DATA SCIENCE | SaaS | U.S.

Churn Risk Model Created From Product Usage Data

A SaaS company needed to identify churn risk earlier than renewal month. We built a churn model using product usage, support activity, account age, plan type, login behavior, and prior renewal history to surface accounts needing proactive attention.

Measured outcomes

82% Churn-risk precision
11 Risk signals modeled
28% Earlier intervention window

Implementation summary

Render Analytics connected the relevant systems, data signals, workflows and reporting logic so the team could make decisions from cleaner evidence and focus on measurable outcomes.