Knowledge-based approach to improving micromarketing decisions in a data-challenged environment

With the growing popularity of micromarketing strategies, more companies are tailoring their marketing efforts to meet individual consumer need based on analysis of consumer-level data. However, there are two major obstacles in the way to effective micromarketing strategies: (1) data limitation at the consumer-level making it difficult to construct robust and accurate promotional response function and (2) misplaced usage of a resource allocation approach effective in a data-rich environment to data-challenged environment. These obstacles lead to suboptimal marketing resource allocation decisions.This paper presents a knowledge-based approach specifically designed for effectively allocating marketing resources in the micromarketing environment. A team of domain experts provide knowledge in refining and imputing data to overcome data limitation issues, as well as identifying consumer-level constraints to strengthen the integer programming model’s performance.Results indicate that this approach is transparent to all levels of management, adaptable to changes in environment, and easy to implement. In addition, there is tremendous potential for improving not only profitability but also growing the company’s intellectual capital. When this approach is applied to a random sales territory, it outperforms the traditional method by more than 19% in profit.