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Case Studies

Designing Cross-Sell strategy

Business Need:

Our client, a leading financial services firm, had been registering robust new account growth. Since the cross sell volume was rather low, the business wanted to focus on their large customer base for cross selling a range of financial products.

Our Solution:

Comprised of a decisioning engine (consisting of product wise cross sell propensity models) which would predict the likely cross sell propensity of various products at a customer level. A detailed campaign plan was designed using the decisioning engine:
  • Since the availability of information in the raw data was limited, we created a ‘surrogate data’ set of a comparable portfolio using statistical techniques, a survey and business logic.
  • Thereafter, we built product wise cross sell propensity models with the help of the surrogate data.
  • We then grouped the customers on the basis of their profiles to identify commonality of traits. For these grouping, clustering techniques was used. The characteristics of these clusters were assigned based on the majority of members by cluster.
  • We matched the results of the two stages to confirm the outputs.


We focused on the key issues viz. who should be targeted and with what product(s) while dealing with the challenge that the data captured by the client only consisted of customer coordinates and basic demographic information.


The cross sell decisioning model formed the logical basis on which the entire customer base was segmented. Based on the segmentation, the cross sell strategy and a pilot campaign was developed which the client used successfully.