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Churn Analysis Research

Analyze customer churn patterns to identify causes and retention opportunities

Complexity: Complex | Duration: 30m+ | Category: Research/Intelligence

Tags: churn-analysis retention-research customer-analytics predictive-modeling SaaS-metrics

Workflow Diagram​

Steps​

Step 1: Churn definition​

Agent: business

intelligence-analyst - Define churn criteria (cancellation, inactivity, downgrade)

Step 2: Cohort analysis​

Agent: data

engineering - Analyze churn rates by cohort, segment, tenure

Step 3: Behavioral analysis​

Agent: data

engineering - Compare behavior of churned vs retained customers

Step 4: Usage patterns​

Agent: data

engineering - Identify usage patterns preceding churn (decline in activity, support tickets)

Step 5: Exit interviews​

Agent: research

agent - Conduct interviews with churned customers to understand reasons

Step 6: Survey analysis​

Agent: research

agent - Analyze cancellation survey feedback for themes

Step 7: Predictive modeling​

Agent: data

engineering - Build churn prediction model to identify at-risk customers

Step 8: Retention strategies​

Agent: business

intelligence-analyst - Recommend retention interventions and win-back campaigns

Step 9: Monitoring​

Agent: data

engineering - Set up churn monitoring dashboard with leading indicators

Usage​

To execute this workflow:

/workflow research/intelligence/churn-analysis-research.workflow

See other workflows in this category for related automation patterns.