Identification of products for campaigning with budget constraint

Technology helps producers to collect enormous amounts of customer-product interaction (CPI) data. From the collected CPI data, the importance of the customers and the products can be measured. This study focuses on finding the best number of products for the business for campaign selection based on customers’ liking and disliking of products and their frequency of purchases. Campaign selection is an essential process for marketing, and when the total budget of the campaign is fixed, identifying the optimal products for campaigning is challenging. This paper aims to identify the important existing customers and products and identify the optimal product combinations for campaign selection. We propose two algorithms to identify highly valuable customers and products and solve the complex optimization problem of identifying the optimal product combinations for campaign selection that maximize the business’s profits. We compare our proposed algorithms on real and synthetic datasets, and the results are presented.