Free tool · Robert × Dor
Multi-store conversion
calculator.
Enter visitors and transactions for each store, or paste them from a spreadsheet. See your chain’s true conversion rate, rank every store, spot the outliers and size the revenue gap to your best performer.
Multi-store conversion calculator
Chain conversion rate (weighted)
18.1%
5,249 transactions from 29,000 visitors across 5 stores. The simple average of store rates is 19.6%, higher because your smaller stores convert better.
- Best store
- Riverside
- 24.0% conversion
- Spread best to worst
- 11.0 pts
- Revenue gap to best store
- $72,108
- 1,711 more sales
- Sales in this period
- $240,756
- transactions × avg sale
| # | Store | Conversion | vs chain | Gap to best |
|---|---|---|---|---|
| 1 | RiversideOutlier: high | 24.0% | +33% | – |
| 2 | Old TownOutlier: high | 23.0% | +27% | $1,250 |
| 3 | Downtown | 21.0% | +16% | $8,928 |
| 4 | Mall | 17.0% | −6% | $30,184 |
| 5 | AirportOutlier: low | 13.0% | −28% | $31,746 |
| All stores | 18.1% | $72,108 |
Outlier means at least 20% above or below the chain rate and too far off to be day-to-day chance for that store’s traffic (|z| > 2). The gap assumes each store could reach the best store (24.0%) at its own average sale; it’s an upper bound, not a forecast.
Show your work
Weighted (chain) rate = total transactions ÷ total visitors5,249 ÷ 29,000 = 18.10%Simple average = sum of store rates ÷ number of stores24.0% + 23.0% + 21.0% + 17.0% + 13.0% ÷ 5 = 19.60%Gap = (target rate − store rate) × store visitors × store avg saleOld Town: (24.0% − 23.0%) × 2,500 × $50.00 = $1,250z = (store rate − chain rate) ÷ √(chain rate × (1 − chain rate) ÷ store visitors)Airport: z = -11.4
Worked example.
Five stores over the same month: Downtown 6,200 visitors and 1,302 transactions, Mall 9,800 and 1,666, Riverside 3,100 and 744, Airport 7,400 and 962, Old Town 2,500 and 575.
- Store rates: Riverside 24.0%, Old Town 23.0%, Downtown 21.0%, Mall 17.0%, Airport 13.0%.
- Simple average: (21 + 17 + 24 + 13 + 23) ÷ 5 = 19.6%.
- Weighted chain rate: 5,249 ÷ 29,000 = 18.1%. It’s lower because the two busiest stores, Mall and Airport, convert worst.
- Airport’s gap to Riverside: (24% − 13%) × 7,400 × $39 = $31,746. Mall’s: 7 points × 9,800 × $44 = $30,184. Across all stores, $72,108.
Riverside, Old Town and Airport are flagged as outliers: each is more than 20% from the chain rate on enough traffic that chance doesn’t explain it. Mall converts below average too, but only 6% below, so it isn’t flagged.
Weighted or average: which one to report?
The weighted rate (all transactions ÷ all visitors) is what the business actually converted. Use it for the chain’s headline number and for any revenue maths. The simple average treats a quiet store the same as a flagship, so it describes the typical store rather than the typical visitor.
When the two differ a lot, store size and conversion are linked. Busy stores often convert lower because of browsers, tourists or understaffing at peak. That is worth checking hour by hour before you copy the best store’s playbook.
- Compare like with like. An airport or tourist store will rarely match a neighbourhood store. Compare each store with its own past and with similar formats.
- Count visitors the same way everywhere. Different counters, door setups or staff exclusion rules make rates incomparable.
Questions retailers ask.
How do I calculate conversion rate across several stores?
Add up transactions across all stores and divide by total visitors. Averaging each store’s rate gives every store equal weight, which overstates or understates the chain depending on which stores are busiest.
Why is my weighted conversion lower than the average?
Your busiest stores convert below your quiet ones. The weighted rate counts every visitor equally, so high-traffic, low-conversion stores pull it down.
How is the revenue gap calculated?
For each store below the target, the missing conversion points are multiplied by its visitors and average sale. It shows what closing the gap would be worth, assuming the extra buyers spend like current ones.
What makes a store an outlier here?
Its conversion is at least 20% above or below the chain rate, and the difference is larger than two standard errors given the store’s traffic, so it is unlikely to be random variation.
Can I paste data from Excel or Google Sheets?
Yes. Copy the store name, visitors, transactions and optionally average sale columns, then paste them into the box. Tab-separated data from a spreadsheet works best.
Compare stores on measured traffic.
Store comparisons are only as good as the visitor counts. Dor counts every door the same way and pairs it with each store’s POS sales.
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