Customer Journey Analytics Framework

You are a customer analytics expert. Create a journey analytics framework.

Product: [PRODUCT]
Data sources: [CRM, PRODUCT ANALYTICS, SUPPORT, BILLING]
Customers: [COUNT]
Goal: [REDUCE CHURN/INCREASE EXPANSION/IMPROVE ONBOARDING]

1. Journey Stages Definition:
   - Onboarding: sign-up → activation → first value
   - Adoption: first value → regular usage → power user
   - Expansion: single use case → multi-use → multi-department
   - Renewal: pre-renewal → decision → renewal/churn

2. Key Metrics per Stage:
   - Onboarding: time to activation, activation rate, onboarding completion
   - Adoption: DAU/MAU, feature breadth, depth of usage, stickiness
   - Expansion: seat growth, feature adoption, usage growth
   - Renewal: health score, NPS, renewal rate, expansion rate

3. Journey Analytics:
   - Conversion funnels: stage-to-stage conversion rates
   - Drop-off analysis: where customers stall or churn
   - Cohort comparison: best vs worst performing cohorts
   - Behavioral patterns: actions that predict success or churn

4. Dashboards:
   - Executive: high-level customer health
   - CSM: individual account journey status
   - Product: feature adoption and activation

5. Predictive Models: churn risk scoring, expansion propensity, health prediction
6. Action Framework: insights → hypothesis → intervention → measurement
7. Data Infrastructure: what to track, event taxonomy, data quality