geo-measure

name	geo-measure
description	Measure AI-search visibility and citations — pull Google Search Console data, check AI-referral and AI-bot telemetry, and run manual citation spot-checks against a baseline. Use when asked "are we getting cited by AI", "track our GEO/AI-search performance", or to report progress after GEO work.

GEO Measure

Report AI-search visibility. Most AI exposure is zero-click, so no single metric is enough — triangulate the five signals below and compare to a baseline.

The five signals

1. Google generative-AI report (impressions). https://search.google.com/search-console/performance/search-analytics/ai?resource_id=<PROPERTY> — impressions in AI Overviews / AI Mode (no click data). Eligibility is gated by AI-impression volume, so small sites may not see it yet.

2. Classic Search Console deltas. Run the kit's pull script and compare to the recorded baseline:

   node src/measurement/gsc-pull.mjs      # writes dated JSON to data/, prints deltas
   

   Auth: Application Default Credentials with the webmasters.readonly scope (gcloud auth application-default login --scopes=…/auth/webmasters.readonly,…/auth/cloud-platform). Watch the target-intent positions (page-2 → page-1 movement) and the new pillar pages appearing.

3. AI-referral events (analytics). In GA4/PostHog, count sessions/events from AI-assistant referrers (chatgpt.com, perplexity.ai, claude.ai, gemini.google.com, …). The kit's AiReferralTracker emits an ai_referral event; segment by ai_source. Caveat: misses app traffic and noreferrer AI Mode.

4. AI-bot fetch telemetry (server/middleware). Count requests whose UA matches the AI bots (kit's matchAiBot). ChatGPT-User / Perplexity-User hits are the closest proxy for being used in a live answer (vs GPTBot = training). Bing Webmaster Tools' AI Performance report adds real citation counts + grounding queries — check it if the site is verified there.

5. Manual citation spot-checks (ground truth). Monthly, ask each engine the canonical prompts and record C=cited / M=mentioned / –=absent. Use the templates/ai-citation-checks.md runbook. Run in the target locale (location matters — engines localise).

Report format

• Headline: direction of travel vs baseline (impressions, target-intent positions, AI-referral count, bot-fetch count, citation spot-check score).
• What moved and why (tie changes to shipped work).
• Realistic framing: LLM referrals are ~0.1% of organic sessions even for top publishers today — report the trend and the citation presence, not just raw referral volume.
• Next actions, ranked by leverage.

Baseline

If no baseline exists, capture one now (today's date) and note that future runs compare against it. Store baselines in the plan doc or templates/ai-citation-checks.md.