OperationsHow to reply to negative reviews across a franchise
A reply standard franchisees can follow: what a good response includes, worked examples, and which complaints should go to head office.
How one weak branch pulls down a multi-site brand's rating, why the group average hides it, and a simple method to find the branch that's costing you most.

One branch drags down a brand rating in two ways. In any combined score, busy branches with lots of reviews count for more, so one weak, busy site can pull the whole figure down. And customers who have a bad experience at one site tend to judge the brand, not just the branch.
To find the culprit, rank branches by how much they pull the group down, not by star rating alone. Multiply each branch's gap to the group median by its share of the group's reviews. The branch with the biggest number is costing you most.
This guide is for marketing and operations leads at multi-site groups. It works through one retail example and one food and drink example.
A combined rating is a weighted average: each branch counts in proportion to how many reviews it has. So a branch's pull on the brand depends on two things, how far below the others it sits and how busy it is.
Combined ratings turn up in more places than you might think: a brand-wide profile on a review site, an app store rating, and the group figure in a board or head-office report.
A two-store example shows the effect. Store A has a 4.6 rating from 100 reviews. Store B has 3.8 from 300 reviews. The combined rating is 4.0, not the 4.2 you'd get by averaging the two ratings, because Store B wrote three-quarters of the reviews.
The group figure also hides the culprit. A brand rating of 4.3 looks the same whether every site sits at 4.3 or one busy site sits at 3.7 and the rest are fine.
For a multi-site brand, every branch draws on the same reputation, so one weak site spends trust that the others have earned. Research on chains points the same way.
These studies are American and, in two cases, years old. Read them as evidence of how customers treat chains, not as UK forecasts.
Rank branches by their drag on the group, not by their star rating. Drag combines how far a branch sits below its peers with how many of the group's reviews it accounts for.
Drag = (group median rating − branch rating) × (branch reviews ÷ all group reviews)
Drag tells you, in stars, how much the group rating would rise if that one branch performed like a typical branch. A positive number means the branch is pulling the group down. A negative number means it's holding the group up. Use the median rather than the average as the benchmark, so the weak branch doesn't lower the bar it's measured against.
Six steps, using a spreadsheet:
In this illustrative group, the lowest-rated store is not the one doing the most damage. The numbers are invented to show the method.
The group received 2,540 reviews in 90 days, for a combined rating of 4.30. The median store rating is 4.45.
| Store | Reviews (90 days) | Rating | Share of reviews | Gap to median | Drag (stars) |
|---|---|---|---|---|---|
| Leeds | 420 | 3.7 | 16.5% | 0.75 | 0.124 |
| Bath | 70 | 3.6 | 2.8% | 0.85 | 0.023 |
| Birmingham | 350 | 4.3 | 13.8% | 0.15 | 0.021 |
| Manchester | 380 | 4.4 | 15.0% | 0.05 | 0.007 |
| Glasgow | 260 | 4.4 | 10.2% | 0.05 | 0.005 |
| Newcastle | 180 | 4.4 | 7.1% | 0.05 | 0.004 |
| Nottingham | 160 | 4.5 | 6.3% | −0.05 | −0.003 |
| Harrogate | 60 | 4.6 | 2.4% | −0.15 | −0.004 |
| Liverpool | 200 | 4.5 | 7.9% | −0.05 | −0.004 |
| Bristol | 220 | 4.5 | 8.7% | −0.05 | −0.004 |
| Sheffield | 150 | 4.6 | 5.9% | −0.15 | −0.009 |
| York | 90 | 4.7 | 3.5% | −0.25 | −0.009 |
Ranked by star rating, Bath looks like the problem at 3.6. But Bath accounts for under 3% of the group's reviews. Leeds, at 3.7, accounts for 16.5%, so its drag is more than five times Bath's.
If Leeds performed like a typical store, the group rating would rise from 4.30 to 4.42. Bringing Bath up to the median would add 0.02. Bath still deserves a look, but Leeds is where the group number moves.
In this illustrative group, one busy commuter site holds the whole brand below 4.5. Again, the numbers are invented to show the method.
The group received 900 reviews in 90 days, for a combined rating of 4.37. The median site rating is 4.5.
| Site | Reviews (90 days) | Rating | Share of reviews | Gap to median | Drag (stars) |
|---|---|---|---|---|---|
| Station Road | 240 | 4.0 | 26.7% | 0.50 | 0.133 |
| Retail Park | 25 | 3.5 | 2.8% | 1.00 | 0.028 |
| University Campus | 160 | 4.4 | 17.8% | 0.10 | 0.018 |
| Market Square | 110 | 4.5 | 12.2% | 0.00 | 0.000 |
| Hospital | 60 | 4.5 | 6.7% | 0.00 | 0.000 |
| Old Town | 80 | 4.6 | 8.9% | −0.10 | −0.009 |
| High Street | 130 | 4.6 | 14.4% | −0.10 | −0.014 |
| Riverside | 95 | 4.7 | 10.6% | −0.20 | −0.021 |
Station Road is the group's busiest site, with more than a quarter of all reviews. At 4.0 it carries nearly five times the drag of Retail Park, even though Retail Park has the lower rating.
If Station Road performed like a typical site, the group rating would rise from 4.37 to 4.50. On a brand-wide profile, that is the 4.5 line 31% of BrightLocal's 2026 US respondents said they use.
The next step is reading Station Road's one- and two-star reviews. Suppose most mention queues at the morning rush. That points to a staffing or layout fix at one site, not a brand-wide campaign.
Retail Park needs watching rather than action for now. With 25 reviews in 90 days, one bad week can move its rating a long way.
Act when a branch tops the drag ranking in two 90-day periods running, has at least 20 reviews in each, and its low reviews share one theme you can fix. Watch rather than act when any of those three is missing.
Signs it's noise:
After you act, run the same calculation for the next 90 days. If the branch's drag falls and its main complaint theme shrinks, the fix worked. If the drag holds, the theme you picked probably wasn't the cause.
Drag shows where to look, not who to blame. A busy site will always carry more weight, and a fair reading takes the location, the trading pattern and the team's own view into account.
This is the work Akili was built to take on. It scores every branch on the same measures from reviews and social comments, shows which sites are pulling the brand down and why, and ranks what to fix first. It's well suited to multi-site retail and food and drink groups. If you'd like to see it on your own branches, book a demo.
Combined ratings weight each branch by its number of reviews, so one or two busy branches with lower ratings can pull the brand figure down on their own. Rank branches by drag to see which ones.
Not on its own. Star rating ignores how many reviews a branch contributes, so the lowest-rated site is often not the one doing most damage. Rank by drag, which combines the gap to your group median with each branch's share of reviews.
There's no universal number, so compare each branch with your own group median. As a guide to customer behaviour, BrightLocal's 2026 US survey found 68% of consumers would only use a business rated four stars or more.
Monthly, on a rolling 90 days of reviews. A monthly check catches problems early, and 90 days gives most branches enough reviews to trust.
Yes. The calculation is the same for company-owned and franchised sites. Sharing the ranking with franchisees also matters: research on Los Angeles restaurants found that making each unit's hygiene score public closed the gap between franchised and company-owned sites.
OperationsA reply standard franchisees can follow: what a good response includes, worked examples, and which complaints should go to head office.
Customer insightA step-by-step method for multi-site brands to track Google reviews branch by branch, the measures to watch, and where spreadsheets stop working.
We will show you how customers see every location, and which fixes will grow revenue and cut churn.