Customer Growth Recommendation Engine
A customer intelligence platform that reads raw transaction history and answers three commercial questions: who is worth keeping, what gets bought together, and what to offer next.
Plenty of transaction data, no growth priorities.
Retail and e-commerce teams sit on hundreds of thousands of transactions but can rarely say which customers hold the most upside, which products travel together, or where cross-sell actually exists.
Without that, campaign planning defaults to intuition and the same broad segments get the same broad offer.
Segment, then recommend.
Recency, frequency, and monetary features cluster customers into Champions, Loyal, At-Risk and other actionable groups.
Concentration analysis showing how much revenue sits with how few customers — the retention argument in one chart.
Apriori association rules surface product affinities that aren't obvious from category structure.
Customer value and product affinity combine into a ranked offer per customer, explorable in the dashboard.
Opportunity sizing, not just reporting.
A recommendation nobody can interrogate doesn't get activated.
The modeling here is standard; the design decision was making every recommendation traceable back to the customer's own purchase history. That's what moves a marketing team from "interesting" to "let's run it."