Advanced data analytics for segmentation

Context and objectives

A major food and beverage company operates a three-level distribution network with hundreds of thousands of retailers.

The company has no direct access to consumers and very limited contact with retailers. The objective was to improve the allocation of marketing and sales resources by collecting and making sense of deep data on retailers and their end customers.

Outcome

Retailers were assigned to segments, and sales and marketing resources were allocated to the accounts with the greatest business potential.

Our approach

Step 1: design

• Design of segmentation criteria, including image and customer typology criteria

Step 2: build

• Automated API calls to several data sources, aggregation of structured and unstructured data per retailer, and deployment of a segmentation algorithm

Step 3: define

• Definition of the ambition for each segment, design of specific sales and marketing programmes, and reallocation of resources accordingly

Step 4: pilot

• Pilot in one state, then roll-out and industrialisation in more than 40 states