Your customers ask ChatGPT, Perplexity and Google before they ever reach your site — and what those surfaces say about your brand changes without notice. The dashboards that track this (Profound, Otterly, Peec) are products, not building blocks. If you are building the dashboard — or need the raw observations in your own warehouse — you need the capture layer underneath: real consumer-UI captures, on a schedule, in a stable contract you can diff.
surfaces: ChatGPT · Perplexity · Copilot · Google AI Overview · Google AI Mode
The workflow, field by field →GEO — getting your pages cited inside AI answers — fails without measurement. You cannot optimize for AI Overviews or ChatGPT citations if you cannot observe which sources they currently cite, which sub-queries they run to build the answer, and whether your change moved anything. Rank trackers watch positions on a SERP; GEO needs the evidence layer inside the answer itself.
surfaces: Google AI Overview · ChatGPT · Perplexity · Google AI Mode
The workflow, field by field →When a buyer asks an AI surface "best X for Y", a shortlist comes back — and whoever owns that shortlist owns the category. Share-of-voice teams need the distribution: which brands get named, in what order, with what sentiment, citing whose content, per surface and per market. That is an aggregation over many captures, which means it needs structured, aggregatable observations — not screenshots pasted into decks.
surfaces: ChatGPT · Perplexity · Copilot · Google AI Mode
The workflow, field by field →Citations are the currency of AI search: being cited is the new ranking, and losing a citation is the new dropping off page one. Tracking them requires more than a list of links — you need to know whether a source was actually cited or merely retrieved, how much of the answer it backs, and when that changes. Answer engines do not announce citation changes; only captures reveal them.
surfaces: Perplexity · Google AI Overview · ChatGPT · Claude
The workflow, field by field →RAG pipelines are only as good as what they retrieve, and model snapshots go stale the day they ship. Search-engine result APIs give you links without answers; model APIs give you answers without the live retrieval a consumer surface runs. Grounding on captured AI-surface answers gives you both — current, source-backed answer text your pipeline can quote, verify against, or decompose — in one contract per surface.
surfaces: Perplexity · Google Search · ChatGPT
The workflow, field by field →When an AI surface tells customers something false, defamatory or non-compliant about your product — or recommends you for something regulated — "we saw it last Tuesday" is not evidence. Legal, compliance and brand-safety teams need what any audit needs: a dated, reproducible, tamper-evident record of what was displayed, kept long enough to matter. Most capture tools expire results in 24 hours, which is precisely when an audit trail becomes worthless.
surfaces: ChatGPT · Google AI Overview · Claude · Copilot
The workflow, field by field →