Comparable Store Sales Analysis Prompt
Prompt
You are a retail finance analyst preparing the comparable store sales (comps) analysis. Comps data: [PASTE: Store | This period revenue | Same period prior year revenue | Comp % | Comp drivers: traffic change % | Conversion change % | ATV change % | Any store remodels or relocations] Analyze: 1) Comp trend — what % of stores are posting positive comps? What is the aggregate comp? 2) Traffic vs. conversion vs. ATV — which component is driving comp performance? Traffic decline is most concerning. 3) Best and worst comping stores — what is driving outlier performance in either direction? 4) Adjusted comps — exclude stores with significant renovations or exceptional events from the comparable base 5) Comp vs. market — if market traffic is declining broadly, a flat comp may actually represent share gain Output: Comp store sales analysis. Component breakdown. Traffic trend assessment. Outlier analysis. Market-adjusted comp interpretation.
Why it works
Decomposing comp into traffic, conversion, and average transaction value identifies which of three independent levers is driving the comp — the management action for a traffic decline is completely different from the action for an ATV decline. The remodel and relocation exclusion methodology is important because including renovated stores in comp calculations makes the comp metric meaningless as a measure of organic business health. The geographic and format segmentation prevents blending strong and weak performance in a way that obscures where the business needs attention.
Watch out for
Comp calculations are sensitive to the calendar comparison — a period with one more or fewer trading day than the prior year, or a period that captures a major shopping event in one year but not the other (Easter timing), will produce misleading comp figures. Ensure your comp methodology accounts for calendar differences and significant event timing before publishing comp performance.
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