RFM Analysis for E-commerce Customer Segmentation
Implements the RFM model (Recency, Frequency, Monetary Value) to classify customers into actionable segments.
Create a data-driven segmentation that identifies most valuable customers, churn risks, and growth potential to guide personalized campaigns.
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Prompt objective
Create a data-driven segmentation that identifies most valuable customers, churn risks, and growth potential to guide personalized campaigns.
Real use case
PetShop Feliz, a pet products e-commerce with 28,000 customers and [CURRENCY]1.2M/month in revenue, sends the same newsletter to their entire database and wants to start personalizing offers based on purchase behavior.
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Prompt
Implement a complete RFM analysis for the customer base of [COMPANY NAME], an e-commerce business in the [SEGMENT] category with [NUMBER] customers. Context: - Average order value: [CURRENCY][AMOUNT] - Average purchase frequency: [FREQUENCY] - Analysis period: last [NUMBER] months - Email platform: [PLATFORM: RD Station/Mailchimp/ActiveCampaign/Klaviyo] - E-commerce platform: [PLATFORM: Shopify/VTEX/Nuvemshop] **1) RFM Metrics Definition:** - **Recency (R)**: Days since last purchase - Score 5: 0-[X] days | Score 4: [X]-[X] | Score 3: [X]-[X] | Score 2: [X]-[X] | Score 1: [X]+ days - Define optimal ranges for the [SEGMENT] sector - **Frequency (F)**: Number of orders in the period - Score 5: [X]+ orders | Score 4: [X]-[X] | ... | Score 1: 1 order - Account for sector seasonality - **Monetary (M)**: Total spend in the period - Score 5: [CURRENCY][X]+ | Score 4: [CURRENCY][X]-[X] | ... | Score 1: [CURRENCY]0-[X] - Adjust for sector average order value **2) Resulting RFM Segments (minimum 8):** For each segment, define: - Segment name (e.g., 'Champions', 'At Risk', 'Hibernating') - RFM combination (e.g., R5F5M5, R1F1M3) - Estimated % of database - Estimated value (CLV) - Specific email strategy - Ideal contact frequency - Recommended offer type - Example subject line **3) Campaigns by Segment:** - **Champions (R5,F5,M5)**: VIP program, early access, zero discount approach - **Loyal (R4,F4,M3+)**: Upsell, loyalty points, cross-sell - **Potential (R4,F2,M3)**: Increase frequency, bundle offers - **New Customers (R5,F1,M2)**: Onboarding, second purchase, education - **Need Attention (R3,F2,M2)**: Light reactivation, survey - **At Risk (R2,F3,M4)**: Urgent win-back, aggressive offer - **Can't Lose (R1,F4,M5)**: Personal contact, maximum offer - **Hibernating (R1,F1,M1)**: Last attempt or list cleanup **4) Technical Implementation:** - Required SQL query/export from platform - How to set up segments in email platform - Score update frequency (weekly/monthly) - Dashboard to track segment migration **5) Expected ROI:** - Estimated revenue increase per email - Expected unsubscribe reduction - Implementation timeline
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