AEO and GEO Research by Josh Blyskal

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Josh Blyskal, Head of AI Strategy & Research at Profound, shares data-driven research exploring how AI search engines like ChatGPT, Claude, and Gemini source, evaluate, and cite brands.

Key points

  1. Blyskal's research draws from Profound datasets covering over 10 billion AI citations and 1.5 billion real user prompts.
  2. Traditional SEO metrics accounted for only 4% to 7% of citation variance across 1,311 analyzed pages.
  3. AI engines diverge in source retrieval: across 400 queries, 79.2% of URLs cited by Claude appeared in Brave Search top 10 results.
  4. The SAGE methodology (Setup, Analyze, Generate, Engineer) provides an operational diagnostic framework when brand visibility fluctuates in AI answers.

Why it matters

Brands can no longer rely purely on classic search engine signals to secure visibility inside AI answer engines. Discrepancies in retrieval sources and index dependencies across platforms require distinct measurement and diagnostic strategies.

Analysis

The portal serves as a resource for empirical Generative Engine Optimization (GEO) and Answer Engine Optimization (AEO) findings. Blyskal illustrates that different AI systems evaluate and retrieve information in fundamentally distinct ways, evidenced by Claude's strong alignment with Brave index rankings. His SAGE methodology emphasizes investigating fanout queries and cited sources to diagnose drops in visibility prior to altering content pipelines.

Found in

Summary generated by AI (Gemini 3.8 Flash, 27 September 2026). It may contain errors – the original source is authoritative.

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  • Mattersburg
    Johann Nepomuk Bergerstraße 7/2/14
    7210 Mattersburg, Austria
  • Vienna
    Ungargasse 64-66/3/404
    1030 Wien, Austria

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