Your competitors' customers are telling the world what they love and hate, in public, every day. Review mining collects that feedback systematically and turns it into decisions: what to build, what to fix, what to say in your marketing.
Where to collect reviews
- Local businesses: Google Maps, Zomato, Yelp, Tripadvisor, Practo, Justdial.
- Products: Amazon, Flipkart, Etsy, the brand's own site, Trustpilot.
- Software: G2, Capterra, app stores, Reddit threads.
- Services: Google, Clutch, industry directories.
Copy 20-50 recent reviews per competitor, and the same number of your own. Focus on the last six to twelve months; older reviews describe a business that may have changed. Leave out reviewer names; you only need the text.
What to look for
Themes. Group comments by topic: price and value, product quality, service and staff, speed and delivery, ease of use, reliability, range, cleanliness and ambience, location, refunds and billing. Count how often each theme appears and whether it is mostly praised or criticised.
Sentiment. A simple positive/negative share per business shows who customers are happiest with. Small differences are noise; large gaps are signals.
Repeated phrases. Two- and three-word phrases that recur ("waiting time", "cold coffee", "hidden charges") are often more precise than themes.
Switching language. "Moved from", "better than", "unlike X" tells you who customers compare.
The free review sentiment analyzer scores sentiment with negation handling ("not good" counts as negative), groups reviews into ten themes and finds repeated phrases, all in the browser.
Turn findings into opportunities
| What you find | What it means | Possible action |
|---|---|---|
| A complaint repeated across all competitors | An unmet need in the market | Solve it and make it your headline |
| A complaint specific to one strong rival | A switching opportunity | Target their customers with the fix |
| Praise concentrated on one rival | A table-stakes expectation you may miss | Match it before differentiating |
| Your own recurring complaint | A weakness competitors can exploit | Fix before spending on acquisition |
Example
A gym compared 40 reviews each for itself and two chains. Both chains had recurring complaints about crowding between 6 and 8 pm and about cancellation difficulties. The gym's own reviews praised trainers but mentioned hard-to-book classes. Actions: launch simple online class booking (own weakness), advertise "never crowded" evening sessions and one-click cancellation to the chains' frustrated members (their weaknesses).
Limits
- Reviews over-represent very happy and very unhappy customers.
- Some platforms filter or order reviews in ways that bias samples.
- Lexicon-based sentiment misses sarcasm and some local language. Read a sample of reviews yourself before acting on a number.
Review mining works best combined with scores and prices in a full competitor analysis.
A simple routine
- Pick your top three competitors and yourself.
- Copy 30 recent reviews from each, same platform, last six months.
- Run each set through the review analyzer or the Review mining module in the workspace.
- Write down the top two praised and top two criticised themes per business.
- Choose one action from each table row above.
- Repeat every quarter and compare.
What good looks like
A useful review-mining summary fits on one page:
| Business | Customers love | Customers complain about | Our move |
|---|---|---|---|
| Rival A | Quality, atmosphere | Waiting time, price | Promote no-wait bookings |
| Rival B | Price, speed | Cleanliness, staff | Emphasise hygiene and trained staff |
| Us | Staff, quality | Hard to book | Add online booking |
Frequently asked questions
Is it allowed to use competitors' reviews? Reading public reviews for analysis is normal market research. Do not copy reviews onto your own site or present them as your own.
What if a competitor has very few reviews? Combine platforms or look at social media comments. Fewer than ten reviews gives anecdotes, not patterns.
Should I respond differently to reviews after this? Yes. Mining your own reviews usually shows which complaints need a public, specific reply and a real fix.