Like-for-like (LFL) sales are an important metric used by business owners and retailers when evaluating the performance of their stores or products. This metric allows companies to compare sales numbers between similar stores or products over a specific period of time, effectively isolating no-comparable outliers that could distort the results. This helps to give an accurate picture of how a store or product is performing, and shapes the foundations of a successful long-term goals-driven strategy.

For example, two stores may each have reported sales of $1.2 million in a given quarter. However, Store A may be a newly opened store, while Store B has been open for some time, and the total sales of each store could include outliers—such as a one-time purchase at Store A—that make the numbers less useful for comparison. To get a better understanding of whether the company’s strategy is working, like-for-like sales can be used to compare the two stores. This means comparing sales for the same period of time at each store stripped of exceptional items. If Store A was a newly opened store and Store B had been open for some time, their like-for-like sales comparison can give the company a better picture of the effectiveness of strategies across stores.

LFL sales numbers can provide insights into the success or failure of a company’s strategies. Comparing the like-for-like sales numbers over time gives insight into the factors that are contributing to a company’s growth or decline. For example, a decrease in like-for-like sales numbers between two periods of time might indicate that the company is having difficulty achieving its goals, while an increase in LFL sales could indicate improved marketing efforts and product offerings.

Using a comprehensive sales analysis, companies can isolate the many factors that contribute to an increase or decrease in sales. Factors such as store location, seasonality, promotions, discounts, and other sales tactics may all be contributing to a poor or successful sales performance. The analysis can provide key insights about a store’s strategy and how it can be improved. For example, if sales drop off during certain times of the day or peak during others, the company can adjust staffing or promotions to better accommodate the customers.

By utilizing like-for-like sales numbers, companies are better positioned to improve their store performance and profitability. Companies can improve like-for-like sales by offering promotions or sales and using customer data to gain important insights. Additionally, investments in marketing campaigns and improving customer service can help create loyalty and attract new customers. Finally, utilizing analytics to track sales and embrace new technologies can help a business make informed decisions and create strategies to maximize sales.