Preference-Based Revenue Optimization for App-Based Lifestyle Membership Plans

Abstract

The demand for a product is rooted in the consumers’ needs and preferences. Therefore, a pricing optimization model will be more valid if the demand function is represented under this basic notion. A preference-based revenue optimization model for an app-based lifestyle membership program is developed and solved in this research. The model considers competitor products and cannibalization effect from products in other fare-class, where both are incorporated using a preference-based demand function. The demand function was derived through a randomized first choice simulation that converts individual utility values into personal choices based on the random parameter logit model. Cannibalizing products are considered as competing products in the simulation scenario. In the pricing optimization, two and three fare classes based on the membership period are considered. The corresponding pricing optimization problem is a mixed-integer nonlinear programming problem with a solution-dependent objective function. Using enumeration, the three-fare-class optimal prices of Rp420,000, Rp300,000, and Rp60,000 for 12-month, 6-month, and 1-month membership, respectively, are better than those of the two-fare-class. Under this policy, the estimated total revenue is Rp30.56 billion, 41.74% greater than that of the current condition.