Optimising allocation of marketing resources among offline channel retailers: A bi-clustering-based model

Abstract

Existing research on optimising marketing resource allocation focuses mainly on the customer rather than the retailer level. However, retailers play an important role in marketing channels, and optimising retailer-level marketing resource allocation poses important decision-making challenges. In this study, we proposed a retailer-level offline marketing resource-optimising allocation model based on retailer segmentation. The model consists of two stages. In the first stage, we built a retailer segmentation index system and introduced a bi-clustering algorithm to segment retailers that can cluster samples and features simultaneously. In the second stage, we proposed a new measurement for the rate of return on the utility of marketing resources and then leveraged the mean–variance model to find optimal marketing resource allocation plans. An empirical study of a famous Chinese alcoholic beverage company demonstrated that the proposed model outperformed four baseline models.