Data Science

Building a Customer-Brand Affinity Engine for Physical Retail

A technical architecture for customer-brand affinity in physical retail: customer windows, lift and PMI, Item2Vec embeddings, graph construction, constrained layout optimization, and causal validation.

By Cyril NoirotAugust 15, 20269 min read

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The strategic case for customer-brand affinity is simple: a physical store recommends through space, and customer histories reveal which brand relationships the current layout serves or suppresses.

1. What is the analytical population? 2. What counts as co-occurrence? 3. How do we separate affinity from popularity and noise? 4. How do we turn relationships into feasible layout scenarios? 5. How do we measure whether a new adjacency caused any incremental value?

This article describes that system from transaction data to measured intervention.

For the executive and merchandising view, start with Your Store Layout Is a Recommendation System.

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Technical writing on forecasting, pricing, and decision systems. No fixed schedule, no spam.

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Building a Customer-Brand Affinity Engine for Physical Retail

Cyril Noirot

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