Research library
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In-depth research and strategic frameworks for teams serious about AI product discovery.
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Featured research
The Provenance Report: Why AI Discovery Content Fails Before It Is Written
AI assistants cite brand-owned pages more than any other source. Most brands write those pages from inputs every competitor shares. This report examines where discovery content comes from, and what it costs when the source is public.
The AI Commerce Protocol Guide: agents.md, llms.txt, UCP and the New Plumbing of Discovery
A practical guide to the protocols now wiring stores into AI shopping conversations — what each one actually does, what the platform defaults leave empty, and the one job no protocol does for you.
The Coherence Report: Why AI Recommends Brands That Agree With Themselves
Two controlled studies published in May 2026 frame the real mechanics of AI visibility: schema alone moves nothing, while coherent brand-owned pages capture the majority of consideration-stage citations. This report assembles the evidence.
GEO for Agencies: Building AI Discovery as a Service
A strategic guide for agencies ready to build a GEO practice — what the opportunity looks like, what a credible service involves, and how to position it to clients.
The Future of Product Discovery
How AI assistants are reshaping ecommerce, what discovery history teaches us, and what comes next.
The Shift from Search to AI Discovery
Why Generative Engine Optimisation (GEO) is the next frontier of ecommerce visibility.
Why Product Data Integrity Is the Foundation of AI Discovery
Structure gets you into the game. Integrity keeps you there. A principles paper on what sustained AI recommendation visibility actually requires.
The GEO Playbook for Ecommerce
A practical five-capability framework and implementation guide for AI product discovery.