What are like-for-like sales?

Like-for-like sales, also called comparable or same-store sales, compare revenue from the same set of locations across two periods. Excluding new openings and closures isolates genuine trading performance from the effect of changing the estate size.

How do you calculate like-for-like sales growth?

Subtract prior period sales from current period sales, divide by prior period sales, and multiply by 100. Both figures must cover only locations trading in both periods.

Why exclude new locations from like-for-like sales?

New sites add revenue simply by existing, which flatters total sales growth and hides whether existing locations are improving or declining. Like-for-like strips that effect out.

What is a good like-for-like sales growth rate?

Anything above inflation represents genuine real-terms growth. Flat like-for-like sales during a high-inflation period usually means volume is falling while prices rise, which is worth investigating.

Should like-for-like sales be adjusted for price increases?

For a full picture, yes. Splitting like-for-like growth into price and volume components shows whether growth comes from charging more or serving more, which have very different long-term implications.

Like-for-Like Sales Calculator

Compare sales for the same set of locations across two periods to find true comparable growth.

Prior Period Sales

Current Period Sales Only include locations open in both periods.

Result

Enter prior and current period sales to see LFL growth.

What like-for-like sales actually measure

Like-for-like sales — also called comparable sales, same-store sales, or simply LFL — compare revenue from the same set of locations across two periods. Any site that was not trading in both periods is excluded from both sides of the comparison.

The point is to isolate genuine trading performance from the effect of changing the size of the estate. Total sales growth conflates two completely different things: whether your existing restaurants are doing better, and whether you opened more of them. Only the first tells you anything about the health of the business.

LFL Growth % = ((Current Period − Prior Period) ÷ Prior Period) × 100

Why total sales growth misleads

Consider a group with four restaurants turning over $2.4m last year. This year it opens two more sites and reports $3.1m — growth of 29%, which reads as an excellent year.

Now strip out the new openings. The original four sites turned over $2.4m last year and $2.26m this year. Like-for-like sales are down 5.8%. The group is buying growth by opening sites while its existing estate declines — a pattern that works right up until the capital runs out.

This is exactly why public restaurant groups lead with like-for-like in their results, and why investors read that line before any other.

Getting the comparison right

The calculation is trivial. The discipline is in defining the comparison, and small inconsistencies produce misleading numbers.

Which sites qualify

The standard convention is that a site enters the like-for-like base once it has traded for a full year, because new restaurants go through an opening spike followed by a settling period that has nothing to do with underlying performance. Sites that closed, were refurbished for an extended period, or were significantly remodelled are usually excluded for the affected periods.

Whatever rule you adopt, write it down and apply it consistently. Quietly changing the qualifying base between reporting periods makes the entire series meaningless.

Align the calendar

Compare equivalent trading periods, not equivalent dates. A month with five Saturdays against one with four will show growth that is purely a calendar artefact. Where a public holiday moves between periods — Easter is the classic case — note it explicitly. Many groups compare 52-week periods aligned by day of week rather than calendar months for exactly this reason.

Be consistent about what counts as revenue

Decide whether delivery, catering, retail, and gift card redemptions are in or out, and keep that definition stable. Adding delivery revenue to the current period but not the prior one produces growth that is entirely fictional.

Splitting growth into price and volume

A single like-for-like percentage hides the most important part of the story. Sales grow either because you served more guests or because you charged them more, and those two have very different implications.

Sales Growth ≈ Volume Growth + Price Growth

Suppose like-for-like sales are up 6% and you raised menu prices by 7% during the period. Volume is down roughly 1% — you are serving fewer guests and covering it with price. That works for a while, but it is a finite strategy, and the trend usually accelerates.

The reverse case is stronger: like-for-like up 4% with no price increase means 4% more guests, which is genuine demand growth and the foundation for a price rise later.

Track cover counts and average check alongside revenue so you can always decompose the number. Average check itself splits further into price and mix — guests trading up to more expensive dishes lifts average check without any price change at all.

How to read your result

LFL Result	What it usually means
Above inflation	Genuine real-terms growth. Check whether it is volume or price led.
Positive but below inflation	Going backwards in real terms. Volume is almost certainly falling.
Flat	With any price increase applied, this means a real decline in guests.
Negative	Investigate before cutting costs. Establish whether it is market-wide or specific to you.

Always compare against inflation and, where you can find it, against a market benchmark. Like-for-like down 2% in a market that is down 6% is a strong relative performance and a completely different conversation from the same number in a growing market.

Diagnosing a decline

When like-for-like turns negative, work through the possibilities in order:

Is it all sites or a few? Estate-wide points to brand, pricing, or market. One or two sites points to local management, a new competitor, or a change in local footfall.
Is it volume or check? Falling covers with a stable check is a demand problem. A falling check with stable covers means guests are trading down.
Is it a particular daypart? Lunch collapsing while dinner holds is a very different problem from a uniform decline.
Did something change? Menu revision, price increase, staff turnover, a road closure, or a new competitor opening nearby.

Falling sales put immediate pressure on margins, because fixed costs do not decline with revenue. Re-run your break-even point as soon as a decline is confirmed, and check whether prime cost is drifting as volume drops.

Frequently asked questions

When does a new restaurant enter the like-for-like base?

Most operators use 12 months of trading, some use 14–18 months to be sure the opening period has fully settled. Any consistent rule works; changing it between periods does not.

Should like-for-like be adjusted for inflation?

Headline like-for-like is normally reported in nominal terms, but you should always interpret it against inflation. Some groups additionally report a volume or transaction-count figure, which is the cleanest read on real demand.

Can a single restaurant use like-for-like?

Yes — compare the same site period over period, typically this year against last year for the same trading weeks. The multi-site adjustments do not apply, but the calendar alignment and price-versus-volume analysis matter just as much.

What about a site that was closed for refurbishment?

Exclude it from both periods for the affected months, then reintroduce it once it has traded a full comparable period post-reopening. Leaving a partially closed site in the base makes the whole estate look worse than it is.

How does delivery affect like-for-like sales?

Delivery can flatter like-for-like considerably while contributing much less margin, because platform commissions of 20–30% are variable costs. If delivery grew as a share of revenue between the two periods, look at like-for-like gross profit rather than revenue alone — sales can rise while contribution falls.