Outlet Group Analysis (Retail Tracking Data)

Retail analytics using tracking data (retail audit/scan data) essentially involves filtering the data to form one or more outlet groups (refer to Exhibit 29.1). The groups may be defined based on the physical characteristics of the outlets (e.g. location, size, type of outlet, type of facilities etc.) or on the sale and distribution of products.

Outlet grouping serves the purpose of drilling into relevant data. If a particular retail issue is to be evaluated, the groups are configured so that they provide a deeper understand of that issue. For example:

• Handlers’ analysis: Outlets are filtered according to whether they stock a product, or any combination of products.
• Assortment analysis: E.g. outlets that stock 1 or 2 models of Sony TVs, outlets that stock 3 to 6 models, and outlets that stock more than 6 models.
• Brand overlap: E.g. outlets that only distribute Coca-Cola, outlets that only distribute Pepsi and outlets that distribute both Coca-Cola and Pepsi.
• Shelf space analysis: E.g. in the breakfast cereals category, outlets with less than 10% forward stock and outlets with more than 10% forward stock of health cereals.
• Pricing: Group stores according to the average price at which some product was sold. Or group according to comparative pricing, e.g. stores where Pantene shampoo is cheaper than Sunsilk, and stores where it is more expensive.
• Promotion: E.g. petrol stations that promoted RON 92 fuel and those that did not promote.
• Rate of sale: Group stores into heavy, medium and light on the basis of their rate of sales for a category.