Review theme miner

About this tool

A few hundred reviews contain the answer to "what should we fix first", but nobody can hold them all in their head, and pasting them into a chatbot produces confident counts that were never counted. This miner works the other way round: your CSV is parsed, deduplicated and star-counted locally, the model only labels aspect-level themes chunk by chunk, and the chunk results are merged with real arithmetic on your device.

Every theme in the report carries verbatim customer quotes, and each quote is verified against your file before it is shown — quotes that cannot be found are dropped and the drop is reported. The result is a theme table (mentions, positive/negative split, evidence) and a priority list ordered by negative mentions, exportable as CSV, Markdown or JSON for the next product meeting.

How to use Review theme miner

1. Add your provider API key in the key panel.
2. Upload a reviews CSV (or paste review text). Columns for text, stars and date are detected automatically.
3. The tool deduplicates, counts star distribution locally, then mines aspect themes in chunks.
4. Read the theme table — every theme carries verbatim quotes that are checked against your file — and export it.

Keep the original files and inspect the exported result before publishing or sharing it.

Frequently asked questions

Are the theme counts real?

Yes. Reviews are deduplicated and counted on your device; the model only labels themes per chunk, and chunk counts are merged locally. Quotes that cannot be found in your file are dropped and counted.

How many reviews can it handle?

CSV files up to about 5 MB. Reviews are processed in chunks, one model call per chunk.

What if my CSV has different column names?

Text, star and date columns are matched by common names (review/comment, stars/rating, date). Rename a column to one of those if detection fails.

Where do my reviews go?

Review text chunks are sent only to the AI provider behind your own key, directly from your browser.

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