Optimal Software Feature-Limited Freemium Model Design: A New Consumer Learning Theoretical Framework

Abstract

The software industry is increasingly adopting a feature-limited freemium business model that combines “free” and “premium” contents in one product, to sell its products. How to determine the optimal product quality differences between the free and premium versions of software is a central business problem facing many software vendors. In this paper, we study the optimal feature-limited freemium software strategy design, as well as the associated pricing strategies based on consumer learning and network externality effects. We propose a new consumer learning framework induced by cross-module synergies that contains both direct and indirect learning processes. By employing a two-stage mathematical theoretical model and a numerical analysis method, we gained some insights regarding the feature-limited free trial strategy design and associated pricing strategies while considering the associated trade-off between the benefits and costs of the free trial strategy. In our modeling and numerical results, consumers’ prior beliefs about the quality of premium content before the free trial, network effect intensity, and indirect learning intensity were found to be three conditions that need to be studied to examine software vendors’ management decisions. For the software industry, the quality difference between free and premium functionality or the service and price strategy for a feature-limited free trial model can be designed while considering these factors, which will provide some useful guidelines for the industry.