SearchEngineAnswer
Founder & Editor · SEO Champion
SEO Champion | Google News, Google Discover & AI Search Expert | Founder of MustHave.ai, Abdessalam.ai & SearchEngineAnswer.com
Experience: Google News, Google Discover, and AI Search specialist; founder of MustHave.ai, Abdessalam.ai, and SearchEngineAnswer.com.
Research, guides & workflows
Evidence-led articles for publishers, marketers, founders, and SEO practitioners who need a clear decision—not another pile of terminology.
Four recent papers expose separate failure points between retrieval and a trustworthy AI citation. SearchEngineAnswer reproduced PageRecall’s public tier-0 checks and built a claim-level audit ledger.
A 960-answer experiment and a separate B2B panel show why AI citations vary by engine, prompt type and measurement unit. Their percentages should not be pooled.
The limited Discover experiment adds a topic overview between some video cards and related web stories. Its effect on publisher clicks remains unmeasured.
A multi-source RAG attack made incorrect answers cite trusted evidence. Source-deletion tests reveal which document actually drove the claim.
A causal replay found that structured rendering increased citation count, while its effect on whether a source was cited at all remained inconclusive.
A Meituan paper reports a seven-day test of objective-specific generative ad retrieval, with separate relevance, click and commercial policies.
An audit of GPT, Claude and Gemini found that responses to the same Ukraine-war statement bank varied across 112 language and script conditions.
We ran the portable Algebraic Retrieval suite and verified its receipt hash. The full 11,429-document Java fixture remains outside this local test.
A 171,264-conversation study shows that four AI platforms differ at every search stage, from deciding to browse through selecting citations.
How the work is produced
SearchEngineAnswer separates documented facts from interpretation, shows important limits, and keeps meaningful corrections visible.
Current primary documentation is preferred for material facts and product behavior.
Recommendations include their scope, uncertainty, tradeoffs, and known limitations.
Each page aims to add a framework, test, checklist, tool, or example readers can use.
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