B2C Healthcare

B2C Healthcare

Identifying Customer Segments with Highest Potential value

The client already had comprehensive RFM analytics, and overall market penetration information. However, this was at the aggregate level and no attempt had been made to identify high potential segments based on current sales data. With a fixed margin and steady purchase frequency, the requirement was to define the largest segments with affinity to the product.

The customer records although large in number were not attribute rich, and several overlays of census and survey data were required to develop a fuller picture of the customers. To zero-in on the most active group, a combination of K-means and hierarchical clustering techniques were used to partition customer attributes based on non-consumptive metrics. The results were definitive: seniors, regardless of affluence or activity were the dominant purchasers. Also, Hispanic families were a significant group purchasing the products. Both segments were surprising: while seniors were not big spenders, they made up for it in numbers, and the latter was a known segment, but the large associated value of this segment was surprising to the client.

RESULT: The client had numbers to support investment in new initiatives for these segments and details to tailor their marketing communication with new and existing customers. Moreover, they knew who were not purchasing their products. The African American segment had been a priority for the client, but the analysis identified no significant revenue. Thus the client had to re-examine their strategies and prioritize investment in the customer experience initiatives by segment.