Make decisions based on data, not gut feel, with predictive models built on your transaction history
Demand forecasting, customer lifetime value modeling, churn prediction, and pricing optimization built on your actual data.
The Problem
Most ecommerce teams make inventory, pricing, and retention decisions based on intuition or backward looking reports. By the time the data is available, the opportunity has passed. Generic analytics tools provide dashboards but not actionable predictions. The result is overstock on slow products, understock on winners, and retention campaigns that arrive too late.
Our Approach
We build predictive models on your actual transaction data, not generic benchmarks. That means demand forecasts calibrated to your seasonality, customer lifetime value models that reflect your specific buying patterns, churn predictions that trigger interventions at the right moment, and pricing intelligence that accounts for your margin structure and competitive position.
What is Included
- Demand forecasting calibrated to your product catalog and seasonality
- Customer lifetime value modeling with segment analysis
- Churn prediction with automated retention triggers
- Pricing optimization based on margin, demand, and competitive data
- Executive reporting dashboard with actionable recommendations
- Monthly model refinement based on new transaction data
Typical Timeline
4 to 6 weeks from kickoff to production deployment
Starting Investment
Ready to make better decisions with predictive intelligence?
Tell us about your data sources and decision challenges. We will scope the analytics build.