Same-Store Sales Growth: Is Retail Growth Just More Shops?
Learn the same-store sales growth formula with a worked example. Separate existing-store demand from new openings, price increases and retail expansion.
Same-store sales growth measures how sales changed at an eligible group of existing shops, rather than allowing new openings to explain the whole growth story. It helps an analyst ask whether the established store network is selling more, but the company’s definition and the price-versus-volume split still matter.
A retailer can open many shops and report higher total revenue while its older shops sell less. Another can add few shops but generate stronger sales from its existing network. The headline growth rate alone does not distinguish the two.
The formula is simple; choosing the stores is not
For a consistent comparable group, the calculation is:
Same-store sales growth = current-period sales from the group ÷ prior-period sales from the same group − 1.
The difficult word is “same”. A store that opened halfway through the prior period may not provide a fair comparison. Renovations, relocations, closures, acquisitions and online fulfilment can also change the perimeter.
An issuer may require a shop to have operated for a minimum period before including it. DMart’s investor presentation dated 11 January 2025, in its operating-summary footnote, defines its like-for-like cohort using stores operational for at least 24 months at the reporting-period end. That is a dated example of why the footnote matters, not a current operating statistic or a rule for every retailer.
When comparing companies, record the definition beside the number. Two percentages with different store-age cut-offs are not automatically comparable.
A worked example: 17% growth can hide weaker old stores
All numbers below are hypothetical. They are not DMart, Trent or another listed retailer’s results. Assume every earlier-period store qualifies for the comparable group, no stores close, and the later period has additional new stores.
| Sales source | Earlier period | Later period |
|---|---|---|
| Same established store group | ₹100 crore | ₹97 crore |
| Newly opened stores | Nil | ₹20 crore |
| Total revenue | ₹100 crore | ₹117 crore |
Total growth is ₹117 crore divided by ₹100 crore, minus one: 17%.
Same-store growth is ₹97 crore divided by ₹100 crore, minus one: negative 3%.
The reconciliation is ₹100 crore, less ₹3 crore at existing stores, plus ₹20 crore from new stores, equals ₹117 crore. New shops more than offset the decline in the established network.
That is not proof that the expansion is unwise. New stores may be building a valuable network. It does mean the headline cannot be presented as evidence that established-store demand improved.
In real disclosures the bridge is often less complete. Young stores may appear in both periods but remain outside the comparable cohort, and online sales may sit elsewhere. Do not assume total growth minus same-store growth equals a clean new-store contribution.
Positive sales growth is not necessarily more shoppers
Sales value can rise because of more transactions, larger baskets, higher prices or a shift toward higher-value products. Same-store growth holds the store perimeter more stable; it does not hold prices or mix constant.
A second hypothetical example illustrates the distinction. Suppose an unchanged store group records 5% more transactions but the average bill is 2% smaller. Sales growth is 1.05 × 0.98 − 1 = 2.9%, not 3%. If the average bill rises instead because prices increased, sales growth need not imply an equal increase in units purchased.
Transactions, units, average bill and product mix answer related but different questions. When a company does not disclose one, mark it unavailable. Dividing sales by an assumed customer count creates precision without evidence.
Festival timing adds another complication. A shopping period moving between quarters can change comparable sales even when the same outlets qualify. Use our Diwali date-shift guide to distinguish a calendar effect from a sustained change.
Why revenue per square foot is a separate measure
Sales density divides revenue by a measure of selling space. Its interpretation depends on whether the company uses average or closing area, how it treats stores open for only part of a period, and whether the revenue and area cover the same business.
Opening a large store near quarter-end can expand closing area before it contributes a full quarter of revenue. A lower revenue-per-square-foot figure can therefore reflect timing or store mix rather than a deterioration in mature stores.
Read sales density alongside same-store growth, selling area and openings. None of the four is a substitute for the other three.
What to check after the revenue bridge
Expansion needs capital and operating resources. Ask how much cash new stores consume, how inventories and lease commitments change, and whether early store costs affect margins. Owned-property and leased formats require different interpretations of costs and capital employed.
Also ask whether a new outlet redirects sales from a nearby old one. A store-level decline may reflect cannibalisation within a growing local network. Without location-level evidence, that remains a question to investigate rather than a conclusion to publish.
The DMart business-model explainer discusses its cost and property choices. The retail revenue bridge provides the broader framework for separating volume, price and scope.
Keep a repeatable quarterly record
For each disclosure, retain the comparable-store definition, reporting dates, sales scope, new openings, closures and supporting transaction or basket data. Write down what is missing and what changed in the definition. A change of cohort can matter as much as a change in the percentage.
Altys is built around source-linked research and reusable company-analysis work. Request access with a retailer and a quarterly research task to evaluate the workflow. The point is to make evidence easier to review, not to replace judgment with a single growth score.
Strong same-store growth does not establish a fair valuation or predict a share-price outcome. This is a method for understanding reported business performance, not a recommendation to own any retailer.
Frequently asked questions
What is same-store sales growth?
It compares sales from an eligible group of existing stores across comparable periods. The company defines eligibility, so check store age, closures, renovations and online-channel treatment.
How do you calculate same-store sales growth?
Divide current-period sales from the comparable store group by its prior-period sales and subtract one. Both periods must use the same eligible group and a consistent sales definition.
Are same-store sales and like-for-like growth identical?
They often describe similar comparisons, but the labels do not guarantee identical definitions across retailers. Read each issuer's eligibility and adjustment rules.
Can total revenue rise while existing-store sales fall?
Yes. Sales added by new stores or other channels can outweigh a decline in the comparable store group. That is why expansion and existing-store performance should be reviewed separately.
Does positive same-store sales growth prove demand is stronger?
No. Higher prices, product mix, selling days and calendar shifts can lift sales value without an equivalent rise in transactions or units. Check the supporting operating disclosures.