How to select the optimal bundling strategy for two products within a sales cycle

Purpose The most difficult problem in bundled sales is how to choose the two most suitable bundled products among a large number of sold products in the retail or online sales market. This article develops an optimal bundling strategy model for two products with demand uncertainty within a single sales cycle. Design/methodology/approach By introducing bundling purchasing intentions for the sale of two products together, a profit-maximizing model for bundled sales is established. It has been proven that there is always an optimal bundling quantity of two products in the retail market through our model. An algorithm is then designed to determine the optimal bundling strategy. Findings The numerical analysis results indicate that the algorithm for the optimal bundling strategy can yield the planned bundling quantities for the two products corresponding to the maximum expected profit, as well as the expected profit itself. This research addresses the theoretical problem of selecting the optimal bundling strategy for two products within a sales cycle, which holds significant guiding value for the study and practice of bundling sales strategies and a bundling strategy model for ordering bundled products for inventory management. Research limitations/implications (1) Participating Data Mining Techniques: Investigate how to obtain the appropriate value of bundling purchasing intentions under different large models or algorithms using data mining techniques. (2) Analyzing with different Probability Distributions: Examine the impact of different probability distributions on bundling strategies and optimal order quantities. (3) Introducing the influence of Online Advertisement: Explore the influence of different types of online advertising on bundling outcomes. (4) Constructing discount Bundling Pricing Models: Construct discount bundling pricing models to enhance research on bundling strategies when implementing discounted sales for bundled products. Practical implications This article proposes a strategy selection methodology for optimal planned bundling quantity, whereas existing theoretical research on product bundling has primarily concentrated on the domain of economy and psychology. And in implementing intelligent decision-making, it has been proven that there always exists an optimal bundling strategy. The introduction of bundling purchasing intentions reduces the difficulty of solving the two product bundling models. Social implications E-retail industry has rich and sufficient historical sales data for implementing intelligent decision-making. Merchants widely adopt product bundling strategies to increase sales and profits. Based on the periodic newsboy model, this study introduces the bundling purchasing intentions, constructs the optimal bundling strategy model for the associated products, and investigates the expressions for their optimal bundling strategies and expected profits. These theoretical researches contribute practical value for explaining the bundling strategy of e-commerce. Originality/value The optimal bundling model of two products for sales is proposed. The bundling purchasing intentions reduce the difficulty of solving the bundling model. Prove that there always exists an optimal bundling strategy for two products. An algorithm is designed to determine the optimal bundling strategy. Determine whether two products are suitable for bundling based on the bundling purchasing intentions.