The SaaS paradigm has popularized the usage of pricings, allowing providers to offer a wide range of subscription possibilities. This creates a vast configuration space for customers, enabling them to choose the features, limits and guarantees that best suit their needs. Regardless of the reasons, changes in pricings are frequent, and are increasing their complexity. Therefore, for those responsible for the development and operation of SaaS, it would be ideal to minimize the time required to transfer changes in SaaS pricing to the software and underlying infrastructure, without compromising quality and reliability. We call this pricing-driven self-adaptation, and this work explores the extent of industry support for it. First, after analyzing 240 pricings from 37 different SaaS over seven years, we reveal a trend of exponentially increasing complexity, mainly driven by a sustained increase in the number of add-ons. Second, acknowledging feature toggling as a promising technique for enabling pricing-driven self-adaptation, we evaluate 18 existing solutions to assess their suitability. However, results reveal a gap between their capabilities and the requirements imposed by the growing complexity of pricings. In light of these results, establishing a standard for pricing serialization and advancing automation in pricing-driven self-adaptation emerge as key steps toward reducing the time-to-market of SaaS pricing updates.