Analytics Skills
Turn your customer data into actionable insights with automated segmentation and predictive analytics.
Available Skills
RFM Segmentation
Automatically segment customers by Recency, Frequency, and Monetary value
Churn Prediction
Identify at-risk customers before they leave
CLV Calculation
Calculate and track Customer Lifetime Value
Cohort Analysis
Track customer behavior over time by acquisition cohort
Revenue Attribution
Attribute revenue to marketing channels and campaigns
Overview
Analytics skills process your customer data to surface insights:
- Automated segmentation - Group customers by behavior
- Predictive scoring - Anticipate future actions
- Lifetime value - Understand true customer worth
- Attribution - Know what’s driving results
RFM Segments
| Segment | Recency | Frequency | Monetary | Action |
|---|---|---|---|---|
| Champions | High | High | High | Reward & upsell |
| Loyal | Medium | High | High | Maintain engagement |
| Potential | High | Low | Low | Nurture to convert |
| At Risk | Low | High | High | Win-back campaign |
| Lost | Low | Low | Low | Re-engagement or sunset |
Key Metrics
| Metric | Description | Update Frequency |
|---|---|---|
| CLV | Predicted lifetime revenue | Weekly |
| Churn Score | Probability of churning | Daily |
| RFM Score | Combined behavioral score | Daily |
| NPS | Net Promoter Score | Per survey |
Getting Started
- Ensure order data is syncing
- Enable RFM Segmentation (runs automatically)
- Review segment distribution in dashboard
- Create targeted campaigns per segment
Tip
RFM segmentation needs at least 90 days of order history for accurate results.