Same-store sales (also called comparable sales or comps) measure year-over-year revenue change at stores open at least a year, stripping out the lift from new openings. Operators, lenders, and real estate committees treat them as the cleanest read on whether a concept is getting stronger or just getting bigger.
That distinction is the whole point of the metric. A 30-store chain that opens ten locations will almost always grow total revenue. Whether each existing store sells more than it did last year is a different question, and it is the one that determines whether the next ten openings are a good idea.
What Same-Store Sales Actually Measure
Same-store sales isolate organic performance. The metric compares revenue from a fixed set of stores — the comparable base — against the same set in the prior-year period. Stores too new to have a clean comparison stay out of the base, so the number reflects how existing locations performed rather than how many new ones opened.
The definition sounds standard. It is not. Comparable sales is a non-GAAP metric, and every company sets its own rules. Dollar General's 10-K defines same-store sales as stores open at least 13 full fiscal months that remain open at the end of the reporting period. It also keeps remodeled, expanded, and relocated stores in the base. Other retailers pull remodels out. Some use 12 months, some 13, some 15. In 53-week fiscal years, most companies exclude the extra week so the comparison stays 52-on-52.
Three practical consequences:
- You cannot compare comps across companies without reading the footnotes. A retailer that excludes remodels will post different comps than one that includes them, on identical performance.
- The base changes every quarter. Stores enter as they pass the 13-month mark and exit when they close. The metric describes a moving population.
- The comp tells you nothing about new-store quality. A chain can post healthy comps while its newest openings underperform, because those stores have not entered the base yet.
How to Calculate Same-Store Sales
The formula is simple division:
Same-store sales growth = (current-period revenue from comp-base stores − prior-period revenue from the same stores) ÷ prior-period revenue from the same stores
A worked example. Say you run 42 stores. Six opened in the last year, so your comparable base is 36 stores. Those 36 stores did $54.0M this year against $52.2M in the same period last year:
($54.0M − $52.2M) ÷ $52.2M = +3.4% same-store sales
Meanwhile your total revenue grew from $52.2M to $61.5M (up 17.8%) because the six new stores added $7.5M. An investor deck that leads with 17.8% is telling the expansion story. The 3.4% is telling the health story. Both are true; only one predicts what store 43 will do.
The discipline that matters is keeping the store set identical in both periods. If a store closed in March, its prior-year revenue comes out of the base too. Mixing populations is the most common way operators accidentally flatter the number.
Why Comp Sales Drive Expansion Decisions
Comps do three jobs in an expansion program.
They are the portfolio health gate. Negative comps mean existing stores are shrinking, and growth capital spent on new units is partly refilling a leaking bucket. Lenders and franchisors read the metric the same way: sustained negative comps invite tighter development schedules and harder questions about whether the concept has saturated its markets.
They calibrate the forecast for every new site. Most site-level revenue forecasts are built on analogs — what comparable existing stores actually do. If the comp base is trending down 3% a year, a forecast that assumes flat performance at a new site inherits a hidden 3% optimism. Sales forecast accuracy starts with an honest read on the trend in the stores you already have.
They set the committee's risk appetite. The 2025 numbers show how differently this can play out. McDonald's closed 2025 with U.S. comparable sales up 6.8% in Q4 and positive guest counts — comps and expansion pointing the same direction, which makes every new site easier to defend. Chipotle had the opposite year: full-year comparable restaurant sales fell 1.7%, with Q4 down 2.5%, yet the company opened 334 new restaurants. Chipotle is betting that unit-level economics, the volumes and cash-on-cash returns at new sites, justify development even while the existing base softens. Either way, the comp number framed the decision.
The pattern across both: comps are the context every site decision gets made inside. A retail expansion strategy that ignores them is flying without an altimeter.
Where Same-Store Sales Mislead
The metric has well-documented blind spots. Four show up constantly in expansion planning.
1. Price increases can mask traffic declines
A comp is traffic times ticket. When menu prices or product mix push the average check up faster than customer counts fall, the comp stays positive while the customer base erodes. In October 2025, Black Box Intelligence measured restaurant industry same-store sales at +0.7% with same-store traffic at −2.0%. The industry "grew" while serving fewer guests.
This is why the decomposition matters more than the headline. Starbucks reported North America comparable sales up 4% in Q1 FY2026, built on a 3% gain in comparable transactions. A comp built on traffic is durable. A comp built on price has a ceiling, and customers decide where it is.
2. Closing weak stores inflates the comp
When a chain closes its worst performers, the survivors define the base. The portfolio looks healthier even if no individual store improved. Watch for comps that improve in the same year a retailer announces a fleet rationalization — some of that improvement is arithmetic, not recovery. If you are diagnosing weak locations rather than celebrating their removal, location data can tell you why a store underperforms before you decide whether closing it is the right call.
3. Your own expansion depresses the comp
Open a new store three miles from an existing one and the existing store's comp absorbs the hit. The transfer of sales from old stores to new ones — cannibalization — shows up as comp weakness even when the market-level decision was sound. Operators who expand into their strongest markets see this constantly: total market revenue rises while the comp dips. Before reading a soft comp as concept weakness, calculate how much of it is self-inflicted.
4. Definitions shift under your feet
Remodel programs, loyalty launches, and calendar shifts all move the comp without changing underlying demand. A store that doubled its footprint can sit in the comp base posting 40% "growth." A loyalty program that pulled spend forward makes next year's comparison artificially hard. All of it is legitimate accounting. It is also why a single quarter's comp is a weak signal and a multi-year traffic trend is a strong one.
Comps Tell You When to Expand. They Cannot Tell You Where
Same-store sales are a portfolio-level instrument. They aggregate every location into one number, which is exactly what makes them useful to a board and nearly useless for picking the next site. A +4% comp does not tell you whether the vacancy your broker just sent over will do $1.8M or $1.1M, or whether it will take 12% of the revenue from your store four miles away.
That requires site-level work: trade areas, foot traffic, demographics, and a revenue forecast built on the analog stores that actually resemble the candidate site. It also requires knowing which metrics in your own portfolio actually predict performance — which is less obvious than it sounds. One VP of Real Estate at a multi-location veterinary group put it this way after rebuilding their model: "We thought we understood what made a good site. GrowthFactor showed us our primary KPI was hiding the real story — and the variables we'd been ignoring were the ones that actually predicted revenue. Now every forecast is built on what drives our business, not assumptions we never tested."
That is the comp-sales lesson applied one level down. The headline number you watch can hide the variables that matter, whether the headline is a portfolio comp or a single store's revenue. Customers who run this workflow report roughly 80% fewer underperforming locations once site decisions are built on tested variables instead of assumptions, and store-level optimization gets easier when the sites were picked well to begin with.
Read your comps for what they are: the truest available signal of whether your existing fleet is earning the right to grow. Then make the where decision with site-level evidence, so the stores you open this year strengthen the comp base they will join 13 months from now.
Your comp trend sets the stakes for the next ten sites. See it on your markets: score a candidate site and inspect the forecast, the analogs behind it, and the cannibalization math before committee.