Like-for-like: The Definitive Guide to Understanding and Applying the Metric

In business reporting, the term Like-for-like is widely used to compare performance across comparable periods and stores. This article explains what Like-for-like means, how it’s calculated, and why it matters for retailers, hoteliers, and online businesses alike. We’ll explore the nuances, common pitfalls, and practical steps for robust Like-for-like reporting.

Like-for-like: Defining the Core Concept

Like-for-like, often written Like-for-like or like-for-like, is a benchmark that aims to measure performance by stripping away effects that would not be experienced by a normally operating unit. In practice, this means comparing sales, volumes, or other metrics for stores or periods that are truly comparable. The goal is to create a level playing field so executives, investors, and analysts can assess underlying growth without distortions caused by store openings, closures, acquisitions, or currency movements.

Like-for-like versus other metrics

• Like-for-like focuses on items and units that have existed for a sufficient period, allowing for a fair comparison across periods.
• Reported growth might mix effects from new stores, disposals, or currency fluctuations, and can be less useful for evaluating ongoing performance.
• Constant currency like-for-like adjusts for exchange rate movements to reveal underlying performance in local terms.

In short, Like-for-like is a method of isolating the business’s intrinsic performance from structural changes in the portfolio. When used consistently, it provides a clearer picture of what is driving growth or decline.

Like-for-like: The History and Why It Matters

The concept emerged from retail and consumer industries where monthly and quarterly results can be heavily influenced by opening new shops or closing underperformers. As chains expand, investors want to separate expansion effects from true operational performance. The historical emphasis on Like-for-like has since broadened to hospitality, services, and online marketplaces, where comparable bases still matter for trends and forecasting.

Today, Like-for-like is a staple in annual reports, investor presentations, and strategy reviews. It provides consistency, comparability, and a common language across geographies and business models. For stakeholders, it’s a signal of how efficiently the core business is performing, independent of growth through acquisitions or portfolio reshaping.

How Like-for-like is Calculated

Calculating Like-for-like can seem straightforward, but the exact rules matter. A robust approach requires clear boundaries about what is included in the base and which items are excluded.

Basic formula

The simplest form of Like-for-like compares the same set of stores or units over two periods. The basic idea is to measure the change in sales or other metrics for consistent, existing outlets.

Basic formula sample for sales:

Like-for-like sales growth = [(Sales in Period B from Like-for-like units – Sales in Period A from the same units) ÷ Sales in Period A from the same units] × 100

Where Period A is the prior period, and Period B is the current period. The calculation excludes new stores opened after Period A and excludes stores closed by Period B.

Adjustments and exclusions

To ensure comparability, many organisations apply standard adjustments. Common exclusions include:

• New stores opened after the start of Period A (and those that have not been trading for a full period in both periods).
• Store closures or disposals during the period under review.
• Acquisitions and disposals that impact the store base during the period.
• Currency effects for multinational groups when presenting in a single reporting currency (constant currency).
• Promotional periods and one-off events that do not reflect normal trading patterns.

Some businesses report both Like-for-like and Constant currency Like-for-like to give a clearer view of performance independent of exchange rate volatility.

Calendar considerations

Calendar effects can influence Like-for-like results. For example, a quarter containing an extra trading day, holidays, or a late Easter can skew comparisons. When calendars differ between periods, analysts may adjust for the number of trading days or use trailing twelve months (TTM) Like-for-like to smooth seasonality.

Like-for-like Across Sectors

The core principle of Like-for-like translates across sectors, but the specifics vary by industry. Below are some common applications.

Like-for-like in Retail and Consumer Goods

In retail, Like-for-like is a central metric for evaluating core performance across stores. It answers questions such as: Are customers buying more per visit? Are footfalls translating into higher basket values? The metric is sometimes expressed as sales growth per existing store, per square foot, or per customer visit, depending on the business model.

Retailers often separate:

• Goods sold in stores versus online (to understand the channel mix).
• Discounting effects (to ensure that promotions don’t distort true underlying demand).
• Seasonality by product category (apparel, electronics, groceries).

Like-for-like in Hospitality and Leisure

Hotels, restaurants, and leisure venues use Like-for-like to compare performance of properties or locations that have been operating for a similar period. For hotels, metrics may include like-for-like room revenue, average daily rate (ADR), and occupancy, adjusted for any new hotel openings or closures in the portfolio. For restaurants, comparable items include same-store sales and comparable customer traffic trends, adjusted for changes in opening hours or service formats.

Like-for-like in E-commerce and Omnichannel

Online retailers face a different set of comparability challenges. Like-for-like still applies, but the base often includes digital stores and physical stores with consistent product availability. In omnichannel models, Like-for-like might be reported for online-only platforms and for stores that offer omnichannel pickup and fulfilment. Online promotions, search visibility, and algorithm-driven merchandising can influence periods differently, so some organisations report Like-for-like in a segmented fashion: web-only Like-for-like, store-based Like-for-like, and total group Like-for-like.

Benefits of Monitoring Like-for-like

There are several compelling reasons to track Like-for-like across a business portfolio.

• Provides a clear lens on core performance, excluding the noise from portfolio changes.
• Benchmarking: Enables apples-to-apples comparisons across stores, regions, or brands.
• Forecasting: Improves forecasting accuracy by focusing on recurring trends rather than one-off events.
• Investor communication: Supports credible narrative about growth drivers and efficiency improvements.

When Like-for-like trends strengthen, it can indicate improved product mix, better store execution, or more effective pricing strategies. Conversely, a decline in Like-for-like often signals deeper issues that require operational attention, such as stock availability, customer experience, or competitive pressure.

Common Pitfalls and How to Avoid Them

Like-for-like is powerful, but it can mislead if not used rigorously. Here are frequent pitfalls and practical ways to avoid them.

Non-comparable bases

Including stores that have undergone recent refurbishments or flagging stores that were temporarily closed can distort results. Maintain a clearly defined baseline of comparable stores and review periodically to ensure consistency.

Promotions and calendar effects

Heavy promotional activity or unusual calendars (such as a leap year or a promotional campaign spanning multiple periods) can distort comparisons. Consider reporting promotional elasticity separately or adjusting for discounting impact where possible.

Product mix and category shifts

A change in product mix may drive growth even if overall store performance is flat. Analysts should segment Like-for-like by product category to uncover underlying drivers and avoid conflating mix effects with volume growth.

Currency movements

Global businesses must decide whether to present Like-for-like in local currency or constant currency. Currency translation can obscure the true performance of local operations, so adding a constant currency series is often prudent.

Acquisitions and disposals

New acquisitions or disposals can complicate the base. Clear disclosure of which stores are included in Like-for-like and the timing of changes is essential for credibility.

Presenting Like-for-like Data to Stakeholders

Communicating Like-for-like effectively requires clarity, consistency, and context. Stakeholders expect straightforward charts, concise explanations, and a view of what is driving the results.

Best practices for reporting

• Define the scope: Which stores, what period, and how are exclusions applied?
• Present both absolute values and percentage changes to provide context.
• Offer a constant currency option and a local currency view where relevant.
• Disclose any calendar adjustments or promotional effects affecting comparability.
• Complement Like-for-like with related metrics such as total sales, footfall, average basket value, and conversion rates.

Visualisation tips

When constructing dashboards or slide decks, consider:

• Line charts showing Like-for-like over multiple periods to reveal trends.
• Bar charts comparing Like-for-like by region or store type for quick benchmarking.
• Supplementary annotations that explain anomalies (e.g., a major refurbishment or a natural disaster).

Practical Case Studies: Illustrative Scenarios

Case Study A: A Mid-Market Retailer

A mid-market retailer tracks Like-for-like growth across its 120 stores. In the latest quarter, 105 stores remained comparable to the previous year. The company reports a Like-for-like sales increase of 3.8%. By segment, apparel shows +5.2% Like-for-like while homeware sits at +1.0%. Management explains that the uplift in apparel stems from a refreshed brand and improved in-store experiences, while homeware faced supply constraints for some SKUs during the quarter. The report also notes that 15 stores were closed for refurbishment during the period, excluded from Like-for-like calculations.

Case Study B: A Hotel Chain

A hotel group discloses Like-for-like revenue per available room (RevPAR) across its properties, excluding new openings in the quarter. The chain reports a 4.5% Like-for-like RevPAR increase, with occupancy stable and ADR up by 3.0%. The commentary highlights that the uplift is driven by improved demand in urban locations and a renewed loyalty programme. Periods with calendar anomalies are adjusted so that the Like-for-like comparison remains meaningful for investors.

The Future of Like-for-like in Business Reporting

As businesses evolve and data capabilities expand, Like-for-like will continue to play a crucial role in performance storytelling. Several trends are shaping how organisations apply this metric:

• Granular segmentation: More detailed Like-for-like analyses by product category, channel, or region, enabling deeper insights into drivers of growth.
• Enhanced data quality: Cleaner data, better store-level analytics, and real-time dashboards enable more timely and accurate Like-for-like reporting.
• Automation and governance: Standardised definitions and automated reporting reduce manual errors and improve comparability across the group.
• Integrated KPI frameworks: Like-for-like is increasingly integrated with other KPIs (customer lifetime value, retention rates, net promoter score) to present a holistic view of business health.

Practical Steps to Implement Robust Like-for-like Reporting

If you’re looking to implement or refine Like-for-like reporting within your organisation, consider the following practical steps.

• Define the scope clearly: Document which stores, channels, and periods are included. Establish the rules for exclusions and adjustments upfront.
• Standardise currency treatment: Decide whether to report in local currency or constant currency, and apply consistently across periods and regions.
• Align with governance: Ensure the finance and operations teams agree on the methodology and the way changes (openings, closures, acquisitions) affect the base.
• Separate promotions from core performance: Consider a separate analysis that isolates the impact of promotions to avoid misinterpreting demand elasticity.
• Maintain documentation: Keep a running log of any methodological changes and the rationale behind them for auditability and future comparability.
• Communicate clearly: When presenting Like-for-like results, accompany the metric with contextual notes and a narrative explaining what is driving the trends.

Conclusion: Harnessing Like-for-like for Clarity and Growth

Like-for-like remains a cornerstone of business analysis, offering a disciplined view of core performance that is shielded from some of the distortions created by portfolio changes. By careful definition, consistent calculations, and transparent communication, organisations can use Like-for-like to diagnose issues, confirm improvements, and guide strategic decisions. Whether in bricks-and-mortar retail, hospitality, or the rapidly evolving world of e-commerce, Like-for-like provides a reliable compass for navigating growth, productivity, and future opportunities.