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Case study / measuring_the_invisible.txt

Attribution when nobody clicks

Problem. AI answers create influence without clicks. The classic analytics stack goes blind exactly where the market is moving.

System. I measure in layers. (1) A 600-prompt share-of-voice system tracks brand mention rate across ChatGPT, Claude, Gemini, Perplexity, and AI Overviews daily — 53% → 87% in eight months. (2) I separated “AI Search” into its own post-purchase survey source, turning anecdote into a trend line tied to signups. (3) A GSC misspelling-divergence method: people who discover you through AI type the brand the way the AI spelled it — the gap between clean and divergent branded queries becomes a proxy for AI-driven discovery.

Why it matters. When the channel hides the click, you measure the echoes. This is the methodology briefed at board level.

Historical mention-rate result: (commercial tooling — since audited and replaced by the in-house platform above). See “The vendor data was synthetic, so I built the real thing” for the replacement platform.

Attribution / three complementary signals

When the click disappears,
the evidence doesn’t.

01 / VISIBILITYShare of voice600-prompt tracking system
02 / SELF-REPORTPost-purchase surveyAI Search as its own source
03 / DISCOVERYQuery divergenceClean vs. misspelled brand queries
Read the signals togetherVisibility, signups, and proxies for AI-driven discovery

Complementary measurements, not a claim that every AI-influenced conversion can be individually identified.

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