Same-store sales

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Same-store sales is a business term which refers to the difference in revenue generated by a retail chain's existing outlets over a certain period (often a fiscal quarter or a particular shopping season), compared to an identical period in the past, usually in the previous year.[1] By comparing sales data from existing outlets (that is, by excluding new outlets or outlets which have since closed), the comparison is like-to-like, and avoids comparing data that are fundamentally incomparable. This financial and operational metric is expressed as a percentage.

Same-store sales are also known as comparable store sales, identical store sales or like-store sales.

Same-store sales are widely reported by publicly owned retail chains as a key element of their operational results. For chains that are growing quickly by opening new outlets, same store sales figures allow analysts to differentiate between revenue growth that comes from new stores, and growth from improved operations at existing outlets.

By comparing how well existing outlets perform during a particular week compared to that same week in the previous year, business trends can be measured more accurately. Seasonal and geographical variations are removed from the measurement: instead of collecting an average over spans of time and location, annual changes in performance are revealed.

Growing same store sales can be explained by a number of reasons, including: marketshare gains in a retailer's trade areas; higher average purchases and/or more frequent customer visits; and successfully cross-selling into a broader product range or upselling to more expensive ones.

Sustained negative same store sales is a sure telltale that a retailer is in trouble. As large retail chains expand geographically they eventually run out of prime locations and often end up cannibalizing their existing stores to some extent, which leads to a relative decline in this metric. A rapid expansion in the number of stores followed a few years later by weak same store sales numbers shows (in hindsight) that the store additions might have been careless or rushed.

Specific store sales can also be compared. For example, a retail chain's finding that its same store sales at location A for the week-long shopping rush before Christmas are greater than those at location B is a useful piece of data. That data would have been less useful if only chain-wide sales for that week were known (with all stores averaged together), or if only year-long sales were known for that particular store. This makes same store sales a useful metric not only for external assessments of a retailer's performance, but also for internal benchmarking guiding store opening, remodeling and closing decisions.


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