Feature prioritization based on mock-purchase: A mobile case study

Abstract

As development teams’ resources are limited, selecting the right features is of utmost importance. Often, features are considered right if they result in increased business value at acceptable implementation cost. Predicting implementation cost and prioritizing features is well documented in literature. However, there has only been little work on the prediction of business value. This article presents an approach for feature proioritization that is based on mock-purchases. Considering several limitations, the approach allows key stakeholders to depict the real business value of a feature without having to implement it. Hence, the approach allows feature prioritization based on facts rather than on predictions. The approach was evaluated with a smartphone application. The business value of two features which were subjectively considered to be equally important was investigated. Moreover, the users were assigned different price categories for the features. Combined with live customer feedback, the approach allows us to identify an adequate pricing for the features. The study yielded insightful results as it showed which of the features incorporates higher revenue as well as how users react to the approach. It contributes to the body of knowledge in requirements engineering and software engineering as it enables practitioners to select features based on facts rather than predictions and to find ideal price points.