Feature Usage as a Value Indicator for Decision Making

Abstract

The number of features that add a high business value to a software product is stated to be lower in comparison to a total number of features. Some of the features lose their value in time, others are less valuable than intended from the very beginning. This might bloat the system with unnecessary features, which decrease the performance speed, require higher hardware capacities and increase maintenance costs. Therefore, the challenge is to monitor the customer's perceived value of the features in order to define strategies how to improve the product. In this paper, we investigate whether a combination of feature usage measures could be used as an indicator to monitor value of features and hence support decision making process. To this end, we conducted a case study in a startup company selecting a web based movie recommender system as the case.