NBA engines that deliver the right product, offer, or communication to each customer at the right moment — increasing conversion, basket size, and lifetime value simultaneously.
Most retail personalisation stops at product recommendations based on purchase history. A properly engineered NBA engine goes further — selecting the optimal action (offer, content, channel, timing) for each customer based on real-time context, propensity scores, and business constraints. The lift over generic personalisation is consistent and significant.
Building a personalisation capability or upgrading from basic recommendations? We're happy to discuss your current setup before this case study is published.
Discuss Your Challenge →Generic recommendations and batch communications missing high-intent customers at the right moment
Real-time NBA engine with propensity models, channel optimisation, and business rule guardrails
Improved conversion rates, higher basket values, and measurable CLV uplift