Why bother
Your customers already told you what to fix — it's buried in reviews, support tickets and Reddit threads. AI makes it fast to pull out the signal.
The 4-step workflow
- Collect the raw text. Export reviews from your store, app store, or a marketplace into a plain text or CSV file.
- Batch it into an assistant. Paste (or upload) the reviews into Claude or ChatGPT. Both handle long inputs well.
- Ask for structure, not summaries. Use a prompt like: "Group these reviews into recurring themes. For each theme give a count, an example quote, and the sentiment (positive/negative)."
- Drill into the negatives. Follow up with: "List the top 5 complaints and, for each, a concrete product change that would address it."
A prompt that works
You are a product analyst. Here are N customer reviews. Extract: (1) the top themes with counts, (2) overall sentiment split, (3) the 5 most actionable complaints, (4) any feature requests. Quote real lines as evidence.
Take it further
- Use Perplexity to compare what reviewers say about competitors.
- Drop the themes into Notion or ClickUp as a prioritized backlog.
- Turn the positive quotes into marketing copy with Jasper.
Bottom line
You don't need a data team — a good assistant like Claude plus a clear prompt turns raw reviews into a roadmap in an afternoon.
