Retail · Analytics ·

Store performance & footfall

Compare revenue, average basket and incoming footfall by store and catchment area.

Illustrative preview of the SAP Analytics Cloud dashboard Store performance & footfall for the Retail industry: metrics Revenue, Average basket, Store footfall, Conversion rate, analyzed by Store, Region, Format.
Illustrative preview of a possible rendering in SAC. Brand colors and structure; synthetic figures.

KPIs included

  • Revenue
  • Average basket
  • Store footfall
  • Conversion rate

Analysis dimensions

  • Store
  • Region
  • Format

About this template

Compare revenue, average basket and incoming footfall by store and catchment area. Designed for teams in the Retail industry, the model pre-wires 4 key metrics — including Revenue and Average basket — analyzable across 3 analysis axes (Store, Region, Format). You start from an already-bounded base (units, aggregations and business labels defined) rather than a blank sheet.

After downloading, import Store performance & footfall into SAC Modeler (Files → New Model → Import data from a file), map the 3 dimensions and 4 measures, then build your Story. The provided dataset contains 720 to 960 rows with realistic values for the Retail industry, available as .xlsx (multi-sheet workbook), .csv (flat table) and .package (ZIP bundle with model.json, data.csv and README).

FAQ

What is the "Store performance & footfall" template for?

It provides a ready-to-use SAC structure to drive analytics in the Retail industry. The standard business KPIs and dimensions are already defined, saving you the modeling phase.

Which KPIs are included?

The template includes 4 metrics: Revenue, Average basket, Store footfall, Conversion rate. Each is computed across the dimensions Store, Region, Format.

How do I import it into SAP Analytics Cloud?

Download the .csv or .xlsx format, then in SAC: Files → New Model → Import data from a file. Map the columns (Dimensions then Measures), validate the types and build your Story. Allow 5 to 10 minutes for an operational model.