A Customer Segmentation Framework for Targeted Category Coupons in Retail
37 Pages Posted: 30 Jun 2019 Last revised: 26 May 2020
Date Written: May 25, 2020
It is customary for short-term measures to be used for designing customized marketing campaigns and evaluating their success. We consider the integration of customer lifetime value (CLV) thinking into the category selection problem for targeted coupons. This category selection problem entails two important considerations: Should the coupon be designed category-specific or not, and, if yes, should short-term or long-term objectives govern the category choice? We are the first scholars to address these questions by developing a data-driven customer segmentation framework based on the dimension of churn, frequency, and loyalty. We base our framework purely on transactional data available to every retailer and combine statistical tests and k-centroid clustering to allocate each customer to a (non-)category-specific targeting strategy. The personalized targeting strategy based on this framework enables multi-category retailers to exploit the full potential of customized marketing by optimizing the trade-off between short-term and CLV considerations. Our analysis reveals that this strategy – as compared with the common strategy in retail practice – can result in a significantly higher CLV even as it reduces wasteful marketing costs.
Keywords: customized coupons, targeted marketing, category selection, clustering
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