Customer Churn Predictor (In ideation)

The problem
Churn warning signs, like repeated issues and slow resolutions, are scattered across teams, so nobody sees the full picture until the customer has already left.

The idea
An early-warning system that brings these signals together and flags at-risk customers in time to act. The first data source is support ticket data, already captured consistently through my Teams-to-ClickUp automation.

Approach: Collect ticket data → find patterns that precede churn → score each account → alert the right team.

Why it matters: It moves the team from reacting to churn to anticipating it, and shows Product which issues hurt retention most.

Status: Ideation, with the data foundation in place. Next step is a first prototype.