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How engines work2026-10-07

What 2 million AI citations show: prompt-content match matters most, checklists matter less

Once you control for the domain, the usual AEO checklist (FAQ blocks, structured data, Core Web Vitals) reverses or collapses to zero — domain authority and prompt alignment dominate.

Sample: roughly 2 million citations from four commercial engines (including ChatGPT, Claude and Gemini) over six months, joined to 10,000 crawled pages across 19 B2B SaaS workspaces, with 60+ page features tested.

Key numbers · 5References · 1Read →
How engines work2026-10-07

Whose side is the AI shopping assistant on? Change its role and the penalty for sponsored results disappears

The same sponsored listings get treated very differently once the prompt names the platform as the agent's principal — disclosure rules built for humans do not carry over.

Controlled choice experiments varied only the assigned role in the system prompt (naming either a traveller or a booking platform as the agent's principal) and compared how the model handled sponsored listings and reasoned about them.

Key numbers · 4References · 1Read →
How engines work2026-10-07

AI search and Google are not the same: identical content, completely different sources

AI search systematically favours third-party authoritative sources while Google keeps a more balanced mix — lifting an SEO playbook across will not work.

Controlled experiments across verticals, languages and query paraphrases compared AI search (ChatGPT, Perplexity, Gemini, Claude) with Google: AI search shows a systematic, overwhelming bias toward earned media over brand-owned and social content.

Key numbers · 4References · 1Read →
How engines work2026-10-06

Is your domain in the retrieval path? That's the difference between 2.8% and 91.4% mention rate

When neither the brand nor its own domain appears in the retrieval path, mention rates sit at 2.8% (GPT) and 3.8% (Gemini). With an own-domain citation, the same prompt reaches 49–58%.

Sample: 34,960 unbranded prompt-engine observations from 75 projects, covering 2,854 distinct prompts, with repeated GPT and Gemini runs from June to September 2026.

Key numbers · 4References · 1Read →
How engines work2026-10-04

When an AI agent chooses for you: price, ratings and nudges move its decisions too

Agents have no human cognitive limits, yet they are still biased choosers — change how a price is framed, where a rating comes from or how a nudge is worded, and the choice changes.

Framework: ABxLab probes agentic choice in a realistic web shopping environment by systematically varying option attributes (price, ratings) and persuasive cues (psychological nudges).

Key numbers · 4References · 1Read →
How engines work2026-08-10

61.7% of AI citations never name the brand

AI cited your page, but customers never saw your name. That is the norm, not the exception.

Across 3,981 domains, 115 prompts, 14 countries and 4 engines, an industry analysis found 61.7% of citations never name the brand.

Key numbers · 4References · 1Read →
How engines work2026-08-10

Relevance and position decide who gets cited first

252,000 controlled trials: appear early and answer the question, get cited.

A controlled RAG testbed ran 252,000 paired trials across six LLMs, changing one content factor at a time.

Key numbers · 3References · 1Read →