Benchmark every store, strengthen every Google profile
Compare store-level ratings and sentiment side by side, and spot staff performance trends from what shoppers actually name in reviews.
What shoppers write about
Retail reviews are written about one branch on one afternoon. Read at chain level they turn into noise; read store by store they turn into a to-do list.
Whether the thing was in stock
A trip made for one item that was not on the shelf is the most common reason a regular customer leaves a first review, and it is always about a specific store.
Whether anyone helped them
Floor staff get named by first name in reviews. Those mentions are the closest thing to a shift-level record of who is doing the job well.
How long the queue was
Checkout waits and closed tills come up constantly, and they cluster around particular stores and particular hours rather than the brand.
How a return was handled
Returns and exchanges are where a policy meets a person. A refused return generates a longer, angrier review than almost anything else in retail.
One console for the whole estate
Compare stores fairly, collect reviews at the till, and answer everything without a head-office bottleneck.
Store-by-store leaderboards
Rank every storefront on rating, review volume and response rate so a struggling branch is visible before the chain average moves.
QR codes at the till and on receipts
Printable codes for the counter, the bag or the receipt. One scan opens your branded page and goes straight to Google.
AI replies in your brand voice
Draft a reply for every store in one consistent voice, grounded in your own returns and service policies through the knowledge base.
Staff and service mention tracking
Sentiment analysis surfaces which staff and which themes are being named, so recognition and coaching come from real customer words.
Google Posts for promotions
Schedule and bulk-publish posts across stores so a promotion appears on every profile without a manager doing it store by store.
Profile health per storefront
Each store gets a health score flagging wrong hours, missing categories and photo sets that have not changed in a year.
Built for Retail & Multi-Store
- Store-by-store leaderboards
- Staff performance from real review mentions
- Google Posts for promotions
A month across twelve stores
The shape of the reporting you get, per store and rolled up.
- Reviews collected
- 946
- Replied within 24h
- 91%
- Stores above 4.5
- 8 of 12
- Queue mentions
- 74
These figures are invented to show the report layout. They are not customer results and not a performance promise — your own numbers depend on your footfall, your timing and how you ask.
Before you decide
The things this industry asks us most, answered plainly.
Can a store manager see only their own store?
Yes. Role-based permissions scope a user to the locations they run, so a manager sees their own reviews and their own reporting, while regional and head-office users get the roll-up across the estate.
How do I compare stores fairly when they are different sizes?
The benchmarking view shows rating, review volume and response rate together rather than a single ranking, so a small high street store is not judged against a flagship purely on volume.
Can one person reply for every store?
Yes. Bulk reply and AI drafts let a single person work through the whole estate in one queue, and automation rules can publish routine positive replies while holding anything critical for approval.
Twelve stores should not mean twelve blind spots.
Put every storefront in one view, see which ones need help this week, and answer the whole estate from a single queue.