Maximizing the Potential of Targeted Marketing: A General Framework for Customized Category Promotions in Retail
36 Pages Posted: 30 Jun 2019
Date Written: May 8, 2019
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 promotions. This problem has received little attention from academics despite the category-specific nature of more than half the targeted promotions at a leading German hypermarket chain. We, therefore, develop the first general framework for category selection in individual-level marketing based on segmenting customers in terms of churn, frequency, and loyalty. For the latter attribute, we propose a novel data-mining methodology that can distinguish between customers who shop at several retailers versus mostly at a single retailer. Using data from our partnering retailer, we propose using category-specific promotions for only half of its customers and demonstrate that promoting less frequently purchased products can substantially increase CLV. The personalized targeting strategy described here enables multi-category retailers to exploit the full potential of customized marketing by optimizing the trade-off between CLV considerations and short-term campaign profitability. Our analysis reveals that this strategy – as compared with the current strategy of our focal retailer – results in a nearly 41% higher CLV increase even as it reduces marketing costs.
Keywords: customized promotions, targeted marketing, category selection, data-mining
Suggested Citation: Suggested Citation