A 20% price hike costs nothing to model. Costs a quarter of revenue to model wrong.
By the time a price test reads cleanly, you've spent the quarter — and learned only that something happened. You don't know which segment churned, which one would have paid more, and what they were saying.
Drop in your current ICP, plan structure, and the proposed change.
Presume builds a weighted persona library that mirrors your cohort distribution.
Each persona reacts to the change in real-time — keep, churn, upgrade, downgrade — with their reasoning.
The synthesizer rolls up to a sentiment distribution + revenue forecast with confidence intervals.
Drop something like this into Presume:
See which segments stay, which churn, and which would have paid more — before you push the change.