Introduction
Like‑for‑like sales (also called comparable‑store sales, same‑store sales, comps, or identical‑store sales) are an adjusted growth metric used to evaluate revenue performance from a company’s existing, comparable operations while excluding results from stores, products, or divisions that would distort trend analysis (for example, newly opened locations, recent acquisitions, or stores that have closed). This metric helps managers and investors understand whether underlying business operations are improving, stable, or weakening independent of expansion activity or structural changes. (Source: Investopedia/T. Anand)1
Why Like‑for‑Like Sales Matter
– Isolates organic performance: Shows whether existing assets (stores, product lines) are getting more or less productive.
– Helps interpret total revenue growth: High total revenue growth with weak comps may indicate growth is driven by new openings rather than improved productivity of established units.
– Guides capital allocation: Informs decisions about opening new stores, closing underperformers, or investing in marketing/operations.
– Detects cannibalization: Reveals whether new stores are stealing sales from existing ones.
– Useful for investors: Analysts use comps to forecast margins, operating leverage, and the sustainability of growth.
How Like‑for‑Like Sales Are Typically Calculated
Basic formula:
Percent change in like‑for‑like sales = (Sales in current period from comparable units − Sales in prior period from those same units) / (Sales in prior period from those same units) × 100
Key choices that affect the calculation:
– Definition of “comparable” (commonly: locations open at least 12 months, but thresholds vary).
– Period comparison (year‑over‑year quarter, sequential quarter, trailing 12 months).
– Treatment of openings/closings: Many companies include only locations that have been open for a minimum period (e.g., ≥12 months).
– Adjustments for currency: Global retailers often report comps both at reported FX and constant currency to isolate operational performance from exchange rate swings.
– Exclusions: Remove stores whose performance was atypical (e.g., permanently closed, damaged, or heavily remodeled), and exclude revenue from acquisitions until comparable history exists. (Source: Investopedia)1
Practical Example (simple)
– Prior‑year sales for comparable stores (same set of stores during both periods): $90 million
– Current‑year sales for those same stores: $100 million
– Like‑for‑like growth = ($100M − $90M) / $90M × 100 = 11.11%
Real‑World Illustration
In Q1 2021 McDonald’s reported global comparable‑store sales up 7.5% and U.S. comparable sales up 13.6%, while total sales rose 9% overall. The combination of higher total sales but more modest comps growth indicated that new store openings contributed materially to total revenue growth while established stores also improved but to a lesser extent.2
Important Considerations & Limitations
– No universal standard: Companies may use different definitions and methodologies, which makes cross‑company comparisons tricky.
– Timing window matters: A 12‑month minimum is common but not universal; some retailers use different cutoffs.
– External shocks: Weather events, pandemics, or one‑off promotions can distort short‑term comparisons.
– Currency and macro effects: FX movements and economic cycles can mask operational performance unless adjusted.
– Omnichannel complexities: E‑commerce and buy‑online/pickup‑in‑store (BOPIS) sales require careful allocation to a store or centralized channel for accurate comps.
– Statistical significance: Small sample sizes (few stores) can make comps swings unreliable.
Step‑by‑Step Practical Guide to Calculating Like‑for‑Like Sales (for Retailers / Analysts)
1. Define the scope
• Decide which units are “comparable” (commonly: stores open ≥12 months).
• Decide whether to include product lines, channels (in‑store vs online), or geographies separately.
2. Select the time period
• Choose the reporting cadence: quarterly YoY, sequential, or trailing 12 months.
• For annual strategic reviews, use FY vs prior FY; for operational monitoring, use quarters or months.
3. Clean the data
• Exclude stores that opened or closed during the comparison window according to your chosen rule.
• Remove outliers caused by natural disasters, major remodeling, or temporary closures.
• Assign e‑commerce or marketplace sales consistently (e.g., allocated to the fulfilling store or reported separately).
4. Adjust for currency and acquisitions
• For multi‑country companies, report both reported comps and comps at constant currency, showing FX impact.
• Exclude revenues from large acquisitions until they have at least one comparable reporting period, or present them separately.
5. Compute the metric
• Sum sales for the qualifying set in the current and prior periods and apply the basic percent change formula.
6. Segment and analyze
• Break comps down by region, format (flagship vs small‑format), category, or customer cohort to spot trends.
• Perform cohort (vintage) analysis to see performance by store opening year or customer acquisition cohort.
7. Report with transparency
• Disclose the definition of comparable units, any exclusions, and currency adjustments.
• Include absolute sales levels in addition to percent changes to give scale context.
Practical Steps to Improve Like‑for‑Like Sales (Operational Playbook)
1. Promotions & pricing
• Run targeted promotions that increase traffic but monitor margin impact.
• Use localized pricing strategies where appropriate.
2. Customer loyalty & data
• Build or enhance loyalty programs to gather first‑party data and encourage repeat purchases.
• Use customer analytics to personalize offers and communications.
3. Merchandising & assortment
• Optimize product mix based on local demand; rotate fast‑movers and test new SKUs in comparable stores first.
• Use planograms and localized assortments to reflect regional preferences.
4. Store experience & staffing
• Improve in‑store experience (layout, signage, cleanliness) and invest in employee training to boost conversion and basket size.
• Use staffing models aligned to peak traffic to improve service and throughput.
5. Omnichannel integration
• Offer BOPIS, curbside pickup, and same‑day delivery integrated with store inventory to capture online demand without losing store credit.
• Allocate e‑commerce sales consistently for comparability.
6. Marketing & customer acquisition efficiency
• Focus on retention marketing (email, push, SMS) to increase repeat purchases per customer.
• Use acquisition only when it delivers profitable LTV (lifetime value), not just incremental foot traffic.
7. Operational reliability & assortment availability
• Reduce out‑of‑stock rates; lost sales due to stockouts depress comps.
• Improve category replenishment and supply chain responsiveness.
8. Test & iterate
• A/B test promotions, layouts, and price changes in representative comparable stores before wider rollout.
• Track lift in transactions, average basket value, and return visit rates.
For Investors & Analysts: How to Use Like‑for‑Like Sales
– Read the footnotes: Ensure you understand how the company defines comparable stores and any adjustments (FX, acquisitions).
– Compare comps to total revenue growth: Disparities indicate whether growth is organic or expansion‑driven.
– Look across segments: Are specific regions or formats driving comps?
– Pair comps with other KPIs: Average transaction value, transactions per period, margin trends, and operating leverage.
– Consider macro effects: Compare comps to peer group performance and retail industry indicators to separate company‑specific from sector‑wide drivers.
Reporting Best Practices & Governance
– Publish methodology in earnings releases and investor presentations.
– Provide both reported and constant‑currency comps (if applicable).
– Disclose the number of comparable units used in the calculation.
– Provide absolute sales alongside percent changes for context.
Checklist for Management Before Reporting Like‑for‑Like Sales
– [ ] Confirm “comparable” definition and cutoffs (e.g., ≥12 months).
– [ ] Reconcile and clean sales data for temporary closures/remodels.
– [ ] Decide and document FX and acquisition treatment.
– [ ] Segment comps by meaningful categories (region, format, channel).
– [ ] Include absolute sales numbers and disclose methodology publicly.
Summary
Like‑for‑like sales are a valuable tool for isolating organic performance from expansion or structural changes. They must be calculated and interpreted carefully because methodology differences, currency movements, omnichannel sales, and one‑off events can materially affect the measure. When well‑defined and transparently reported, comps provide critical insight for operations, capital allocation, and investor analysis.
Sources
1. Investopedia, “Like‑for‑Like Sales,” Tara Anand. Accessed Sept. 3, 2021.
2. McDonald’s Corporation, “McDonald’s Reports First Quarter 2021 Results,” Q1 2021 press release. Accessed Sept. 3, 2021.
– Create a spreadsheet template to calculate comparable‑store sales given your store‑level data.
– Walk through a worked example including currency adjustments, acquisitions, and e‑commerce allocation.