Mine Voice-of-Customer Language From Reviews

This prompt mines a pile of customer reviews for the exact language buyers use — their value phrases, the words for their pain before they found you, recurring emotional words, and lines that would work as landing-page copy — returned with frequency counts and example quotes. Reach for it when you have reviews, survey responses, or support transcripts and want your marketing to speak in customers' words instead of your own. Writing copy in the phrases customers already use is one of the most reliable conversion levers, and this turns raw feedback into that raw material.

What you can expect back

Value phrases
- 'done in ten minutes' (11 mentions) — 'The whole week is done in ten minutes.'
- 'I actually stick to it' (8) — 'First plan I've actually stuck to.'
- 'saves my Sundays' (6) — 'It gave me my Sundays back.'

Pain points before finding us
- 'wasting the whole weekend' (9) — 'I used to waste my whole weekend planning.'
- 'ordering takeout again' (7) — 'By Wednesday I was ordering takeout again.'
- 'decision fatigue' (5) — 'I was so sick of deciding what to cook.'

Repeated emotional words
- 'overwhelmed' (10), 'relief' (8), 'finally' (12), 'guilty' (4)

Landing-page-ready lines
- 'Your whole week, done in ten minutes.'
- 'Stop ordering takeout by Wednesday.'
- 'Get your Sundays back.'

Illustrative example — your results will vary by tool and inputs.

Get sharper results

• 01Paste a large enough sample — frequency counts only mean something across dozens of reviews, not five, so batch them before running.
• 02Mix sources if you can (app reviews, support tickets, sales-call notes); the language people use when frustrated differs from when they're praising you.
• 03Ask it to keep customers' exact wording, including imperfect grammar — the rough phrasing is often the most authentic and convertible.
• 04Have it separate language by customer segment if your reviews mention roles or use cases, so you can target each with its own copy.
• 05Treat the 'landing-page-ready lines' as candidates to test, not finished headlines — the value is that they're grounded in real demand, but they still need A/B validation.

Adapt it for your case