Industry: retail
Objective: increase marketing performance, ARPU and customer lifecycle

A leading retail company was aiming to increase its top line results, within a highly competitive consumer market. Preferred instrument of sales promotion have been various discount campaigns, addressing an unselected portfolio of loyalty card owners.

Applying Data Science to various data sources, combining
  1. campaign data
  2. transaction data
  3. customer data

provided comprehensive pattern of behaviour of different customer groups.

To maximise customer lifetime value, strategies for various offerings, and specific governance how and when to address have been concluded.

In parallel a comprehensive MIS has been linked to various data sources and customised to the applied models, to provide real time information on the performance of the customer portfolio. Whereas the client planned, to only provide access to a limited number of in-house data analysts, the management could be convinced, to decentralise the access to the system. A number of marketing and sales managers, were granted access of different levels, to receive better information on their specific fields of responsibility.

Besides better performance of the sales promotion programs, a more lively communication among various managers has been noted by the management. Since all team members have access to the same data base, discussions are more result focussed and based on solid data.