CUSTOMER & REVENUE ANALYTICS
Your best customers are leaving. You just don't know it yet.
By the time a customer stops ordering, they decided to leave 60 to 90 days ago. The signals were always there — declining basket size, shrinking category mix, shift to promo-only buying. We build the models that catch them early and give your retention team the list that matters.
FEATURED BOX
The €21.5M case teaser
A European subscription retailer with approximately €340M in annual revenue and 1.2 million active subscribers had a churn problem they could not see clearly until it had already happened.
The four capability blocks
Churn Prediction & Retention
90-day-ahead churn probability scores. Intervention matrix mapping customer value × churn risk to action type. Post-intervention attribution.
Customer Lifetime Value (CLV)
Probabilistic CLV modeling by cohort, channel, category. Acquisition payback analysis. Retention multiplier simulations.
Segmentation & Targeting
Behavioral segmentation. Next-best-action recommendations. Cross-sell/up-sell propensity modeling. A/B-ready campaign audiences.
Commercial Pipeline Analytics
Win/loss analytics. Pipeline health scoring. Deal velocity tracking. Rep effectiveness models.
How much revenue are you losing to silent churn?
Book a 30-minute call — bring 2–3 customer examples and we’ll tell you if (and when) our model would have caught them.