UC-130
Renewal Radar - Churn Early Warning
Scores every school on churn risk with a reason code and drops the next-best action into the consultant's queue.
6-10Build Duration
25-50xIndicative ROI
The Challenge
Around 427k students are lost each year (~EUR 26M) and consultants learn a school is at risk only when the renewal call goes badly. Usage decay and payment signals sit unread.
How It Works
- Ingests usage decay (e-stela), assessment participation (Pleno) and payment data (Pegasus).
- ML scores churn risk per school with reason codes; GenAI drafts the renewal brief.
- Drops the next-best action into the consultant's Dynamics queue inside 14 days.
What It Removes
- Churn discovered at the renewal conversation
- Usage-decay signals sitting unread
- Retention effort spread evenly, not by risk
Input Data Requirementse-stela usage logs, Pleno assessment participation, Pegasus payment behaviour, renewal history
Output FormatChurn-risk scores with reasons, GenAI renewal briefs, next-best-action queue
“Every retention point protects roughly EUR 2.2M a year - and we now see risk months early.”