Population: existing, new, closed
Eligibility: tenure and valid days
Events: renovation, relocation, closure
Metrics: sales, traffic, conversion, basket
Result: comparable growth + net contribution
Total growth is not store improvement
New stores raise totals while old stores may decline; closing weak stores can lift averages. Comparable stores show change on a stable base.
Define tenure, operating-day minimum, treatment of renovations and moves, and comparison period.
Historical store state is required
Version opening, closure, suspension, renovation, relocation, format, and region. Keep a daily trading calendar with hours and exception reasons.
Join sales by store and date to reconstruct each period’s population.
Decompose growth
Show comparable change, new-store contribution, closure impact, and adjustments. Within comparable stores, analyze traffic, conversion, basket, mix, and promotion.
Define tax, refunds, online attribution, and cross-store orders.
Handle calendar effects
Holiday timing, weekdays, weather, and campaign dates affect comparison. Align weeks, normalize trading days, or mark events with disclosed methods.
Adjustments aid comparison but do not prove causality.
Accept reproducible population
Sample new, closed, renovated, suspended, and missing stores and list every included location with reason.
BI0 can organize store and sales analysis; historical dimensions, calendars, and attribution need project verification.
Public references
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