Mine voice-of-customer evidence
Autonomously gathers and clusters real learner language from past client notes, community threads, survey exports, and interview transcripts, returning recurring phrasings, frustrations, and desired outcomes.
In / outFile paths / links to notes, threads, transcripts, survey exports → Clustered voice-of-customer report: recurring phrasings, top frustrations, desired outcomes
You might say…
“I have three years of client emails and community posts sitting in folders I never have time to read through.”
What it does
Autonomously gathers and clusters real learner language from past client notes, community threads, survey exports, and interview transcripts the educator points it at, returning recurring phrasings, frustrations, and desired outcomes to sharpen the persona. Used when there is a corpus of raw audience evidence too large to read by hand; an agent because it loops over many sources and synthesises iteratively.
Trigger: Use when you have a corpus of raw audience evidence too large to read by hand and need recurring language patterns extracted automatically.
Autonomy: Acts autonomously — runs end-to-end without a human in each loop.
Recognise the problem?
The primitives are the commodity part. The fastest next step is a conversation about composing them into something that works for you.
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