Insights
Frameworks and field notes for teams building visibility across traditional results, direct answers, and generative recommendations.
Search in 2027: what the numbers already tell us
Google is not dying and AI is not a fad. The data from 2025 and 2026 points to something less dramatic and more useful: the click is getting rarer, and the answer is moving closer to the question.
Read analysisAEO in 2027: how to be the answer when nobody clicks
When an AI summary sits above the results, the top-ranked page loses a large share of its clicks. Here is what the studies measured, where they disagree, and how to write pages that still earn the mention.
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GEO in 2027: how AI assistants decide which brands to name
Ranking in Google's top ten used to be most of the job. New data shows AI answers increasingly cite pages from outside it, lean on community sites, and recommend far fewer local businesses than the map pack does.
Read analysisSEO, AEO and GEO: one visibility system, three surfaces
How to connect rankings, direct answers, and generative recommendations without creating three disconnected programs.
Read analysisWhat makes content answer-engine ready?
A practical framework for producing direct, evidence-led answers without flattening expertise into generic summaries.
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How brands become credible sources in generative search
Why entity consistency, original information, and third-party corroboration matter more than chasing AI-specific tricks.
Read analysisThe answer engine checklist we run before publishing any B2B page
A page-by-page checklist we use to decide whether a page can win a direct answer, based on the pages we have shipped and measured.
Read analysisHow to measure whether AI answers actually mention your business
Generative engines rarely send obvious traffic. Here is the measurement approach we use so GEO work can be judged on evidence rather than belief.
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