What I help with
Solutions
Six practices, one method: frame the decision, build the system, hand it over.
Marketing measurement
Marketing mix modeling, built to allocate budget
Measurement that changes where the money goes. Bayesian MMM, incrementality, response curves and budget allocation, deployed as a system your team runs on a monthly cadence.
See the practiceDemand and pricing
Demand planning and pricing, under real uncertainty
Forecasting, markdown and price decisions built as one system. Probabilistic where it matters, constrained by how the business actually operates, and deployed on the cadence planning already runs on.
See the practicePricing and revenue
Pricing, elasticity and revenue optimization
Price, markdown and promotion decisions as one system: elasticities the data can actually identify, constraints the business actually has, and an optimizer that recommends a price list, not a chart.
See the practiceCustomer value
Customer lifetime value, churn and product recommendations
Models that decide who to acquire, who to keep and what to show them: predicted value used for activation, churn scored where an action still exists, recommendations that stay auditable even when an LLM is involved.
See the practiceRisk and credit
Fraud detection, credit risk and operational risk models
Decisions that must be fast, explainable and right most of the time: automated credit decisions, fraud scoring on retail transactions, and supplier risk mapped as a network rather than a scorecard.
See the practiceAgentic and AI systems
AI systems that reach production
RAG, assistants and agentic workflows where the interesting part is not the model. Auditable business logic, a deterministic core, and a deployment that survives contact with real users.
See the practice