I feel like revenue simulators are the most underrated pricing research method -- you get insights similar to A/B testing but without needing deep pockets and a huge customer base to test against. More of the teams I work with have been asking to run simulator projects recently, for stuff like introducing a new pricing plan, optimizing their recommendation engine, launching optional add-ons, etc. Especially with so much pricing experimentation going on around AI feature releases, it feels like revenue simulators are kinda having their moment right now. I put together a detailed example (with plenty of GIFs and screenshots) showing how a revenue simulator works, how you set up a study like this, and what kind of outcomes you can expect to get it: https://fullstackresearcher.substack.com/p/how-not-to-price-your-new-ai-feature

Back with another question for the pricing experts! Chatting with a pricing leader who's looking to create a clear framework for when something should be a standalone product vs. an Add-On for an existing product. Curious how others have thought about this? Would love to see any frameworks or hear any anecdotes from past experiences.