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SEO and GEO white papers
In-depth frameworks. 14 pieces and counting, all field-tested with enterprise clients.
ANALYTICS23 MINAI search measurement: the enterprise error bar modelPublished studies put the AI traffic conversion premium anywhere from 4.4x to 23x, and cross-engine citation overlap anywhere from 6.8% to 16%. The spread is not error. It is four incompatible measurement methods being reported as one number. This whitepaper maps each method, its blind spots, and how to construct an AI search measurement number an enterprise can defend.JOSH BERNSTEIN · SEP 1, 2026TECHNICAL SEO25 MINThe 2026 technical SEO audit: mapping your search dependenciesEnterprise search programs rest on assumptions that were never written down: that PDFs stay indexed, that result data stays cheap, that Search Console reports what happened. August 2026 tested all three.JOSH BERNSTEIN · AUG 28, 2026GEO21 MINThe AI answer accuracy framework: detecting and correcting what AI engines get wrongMost GEO programs track whether AI engines mention a brand at all. Almost none track whether what those engines say is true. This paper is a model for closing that gap.JOSH BERNSTEIN · AUG 23, 2026STRATEGY24 MINThe AI visibility ownership modelCitations are produced by four teams and owned by none of them. A governance model for enterprises that want AI visibility on someone's scorecard.JOSH BERNSTEIN · AUG 2026STRATEGY22 MINThe AI answer surface: a three-layer frameworkOne surface, three qualification systems. A framework for measuring and funding generated, cited, and paid visibility separately.TYLER TRUFFI · AUG 2026STRATEGY27 MINThe 2026 AI Citation Economics FrameworkFour independently verified 2026 datasets, on crawler economics, source-trust concentration, AI Overview commercial penetration, and agent-readable incentive design, describe four separate markets behind AI citation. This paper synthesizes them into one framework enterprise teams can use to diagnose where their citation strategy is actually breaking.JOSH BERNSTEIN · AUG 2026STRATEGY24 MINThe B2B Data Enrichment Audit Framework: Five Layers Worth Scoring IndependentlyColdIQ stopped writing about outbound tactics and started reviewing data vendors. LeadMagic started measuring list decay rate by industry. HubSpot tried and failed, in four days, to launch a customer data co-op. Here is the five-layer framework for auditing what is actually happening inside your b2b data enrichment stack.JOSH BERNSTEIN · AUG 1, 2026GEO25 MINGenerative engine optimization is not one practice: a per-engine investment frameworkA three-axis scoring model, retrieval frequency, source concentration, and share stability, for deciding where next quarter's generative engine optimization budget actually belongs.JOSH BERNSTEIN · JUL 28, 2026GEO22 MINThe enterprise AI agent readiness frameworkCitation readiness and agent readiness are different problems. This framework, and the benchmark data behind it, is for the second one.JOSH BERNSTEIN · JUL 24, 2026TECHNICAL SEO22 MINThe enterprise technical SEO maturity modelA five-level maturity model with observable criteria per dimension and benchmark data from 60 enterprise crawls.JOSH BERNSTEIN · JUL 2026STRATEGY18 MINThe enterprise GEO readiness frameworkA four-dimension readiness model, with benchmark data from 60 enterprise sites.JOSH BERNSTEIN · JUN 2026CONTENT20 MINA B2B content-to-pipeline frameworkA model that maps content to the buying committee, attributes it to pipeline, and separates leading from lagging indicators, drawn from 40 B2B programs.JOSH BERNSTEIN · JUN 2026GEO21 MINThe AI citation authority frameworkHow AI engines judge authority, the three buildable signals behind a citation, and the metrics to run the practice.TYLER TRUFFI · JUN 2026STRATEGY19 MINMeasuring SEO and GEO in revenue termsA metric hierarchy from activity to revenue, plus a credible method for valuing organic and AI-cited traffic.TYLER TRUFFI · MAY 2026