customer-segmentation

RFM analysis scores your Shopify customers by recency, frequency, and monetary value to reveal loyalty patterns. You provide customer purchase history and segment definitions to receive customer counts, lifetime value estimates, and recommended marketing actions for each group.

Behavioral cohort analysis groups customers by shared activity, lifecycle stage, and purchase history for precise targeting. It identifies patterns among champions, loyal buyers, at-risk customers, and dormant users to improve retention marketing and personalization.

Yes, churn-risk identification uses lifetime value estimates and RFM scoring to flag at-risk buyers. The analysis segments your customer population by behavior and purchase history, then recommends specific churn prevention campaigns for those groups.

Segment-specific marketing actions are generated by analyzing customer behavior and lifetime value. The analysis recommends targeted campaigns such as VIP rewards, win-back offers, onboarding flows, and churn prevention tailored to each behavioral cohort.

Customer segmentation applies directly to Shopify retention marketing by processing your store's purchase and engagement data. It requires segment definitions and customer counts to deliver actionable groups with characteristics and recommended retention actions.

Grouping Shopify customers by purchase history uses RFM scoring and behavioral cohorts to categorize them into champions, loyal customers, new buyers, and dormant users. This requires segment definitions and returns counts with lifetime value insights for each group.