The short answer
Share-of-answer is the percentage of buyer-relevant questions for which an AI engine names your brand in its answer. It is measured by defining the question set your buyers actually ask, querying each major engine systematically and repeatedly, and recording whether — and how — your brand appears versus competitors. It is the GEO equivalent of rank tracking, adapted to a world where there are no ranks, only answers.
Why rank tracking fails for AI answers
Classic rank tracking assumes a stable, ordered results list. Generative answers are neither stable nor ordered: the same question can yield differently-phrased answers across sessions, engines synthesize rather than list, and being mentioned is binary in effect — the brands named shape the decision; everyone else is invisible.
Measurement therefore has to change shape: from position on a list to presence in an answer, sampled across engines and across time to average out generation variance.
Building the question set
The question set is the foundation. It should mirror real buyer language across the funnel: category questions (“what is the best X for Y”), comparison questions (“X vs Z”), problem questions (“how do I solve W”), and brand questions (“is X any good”, “X pricing”). A workable starting set is 50–150 questions, weighted toward the queries that precede purchase decisions.
Sources for the set: sales call transcripts, support tickets, People-Also-Ask data, community threads in your category, and — increasingly — asking the engines themselves what people ask about your space.
Running the measurement
Each question is put to each engine — ChatGPT, Perplexity, Gemini, Claude, Google AI Overviews — on a fixed cadence, with multiple samples per question to account for generation variance. For every answer, record three things: mention (were you named), framing (how were you described — leader, alternative, caveat), and citation (which sources the engine pointed to).
The citation record is strategically decisive: it tells you which third-party surfaces the engines trust in your category. Those surfaces become your authority-building roadmap.
Reading the results
Track share-of-answer as a trend, not a snapshot — single readings are noisy by construction. Meaningful movement shows up in four-to-six-week windows for retrieval-based engines, and quarterly for training-based recall.
The most actionable view is competitive: for every question you lose, someone else is the answer. Their citations show you exactly which signals convinced the engine — and which signals you need to build or displace.
Key takeaways
- Share-of-answer = the share of buyer questions for which engines name your brand.
- Measure mention, framing and citation — across engines, sampled over time.
- The engines’ citation patterns reveal which third-party surfaces to invest in.
- Read trends over four-to-six-week windows, not single snapshots.
Questions people ask
How many questions should a share-of-answer program track?
Between 50 and 150 for most brands — enough to cover category, comparison, problem and brand queries across the funnel without diluting focus. Enterprise categories with many product lines may warrant more, segmented by line.
How often should share-of-answer be measured?
Monthly reporting on a weekly or bi-weekly sampling cadence is the practical standard: frequent enough to catch engine behavior shifts, spaced enough that trends dominate noise.
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