Distributed authority in AEO: why outside sources matter
Learn why answer engines often trust external sources before a brand's own site, and how to build distributed authority without fake mentions or spam.
Blog
Field notes on AI visibility.
Research, methods and practical observations about how companies become easier for AI systems to understand, cite and recommend.
Brand mention vs source citation in AEO
Learn why an AI answer can mention a brand without citing its website, and how to measure the gap between awareness, evidence and answer-engine trust.
AI opt-out, crawler block or CDN default: which control affects AEO?
A practical guide to separating Search Console opt-outs, robots.txt crawler rules and platform AI controls so answer engines can still find and cite the right pages.
Why ChatGPT citations change between checks
Hidden retrieval pipelines help explain why a single ChatGPT citation check is not enough, and how AEO teams should measure visibility with repeated samples.
Factual authority vs domain authority in AEO
Learn why answer engines cite sources that prove a specific claim, not only the biggest domain, and how to build factual authority for AEO.
Entity consistency audit for AEO: a practical checklist
Audit the facts answer engines use to identify, compare and cite your brand across your site, schema and third-party sources.
Why no honest AEO agency guarantees an AI citation
Learn why guaranteed ChatGPT, Gemini or AI Overview placements are a red flag, and how to evaluate AEO work with evidence instead.
Why top 10 rankings do not guarantee AI Overview citations
Learn why ranking on page one still matters for Google AI Overviews, but no longer works as a reliable proxy for citation visibility.
Citation is not recommendation: the AEO metric that decides whether AI visibility sells
Learn why AI citations, brand mentions and recommendations must be measured separately, and how to turn answer-engine visibility into commercial evidence.
AEO source mapping: which domains AI engines need to see before they cite you
Learn how to map the source categories, third-party domains and evidence gaps that influence whether answer engines cite, mention or recommend a brand.
Per-engine citation volatility: why one model update does not move all answer engines
Learn why citation shifts in ChatGPT, Gemini, Perplexity, Claude and Google AI Mode must be measured per engine, not as one blended AEO score.
Query fan-out for AEO: how to cover subqueries without thin pages
A practical guide to mapping answer-engine subqueries, strengthening citable pages and avoiding duplicate or superficial content.
How to set a citation baseline before a model update
A practical AEO workflow for freezing prompts, competitors, engines and citation metrics before an answer engine changes its model.
Why thin content fails in AI answers
A practical AEO guide to turning thin pages into retrieval-ready, source-backed content that answer engines can understand, verify and cite.
AI visibility tools: when to measure and when to execute
A practical AEO guide to evaluating AI visibility platforms as they move from monitoring dashboards into content workflows and execution.
How to measure competitor share of voice in AI answers
A practical AEO framework for measuring how often answer engines mention, cite and recommend your brand versus competitors.
How to create citable evidence pages for answer engines
A practical guide to turning claims, data and brand proof into pages that ChatGPT, Gemini, Perplexity, Copilot and AI Overviews can understand, verify and cite.
Legitimate AEO or spam: where the line is in AI answer optimization
A practical guide to separating legitimate AEO from AI answer manipulation, paid citations, fake recommendations and spam tactics.
Why AI engines cite different sources for the same question
A practical AEO guide to engine-level citation divergence: why ChatGPT, Gemini, Perplexity, Claude and Google AI Mode use different sources, and how to measure it.
Why ChatGPT citations change after model updates
A practical AEO guide to diagnosing ChatGPT citation changes, separating platform volatility from your own work and responding without chasing noise.
llms.txt for AEO: what it is and how to use it
A practical guide to creating a useful llms.txt file, what to avoid, and how it fits with sitemaps, robots.txt, structured data and AEO measurement.
Structured data for AI answers: what matters for AEO
A practical guide to the schema.org markup that helps answer engines understand entities, definitions, evidence and datasets without chasing schema hacks.
How to build a prompt portfolio for AI visibility
A practical AEO framework for choosing, grouping and measuring prompts so AI visibility reports show citations, mentions, recommendations and competitors clearly.
AI crawlers and AEO: what to allow, block and monitor
A practical guide to AI crawler access for AEO: separate training bots from search bots, avoid accidental blocks and verify whether access becomes citations.
AI referral traffic and dark AI traffic: how to measure what GA4 misses
A practical AEO guide to measuring visible AI referrals, dark AI traffic, citations and conversions without confusing exposure with real business impact.
ChatGPT's first 'core update': what GPT-5.5 changed in citations
When ChatGPT made GPT-5.5 its default in May 2026, about 47% of its citations shifted in 48 hours. What the SISTRIX data shows, and what to do about it.
AEO in 2026: how to win the first citation with relevance, price signals, freshness, and source structure
What the newest 2026 research says about winning the first citation in AI answers, and how to turn those signals into practical AEO and SEO gains.
AEO in 2026: how to win useful citations with original sources, grounding, and real citation absorption
A practical 2026 framework for turning service pages and original evidence into AI-search sources that improve both AEO visibility and SEO performance.
AEO and SEO in 2026: what the newest studies say about traffic, citations, and real growth
A practical 2026 guide to separating platform tailwinds from true AEO gains, protecting SEO, and publishing citation-ready pages that support commercial intent.
Google AI Search reporting in 2026: the AEO playbook for Search Console, AI Mode, and Bing AI Performance
A practical AEO playbook for Google's new AI Search controls and reporting, combining Search Console signals, Bing AI Performance, and citation-absorption research.
AEO metrics in 2026: how to measure citations, grounding queries, and AI visibility
A practical AEO measurement framework built around Bing AI Performance, Google's latest AI Search updates, ChatGPT shopping research, and citation-quality audits.
AEO in 2026: how to become the answer AI engines can cite
A practical playbook for turning your website, brand facts and external proof into evidence that ChatGPT, Gemini, Copilot, Perplexity and AI search systems can use.
A local AEO lab: documenting the Elda-Petrer business center pilot
We are testing AEO on a real local business and documenting the process from technical crawl access to entity signals and external sources.
How AI engines choose sources for business recommendations
AI answers are shaped by the sources that models can retrieve, trust and synthesize. Here is what that means for company visibility.
GEO vs SEO: what actually changes
Traditional SEO still matters, but generative engine optimization changes the unit of visibility from ranking pages to being understood, cited and recommended.
How to measure AI visibility over time
One prompt is not a KPI. AI visibility should be tracked with repeated samples, prompt portfolios, source maps and competitor context.