Models that answer the questions your business is asking
We have spent more than a decade turning statistical learning into business decisions for Fortune 500 clients. Every engagement starts from the decision to be made, then works back to the data and the model.
What we deliver
Marketing and customer analytics
Know which customers to keep, which channels work and where to spend the next rupee or dollar.
- Churn and retention models
- Marketing mix modelling and attribution
- Customer lifetime value and segmentation
Pricing and revenue management
Set prices with evidence instead of instinct, at SKU, category and store level.
- Price elasticity and optimisation
- Cannibalisation and affinity
- Promotion effectiveness
Forecasting and planning
Forecast demand accurately enough to plan stock, staff and supply around it.
- Sales and demand forecasting
- Inventory planning
- Workforce planning
Risk and finance analytics
Quantify credit, default and prepayment risk under changing economic conditions.
- Loss forecasting
- Survival and hazard models
- Stress testing scenarios
People analytics
Measure performance fairly and plan headcount around real demand.
- Associate performance studies
- Hiring and attrition models
- Incentive design
Experimentation
Test before you roll out, and measure what actually changed.
- Test and control design
- Uplift measurement
- Market pilots before national rollout
Solutions by business function
Marketing & Customer
Customer retention, Path analysis, Social media analytics
3 case studiesPricing & Commercial
Sales forecasting, Price optimisation, Cannibalisation & affinity
1 case studiesOperations & Supply Chain
Inventory planning
2 case studiesPeople & Workforce
Workforce planning, Associate performance
2 case studiesRisk & Finance
Risk management, Enterprise performance dashboard
Related case studies
An automated pricing tool for 90,000 SKUs across 2,000 stores
Elasticity models and a pricing framework that replaced gut-feel pricing, tested in market before rollout.
Read the case study →Finding the drivers of churn for a US telecom provider
Churn segments and models that showed a telecom client why customers were leaving, and where to act first.
Read the case study →Lifetime loss forecasting on a $15 billion mortgage portfolio
A competing-hazards model that tracked default and prepayment risk across a $15 billion portfolio.
Read the case study →Have a decision you want to get right?
Tell us the decision, the data you have and the timeline. We will come back with how we would approach it.