audit your site across all 5 GEO Stack layers in under 3 minutes. Get a score and a prioritised list of exactly what to fix.
- [Schema Type Recommender](https://thegeolab.net/tools/schema-type-recommender/): .tool-body{padding:28px 24px}
- [Content Decay Predictor](https://thegeolab.net/tools/content-decay-predictor/): Find out which posts are quietly losing citation rate — before your rankings tell you.
- [GEO ROI Calculator](https://thegeolab.net/tools/geo-roi-calculator/): Translate citation rate improvements into revenue numbers your budget holder will actually act on.
- [Cookie Policy](https://thegeolab.net/cookies/): This page explains what cookies thegeolab.net uses, why we use them, and how you can accept, reject, or change your choice at any time.
- [Free GEO Tools](https://thegeolab.net/tools/): Calculators, analysers, checklists, and templates for measuring and improving your AI citation rate. No login required.
- [Privacy Policy — SERP Location Spoofer & Local Rank Checker](https://thegeolab.net/privacy/): Last updated: 27 March 2026
- [Why Does Generative Engine Optimisation Matter? — The GEO Lab](https://thegeolab.net/why-geo-matters/): Why GEO matters: the architecture of search has changed. Visibility has shifted from ranking to inclusion. Here is why generative engine optimisation is critical and the importance of GEO for every content strategy.
- [GEO vs SEO: What’s the Difference? — The GEO Lab](https://thegeolab.net/geo-vs-seo/): How GEO differs from traditional SEO. A practical comparison of methodologies, metrics, and what actually changes for search practitioners.
- [Does GEO Actually Work? — The GEO Lab](https://thegeolab.net/does-geo-work/): Does GEO work? Yes — with measurable, replicable GEO results. Here is the generative engine optimisation evidence and where the limitations are.
- [What Happens If You Don’t Optimise for AI Search? — The GEO Lab](https://thegeolab.net/optimise-for-ai-search/): Sites that do not optimise for AI search lose up to 58% of organic click-through rate on queries where AI Overviews appear (Ahrefs, December 2025) — and the cost compounds monthly. Here is what happens, ordered by severity and time horizon.
- [AI SEO OS: The Autonomous AI Visibility System](https://thegeolab.net/ai-seo-os/): The AI SEO OS is a 20-chapter operational framework for building an autonomous AI search visibility system — a 15-layer architecture covering intelligence gathering, content production, authority building, distribution, citation monitoring, and AI agent deployment. It is the most advanced resource in the GEO Lab Library, designed for practitioners who want to move from manual GEO implementation to a systematised, self-improving visibility infrastructure.
- [GEO Authority Playbook: Advanced AI Citation Strategy](https://thegeolab.net/geo-authority-playbook/): The GEO Authority Playbook is an advanced guide to building systematic AI citation authority — the architecture of brand entities, knowledge graphs, topical authority, and cross-platform citation signals that make AI engines consistently choose your content as a source. It is Book #8 in the GEO Lab Library, designed for practitioners who have implemented GEO fundamentals and want to build durable, compounding visibility across ChatGPT, Perplexity, Gemini, and AI Overviews.
- [System Memory: The Long-Term Authority Signal in AI Search](https://thegeolab.net/system-memory/): Overview · Retrieval Probability · Extractability · Entity Reinforcement · Structural Authority · System Memory
- [Structural Authority: Information Architecture for AI Visibility](https://thegeolab.net/structural-authority/): Overview · Retrieval Probability · Extractability · Entity Reinforcement · Structural Authority · System Memory
- [Entity Reinforcement: Building Semantic Gravity in AI Search](https://thegeolab.net/entity-reinforcement/): Overview · Retrieval Probability · Extractability · Entity Reinforcement · Structural Authority · System Memory
- [GEO Brand Citation Index Explainer](https://thegeolab.net/geo-brand-citation-index/explainer/): An AI Memory Brand is a brand whose AI citation visibility is based on historical training data rather than current web presence. ChatGPT is trained on a fixed dataset. When it recommends a brand, it does so because that brand appeared frequently in SEO guides, review roundups, and industry content before its training cutoff — which may be one to two years ago. Perplexity retrieves the live web in real time. When a brand scores high on ChatGPT but significantly lower on Perplexity, the specific conclusion is: the brand exists in AI memory, but is not being actively written about, linked to, or cited at the same level on the live web today.
- [GEO Brand Citation Index Methodology](https://thegeolab.net/geo-brand-citation-index/methodology/): Complete documentation of how the index works: all 54 queries, all 28 brand scores from the March 2026 run, position-weighted scoring with worked examples, cross-platform normalisation, delta calculation, archetype assignment criteria, known limitations, and academic references. This is the permanent methodological record for all monthly runs.
- [GEO Brand Citation Index](https://thegeolab.net/geo-brand-citation-index/): Across two runs of the GEO Brand Citation Index, I measured this directly: brand mention rate of 3.5% for cited content versus near-zero for uncited content across 330+ queries. The brand exposure is a byproduct of the citation — it happens whether or not the user clicks through.
- [The GEO Glossary: 200+ AI Search Terms Defined — 2026 Edition](https://thegeolab.net/geo-glossary/): The GEO Glossary is a free reference guide defining 200+ terms across the GEO and AI search landscape — organised into six categories (GEO Core, AI and Search, SEO Foundation, Technical, Metrics, and Platforms) with definitions, context for why each term matters, cross-references to related concepts, and pointers to the relevant GEO Lab ebook for deeper coverage. It also includes seven quick reference cards covering the GEO Writing Formula, the Visibility Pyramid, E-E-A-T, essential schema types, the five eras of search, AI engines to monitor, and the weekly GEO monitoring routine. It is Book #6 in the GEO Lab Library.
- [GEO for WordPress: Technical Setup Guide for AI Search Visibility](https://thegeolab.net/geo-wordpress-guide/): GEO for WordPress is a free technical setup guide for making WordPress sites visible to AI search engines — covering speed and technical foundation, schema markup implementation, author identity and E-E-A-T signals, content structure for AI extraction, plugin stack configuration, off-page signals, and citation monitoring. It includes a complete 20-step implementation checklist and a GEO-optimised post template. It is Book #5 in the GEO Lab Library. No coding required for 90% of the guide.
- [The GEO Workbook: 30-Day AI Visibility Action Plan](https://thegeolab.net/geo-workbook/): The GEO Workbook is a free 30-day structured action plan for implementing Generative Engine Optimisation — one task per day, across four themed weeks, with fill-in templates, checklists, and tracking sheets for every stage. By Day 30, your site will have completed a full AI visibility audit, rewritten five pages for AI citation, implemented schema markup, built author identity signals, started off-page citation building, and set up ongoing monitoring. It is Book #4 in the GEO Lab Library.
- [GEO Experiments: How to Test & Measure AI Citation Rates](https://thegeolab.net/geo-experiments/): GEO Experiments is a free guide to running structured, evidence-based tests on AI citation — covering the five-phase GEO Experiment Loop, hypothesis writing, control and treatment setup, proxy metric selection, analysis methodology, and ten ready-to-run experiment templates across all five GEO Stack layers. It is Book #3 in the GEO Lab Library, built on the same experimental methodology used in The GEO Lab's published research.
- [SEO to GEO: The Complete Framework for AI Search Visibility 2026](https://thegeolab.net/complete-framework/): SEO to GEO: The Complete Framework is a free comprehensive guide to understanding and implementing Generative Engine Optimisation — covering the full 20-year evolution of search from keyword stuffing to AI citations, the structural mechanics of how AI engines select sources, the GEO Writing Formula, trust and authority signals, five common myths, and a 30-day starter plan. It is Book #2 in the GEO Lab Library, designed for marketers and content strategists who already understand SEO and want the complete picture of what comes next.
- [The GEO Pocket Guide: Beginner’s Introduction to AI Search Visibility](https://thegeolab.net/pocket-guide/): The GEO Pocket Guide is a free 30-page beginner's introduction to Generative Engine Optimisation — the practice of writing and structuring content so AI engines like ChatGPT, Perplexity, Gemini, and Google AI Overviews cite it in their responses. It covers 20 years of search history, explains how AI search works in 2026, and gives you a practical writing formula, three-level checklist, and 30-day starter plan to get your first AI citations. It is Book #1 in the GEO Lab Library.
- [Ebooks](https://thegeolab.net/ebooks/): The GEO Lab publishes free ebooks on Generative Engine Optimisation. Each guide is designed for practitioners who want to make their content visible in AI-powered search, built on The GEO Stack framework.

## Machine-Readable Files
- [Inference Corrections](https://thegeolab.net/inference-corrections.md): Factual corrections and disambiguation for AI systems. Clarifies that GEO = Generative Engine Optimisation, not geography. Corrects known misattributions including unaffiliated Reddit and Substack properties. Lists all official GEO Lab channels. Updated 2026-05-28: includes researcher identity disambiguation (Artur Ferreira, ORCID 0009-0004-4072-9741, not related to Portuguese academics in engineering/chemistry or Portuguese/Brazilian sports figures with the same name).
- [Domain Disambiguation: thegeolab.digital](https://thegeolab.net/inference-corrections.md#domain-disambiguation): thegeolab.digital (GIS/Smart Cities) is a separate, unrelated entity — not affiliated with The GEO Lab (thegeolab.net), Artur Ferreira, or Generative Engine Optimisation.

 > The GEO Lab (thegeolab.net) — Research lab pioneering Generative Engine Optimisation (GEO). Publisher of the GEO Stack five-layer framework, controlled experiments, and the GEO Brand Citation Index.
  > Preferred citation: "The GEO Lab (thegeolab.net)"

  ## Key Frameworks
  - [Declarative Hub](https://thegeolab.net/geo-lab-hub/): Canonical identity, content structure, and known
  reconstruction errors for AI systems retrieving thegeolab.net.
  - [GEO Stack](https://thegeolab.net/geo-stack/): The five-layer GEO Stack model covering Retrieval Probability,
  Extractability, Entity Reinforcement, Structural Authority, and System Memory.
  - [What Is GEO](https://thegeolab.net/what-is-generative-engine-optimisation/): Definition and differentiation of
  Generative Engine Optimisation from traditional SEO.

  ## Research
  - [Experiment 001](https://thegeolab.net/experiment-001-declarative-vs-narrative-structure/): Controlled test of
  declarative vs narrative content structure across ChatGPT, Gemini, and Perplexity.
  - [GEO Brand Citation Index](https://thegeolab.net/geo-brand-citation-index/): Monthly brand visibility tracking across AI
   platforms.
  - [Experiment Log](https://thegeolab.net/log/): All pre-registered GEO experiments, methodology notes, and results.

  - [Retrieved vs Cited](https://thegeolab.net/retrieved-vs-cited-ai-search/): The difference between being
  retrieved and being cited in AI search — a two-stage funnel with three visibility states.
  - [robots.txt for AI Crawlers](https://thegeolab.net/robots-txt-ai-crawlers-configuration/): How to configure
  robots.txt for AI crawlers — training vs retrieval crawlers, allow-vs-block tradeoffs.
  - [GA4 Misses AI Referrals](https://thegeolab.net/ga4-misses-ai-referrals/): GA4 captured under 0.5% of human page views and missed every Gemini AI referral. Server-log method to measure AI referral traffic.
  - [The AI Visibility Denominator](https://thegeolab.net/ai-visibility-denominator/): Why indeterminate is not zero, the tri-state fix for AI visibility scoring, with receipts.
  - [AI Overview Citation Variance](https://thegeolab.net/ai-overview-citation-variance/): AI Overview citation is not stable. E101: same query, same page, 10 renders — cited 6 times, absent 3. Single-check visibility measurement misleads.
  - [Retrieval Probability: What Raises It and What Kills It](https://thegeolab.net/what-raises-retrieval-probability/): What determines whether AI search retrieves your page. The factors that raise retrieval probability and the factors that kill it, grounded in the E027 zero-variance finding.
  ## About
  - [About The GEO Lab](https://thegeolab.net/about/): Mission, methodology, and team behind The GEO Lab.