Review monitoring across a 1000-outlet franchise

A franchise with 1000 outlets across the country. The reputation of every location lives on Yandex Maps: reviews, ratings, guest photos. A single outlet can damage the brand in its own city — and the franchisor learns about it last: franchisees have their own accounts, the head office has no access to them, only the public pages.

What breaks with manual monitoring

To understand what's happening in the outlets, someone had to open each page and read the reviews by hand. A thousand outlets means thousands of reviews, and among them you have to find the few that signal a real problem — violations that hurt the guest and the brand's reputation. Reading everything takes time nobody has. Spot checks don't save you: a problem can sit for weeks until someone stumbles on it, and if it repeats in several cities it's a systemic franchise failure that's invisible without a consolidated view.

Why manual monitoring didn't help

The issue isn't that reviews are bad — it's that they can't be processed by hand at the scale of a network. Even if you assign someone to read everything, one person doesn't cover a thousand outlets, and conclusions from a random sample don't show the picture. What was needed was a process that reads 100% of reviews and leaves only the signals to a human.

What we did: an agent collects and tags reviews across the network

We connected an agent: it maintains a register of all outlets and continuously collects their reviews, reads each one and breaks it down by topic with a severity level.

• Outlet register: name, city, address, page link — the whole network in one list instead of scattered across franchisee accounts.
• The agent pulls reviews from the maps for every outlet on an ongoing basis and makes sure collection covers the entire network: for each outlet you can see when its reviews were last collected.
• Each review is read and analysed: tags by topic with a severity level — red, orange, yellow — plus a short summary of what the review says.
• Problematic reviews are marked with a red flag: the head office doesn't need to read everything, only the signals.
• The dashboard shows: new red flags, how many outlets are affected, the top problem topics and the worst outlets by number of signals.
• Reviewed items get a status, so a signal doesn't get lost in the flow and it's clear it has already been handled.

The head office doesn't need to read thousands of reviews

Open the dashboard and see where and what happened: outlet, city, topic, review summary. Instead of "we should check the network sometime" — a concrete list of addresses with problems and priorities. A systemic topic repeated across a dozen cities is visible immediately, so you can act on the whole franchise rather than one outlet.

What stays with the human

Working through the red flags: contacting the outlet, replying to the guest, fixing the process. And deciding on systemic topics — if the same problem keeps repeating across the network, that's a signal for the whole franchise. The agent collects and tags, the human decides — the routine goes to the agent.