$4.2M ARR recovered
Reducing SaaS churn 35% with AI health scoring
Early warning system identified at-risk customers 60-90 days before cancellation, recovering $4.2M in annual recurring revenue
Project Info:
Industry
B2B SaaS
Company Size
$50M ARR SaaS
Timeline
12 weeks
Investment
$145K
Challenge:
20% annual churn killing growth targets. Unable to identify at-risk customers until cancellation notice received. Retention team reactive instead of proactive.
Solution:
Customer health scoring system analyzing 50+ signals: usage patterns, support interactions, feature adoption, engagement metrics. Identified churn risk 60-90 days before cancellation.
Results:
35% reduction in customer churn (20% → 13% annual rate)
$4.2M recovered ARR in first year
6x improvement in retention efficiency
Net revenue retention: 92% → 108%
Technical approach:
Gradient boosting models with regular score updates.
Segment-specific models.
Salesforce integration for alerts.
A/B tested intervention strategies.
Key takeaway:
Behavioral signals (usage patterns) proved 3x more predictive than demographic data. Feedback loop from saved accounts improved model accuracy 15%.
