Production-Grade Data Science & Predictive Modelling
Turning raw data into automated, profitable actions — predictive models deployed straight into production environments to influence customer behaviour and drive top-line growth.
The Project
Many organisations have data scientists producing notebooks that never make it past slideware. We built and deployed predictive models directly into production environments, integrated with the data warehouse so they trigger real-time business actions: retargeting, cross-sell offers, and proactive retention.
The focus is always commercial: every model has a measurable revenue impact, a clear owner, and a feedback loop so it keeps improving once it's live.
The Tooling
Predictive Algorithms
Cross-sell, churn, LTV, propensity, and basket-abandonment models tuned to live business data.
Real-Time Triggers
Models integrated with the data warehouse to trigger marketing, retention, and CX actions automatically.
Monitoring & Drift
Production monitoring catches model drift early so performance doesn't silently degrade.
Business Benefits
Revenue Creation
Automated retargeting for abandoned baskets and high-probability cross-sell triggers drive immediate top-line growth — every prediction is wired to an action.
Cost Cutting
Marketing spend optimised by focusing resources on the customers with the highest predicted Lifetime Value (LTV), instead of broad-brush campaigns.
Risk Mitigation
Models predict churn and customer dissatisfaction before they happen, enabling proactive retention strategies that protect the most valuable accounts.
Take a model out of the notebook
We'll help you ship predictive models into production where they can actually move the numbers.
Productionise a predictive model