Developing a data-driven customer loyalty strategy to improve customer retention

Posted by | Fuld & Company

Challenge

The client wanted to drive retention among its ‘loyalty’ customer base and increase the revenue generated from this segment, without causing a significant increase in promotion and discount costs. It wanted to develop hyper-personalized targeting campaigns to achieve this.

Solution

We leveraged its data analytics capabilities to come-up with the optimum solution:

• All sources of the client’s ‘loyalty’ data was integrated into a single source of truth
• Once the single source of truth was built, micro-segments of the ‘loyalty’ base were created and predictive models developed to identify the early indicators of passive churn
• With the micro-segments in place, targeted marketing campaigns were designed for each of them, in order to boost customer engagement
• These marketing campaigns were enhanced using Neuromarketing concepts to increase success rates, including:
  • Goal gradient hypothesis
  • Pain at loss of privilege

Impact

This hyper-personalized, targeted approach to client segmentation resulted in the client achieving:

Incremental revenue from targeted customers of up to 15%
A reduction in engagement inactivity of up to 8%

Tags: Customer Segementation, Data, Data analytics