Renewal & Expansion Operations
Build AI-native renewal systems that detect churn signals early, automate renewal timelines, and surface expansion opportunities before customers start shopping alternatives. Based on the renewal playbook framework.
Also included with Pro membership — $299/mo
Course Modules
3 modules, 8 lessons
Why Renewals Fail
Understand the structural problems that keep renewal rates stuck in the mid-80s: data decay, misleading health scores, and feedback cycles that are too slow to catch risk.
3 lessons
Building AI-Native Renewal Systems
Build the three core AI-native capabilities that transform renewal operations: usage decline detection, stakeholder turnover tracking, and expansion signal qualification.
3 lessons
Operating the Renewal Machine
Learn the implementation sequence that ensures each capability builds on the previous one, and the metric framework that drives continuous improvement in retention and expansion.
2 lessons
What You'll Learn
- Decompose your retention number to reveal the true cost of your current renewal process
- Build an outcome-based health scoring model validated against your historical churn data
- Implement automated detection for the three churn signals that predict failure 6-8 weeks early
- Design triggered playbooks that respond to risk signals without depending on CSM attention
- Build an expansion signal detection system that converts at 3x manual identification rates
- Operate a three-metric framework (GRR, NRR, expansion rate) that drives continuous improvement
Downloadable Resources
PDF worksheets and templates included with this course
Renewal & Expansion Operations — Complete Worksheet
PDF · ~420 KB
Included in worksheet