Mine customer reviews for your value proposition
Finds the benefits, phrases and objections customers actually use in reviews, so your copy sounds like them.
Here are customer reviews of {{PRODUCT}} (ours or a competitor's):
<reviews>
{{REVIEWS}}
</reviews>
Find:
1. The 5 most mentioned benefits, with the number of reviews for each and 2 exact quotes.
2. Phrases customers use that we should borrow for our copy, word for word.
3. The top 3 complaints or objections, with counts.
4. Words customers never use that marketing teams often do (for example "solution" or "platform").
5. One headline and one subhead written mostly in customers' own words.
Only count what is actually written. Quote exactly.Example output
Top benefit: "saves my Sunday evenings" (11 reviews mention time saved at weekends). Phrase to steal: "finally stopped dreading invoicing". Objection: setup took longer than expected (5 reviews).
How to use
Collect 30 to 200 reviews from app stores, G2, Trustpilot or Amazon, including 3-star ones. For bigger sets, group similar reviews first with an embeddings tool, then run this prompt on each group.
Why it works
Copy built from customer language tends to convert because readers recognise themselves in it. Requiring counts and exact quotes stops the model from summarising reviews into generic marketing speak.