E-commerce Use Cases/Product & CatalogData Analyst

Which 10 category pairs have the highest co-purchase affinity score (lift > 3.0) based on the last 12 months of order data?

Build a category co-purchase matrix to identify natural cross-category affinities for recommendation and merchandising.

Metrics & KPIs

Lift score per category pairco-purchase frequencybasket size with cross-category

Required Data

Order line itemscategory mappingscustomer IDs

Data Sources

Data WarehouseE-commerce Platform

Works with tools like

SnowflakeBigQueryRedshiftDatabricksClickHouseShopifyWooCommerceMagentoBigCommerceSalesforce Commerce Cloud

How Bruin answers this

Bruin

Bruin AI Data Analyst

Which 10 category pairs have the highest co-purchase affinity score (lift > 3.0) based on the last 12 months of order data?

Bruin connects to your Data Warehouse, E-commerce Platform and runs the analysis automatically.

It tracks Lift score per category pair, co-purchase frequency, basket size with cross-category and delivers the answer in seconds, in Slack, Discord, Teams, Google Chat, WhatsApp, Telegram, email, or your browser.

Bruin for e-commerce

Use cases across every team in your e-commerce business, from conversion funnels to inventory, marketing to customer lifetime value. One AI that speaks your data.

C-Level/ExecutiveCategory ManagerCustomer Experience ManagerData AnalystDigital Marketing SpecialistE-commerce ManagerFinance ManagerGrowth ManagerMarketing ManagerMerchandiserOperations ManagerSupply Chain Manager

Get this answer in seconds

Connect your data, ask the question, get the answer. No SQL needed.