Verbatim Answer Capture
Verbatim answer capture is the practice of storing the full, word-for-word text an AI engine produced for a prompt, rather than only derived scores or mention counts. The raw answer is the evidence layer: it lets teams see exactly what buyers were told, quote it internally, and prove that a change actually occurred.
Scores summarize; verbatims convince. 'Our recommendation rate dropped six points' starts a debate — the actual paragraph where ChatGPT tells a buyer to choose your competitor, on a named prompt, ends it. Raw answers are what turn AI monitoring from an abstract dashboard into something a founder or CMO acts on.
Verbatims are also the audit trail that derived metrics depend on. Claim classifications, sentiment labels, and recommendation calls can all be re-checked against the stored text; without it, every number is unverifiable and every historical comparison is frozen at whatever was extracted at the time.
Perciva's product wedge is built on this principle: the 'receipt' — the verbatim AI answer recommending a rival, and the before/after text when a question flips back — is shown alongside every metric, so the evidence is never more than one click from the number.
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