Optimize your marketing campaigns by predicting customer propensity to purchase

Background

Our client, a subsidiary of a leading international health group, is the leading private health insurance company in Spain with more than 1.96 million customers. The company has four independent business units. The goal of the data science initiative was to combine information from three of these units (dental, insurance, and hospitals) in order to leverage the information for strategic initiatives.

Challenge

The client wanted to combine customer data from the three business units to segment customers who met a series of characteristics in order to effectively implement cross-selling and upselling campaigns.

Approach

Keyrus held meetings with the three business units in order to identify which customer parameters and characteristics were relevant to include in the target segmentation group. The target audience was defined as VIP customers, i.e. customers who had contracted certain high-value services. This information was combined with other variables to determine whether or not they would be included in the segment. Keyrus then created predictive statistical and business analytics models to predict the likeliness to contract certain services. With these insights, the marketing team could create targeted marketing campaigns in order to increase sales.

Key results

Increased sales through optimized marketing campaigns

Greater insights into the behavior of highest-value customers in order to personalize offerings

Increased customer lifetime value

Benefits

The client has a unified view of its customers in three of its business units. With a better understanding of high-value customer behavior, the company can optimize marketing campaigns, boost sales through cross-selling and up-selling actions, and personalize offerings.