Research
Methods and findings in GEO
How we measure, why we measure that way, and what we see in the field. Every piece is sourced and re-checkable — the same standard as our reports.
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BASELINE × Tencent: A Deep Technical Partnership for Chinese GEO
We maintain a deep technical partnership with Tencent — Tencent provides GEO expert support, the underlying technology of our engine-behavior benchmark platform involves Tencent's engineering team, and the product and assessment system are built in-house by BASELINE.
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Structure beats rewriting: the stable lever in AI citations
Several independent studies point the same way — giving content structure earns more AI citations than polishing wording, and pure rewriting can even lose ground.
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Why we report raw counts, not percentages
At N=5, "0%" and "20%" differ by a single answer yet read completely differently. Here's why we insist on X/Y raw counts with a Wilson 95% confidence interval.
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How BASELINE Tackles Citation-Source Fragmentation in Chinese AI Engines
A technical white paper — from the four core problems the research exposes (fragmentation, winner-takes-all, source asymmetry, the query-lens trap) to the seven architectural responses the platform builds.
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Beyond Final Visibility: A Three-Stage Diagnostic Framework for Enterprise GEO
A controlled, stage-isolated evaluation that converts retrieval, ranking and generation errors into fact-grounded sitemap revisions — lifting a held-out enterprise GEO score from 58.78 to 69.98.
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Source Decoupling in Chinese AI Search Engines
A cross-industry empirical analysis of 2,307 category queries across six Chinese AI engines — citation sources are highly decoupled across engines, nearly disjoint from traditional search, with large industry differences in brand visibility.
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