Retail · Analytics ·

Loyalty program

Manage your member base: acquisition, purchase frequency and the basket gap between members and non-members.

Illustrative preview of the SAP Analytics Cloud dashboard Loyalty program for the Retail industry: metrics Enrollment rate, Repurchase rate, Member vs non-member basket, Points redeemed, analyzed by Loyalty segment, Store, Category.
Illustrative preview of a possible rendering in SAC. Brand colors and structure; synthetic figures.

KPIs included

  • Enrollment rate
  • Repurchase rate
  • Member vs non-member basket
  • Points redeemed

Analysis dimensions

  • Loyalty segment
  • Store
  • Category

About this template

Manage your member base: acquisition, purchase frequency and the basket gap between members and non-members. Designed for teams in the Retail industry, the model pre-wires 4 key metrics — including Enrollment rate and Repurchase rate — analyzable across 3 analysis axes (Loyalty segment, Store, Category). You start from an already-bounded base (units, aggregations and business labels defined) rather than a blank sheet.

After downloading, import Loyalty program 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 "Loyalty program" 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: Enrollment rate, Repurchase rate, Member vs non-member basket, Points redeemed. Each is computed across the dimensions Loyalty segment, Store, Category.

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.