Feature and Subscription Relevance in Software-as-a-Service Pricing

Abstract

Softwares-as-a-Service (SaaS) are gaining prominence due to their availability, scalability, and cost-effectiveness. SaaS make benefits from subscriptions, which consist of pricing plans and add-ons, enabling user-tailored services, which we call subscription configurations. However, as modern SaaS subscription configuration possibilities rise over the thousands, the demand for tools to streamline pricing management becomes more urgent. How can an owner of a SaaS know the best-selling subscription? And how can they know why it may or may not be selling right? This proposal sheds light by providing a mathematical solution that enables understanding of the relevance of features and subscriptions based on the subscription price and percentage of adoption. The outputs are the Feature Relevance Score (FRS) and the Subscription Relevance Score (SRS). These metrics allow SaaS owners to comprehend the performance of the features and subscriptions of their product, aiding in the management of their product's pricing model.