Customer lifetime value modeling
CLTV Prediction
A predictive model for Customer Lifetime Value that forecasts long-term revenue per segment by combining historical purchase patterns with behavioural signals.
- Engagement
- Applied AI delivery
- System type
- Customer lifetime value modeling
- Primary outcome
- Operational leverage
Challenge
The existing operating model made customer lifetime value modeling slow to inspect, difficult to scale and dependent on manual coordination.
Response
Probabilistic revenue forecasting (BG/NBD, Gamma-Gamma). Customer segmentation into value tiers for differentiated treatment
Result
Improves marketing ROI by aligning spend with customer value — investing in high-LTV segments and reducing waste on low-return cohorts.
System architecture
From signal to controlled action.
01
Probabilistic revenue forecasting (BG/NBD, Gamma-Gamma)
02
Customer segmentation into value tiers for differentiated treatment
Business value
The system changes the operating baseline.
Improves marketing ROI by aligning spend with customer value — investing in high-LTV segments and reducing waste on low-return cohorts.
Next case: Czech Radio Analytics