Co-op Case Study

Aufgabe

The Co-op have over 3,500 stores across the UK, and is the local choice for many. Understanding the primary catchment of stores is a key part of the Co-op being able to accurately forecast new store sales and understand potential cannibalisation.

The Co-op have a team of location planning experts who can create these primary catchments, but this takes valuable time. Using simple distance and market share rules doesn’t work that well for the Co-op; the catchments are too localised and affected by format, location type and competition.

Our challenge was to work with the Co-op team to find a way to automate catchments that reflected what the experts would draw.

Herangehensweise

• Calculate market shares using Co-op membership data, taking into account its limitations.
• Review the most effective geography to use avoiding small number issues while being as detailed as possible.
• Create a series of catchment outputs using different methods and review hundreds of catchments with the Co-op team
• Develop a novel algorithm
• Successfully identify ‘break points’ in penetrations and create natural shapes reflecting where the underlying member behaviour changes
• Create a composite distance / market share score and rule sets to calculate intuitive segregations for new stores