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Customer testimonial mining and rewrite for credibility
I have raw, messy customer feedback (reviews, support tickets, survey responses) below. Help me find and shape the strongest testimonials without fabricating anything.
Raw feedback:
raw_feedback_text
Do this:
1. Identify the 3-5 strongest candidate quotes, ranked by specificity (a testimonial that names a specific number, before/after, or use case is far more credible than generic praise like 'great product, highly recommend').
2. For each candidate, note whether it can be used verbatim or needs light editing for clarity, and show ONLY grammar/clarity edits, never add claims, numbers, or sentiment the customer didn't express.
3. Flag any quote that sounds strong but is actually too vague to be useful ('this changed everything for us') and explain why it won't perform in actual marketing use even though it sounds positive.
4. Suggest what specific follow-up question I could ask that customer to get a more specific, usable quote, if the raw material is thin.
5. Organize the good ones by which page/use case they're best suited for (homepage social proof vs. a specific feature page vs. a case study).