Store comparison
Net sales and gross margin by store and period. Like-for-like rules should address new stores, closures and comparable trading days.
Industry solution · Written delivery
Retail & multi-store businesses analytics
Compare sales, product mix, stock and store performance with consistent reporting rules.
Check My Data — FreeBusiness areas for this industry
Explore the relevant analytics areas
These are applicable areas to consider. Your agreed question and available data determine which ones are included in a project.
Need a different combination? Custom Analytics can be scoped around your requirements.
Operational decisions
See which stores and products contribute to the result
A strong sales week can hide discounting, returns or an uneven product mix. A retail view compares net sales with costs and stock exposure so the result can be read in context.
Start with point-of-sale exports, item identifiers and store codes. We check reporting dates, return handling and currency before presenting store rankings or period comparisons. A new store or a store with a different opening schedule should not automatically be treated as like-for-like.
The sales example illustrates the combination of revenue, margin and detailed contributions. It shows synthetic data, not measured performance from a retail customer.
Useful questions and measures
Product mix
Category and item contribution, including discounts and returns where the source supports them. Revenue contribution and profitability are different measures.
Stock review
Stock cover, low-stock exceptions and valuation. Actual balances and movement history are needed; POS totals alone do not establish current availability.
Interpretation and limits
Balance availability with stock exposure
Stock value tells you how much capital is held in inventory, while stock cover relates availability to usage. Both are useful, but neither should be read without seasonality, product range and replenishment context.
A focused review can identify items below agreed reorder points and categories with unusually high cover. It creates a review list for the business rather than automatically making replenishment decisions.
Customer behaviour can be added where stable identifiers and an appropriate data basis are available. Aggregated store and product reporting is often a practical first step without personal customer records.
Useful starting data
- POS or invoice lines with dates, store codes, item IDs and net amounts
- Product costs and category mapping for gross-margin questions
- Stock balances or movements and an agreed store hierarchy
For the Fit Check, describe the columns, approximate volume and time period. Do not send production credentials or personal records.
A focused first delivery
Choose one decision, one reporting period and an agreed set of sources. Receive the scoped dashboard, written observations, source assumptions and a documented handover.
The Fit Check identifies whether the data is suitable and recommends a fixed next step. Project price, exclusions, delivery environment and timing are confirmed in writing before work begins.
View the existing fixed-price packagesBefore you begin
Can we start with a single store?
Yes. A scoped first project can focus on one store or product category, then extend once the export and definitions are reliable.
Are all store rankings like-for-like?
No. Opening dates, trading days and assortment differences can change the interpretation. Comparable-store rules must be defined explicitly.
Example project scope
A focused first project: category margin and store comparison
Choose an agreed group of comparable stores and one reporting period. We confirm net amounts, returns and cost coverage, then review product contribution before presenting an overall store comparison.
A finance extension can add accepted expenses and receivables. The adjacent report is a general synthetic example; its operating-profit figures do not belong to the store scenario.
The final scope specifies the question, accepted sources, excluded calculations and the output to be delivered. Any additional view is an agreed extension rather than an implied inclusion in every package.
Start with one business question
Start with your question and a description of your data. We confirm data fit and scope in writing.