Customer Segmentation Matrix with RFM Scoring in Excel,\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n
Implement Recency-Frequency-Monetary (RFM) scoring to segment customers into actionable groups for targeted marketing campaigns.
Build an RFM customer segmentation model in Excel that scores each customer on recency, frequency, and monetary value, then classifies them into segments with specific marketing strategies.
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Prompt objective
Build an RFM customer segmentation model in Excel that scores each customer on recency, frequency, and monetary value, then classifies them into segments with specific marketing strategies.
Real use case
An e-commerce store with 15,000 customers sends the same promotional email to everyone. They want to segment customers so high-value loyal customers get VIP treatment, at-risk customers get win-back offers, and new customers get onboarding sequences.
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Prompt
Build an RFM customer segmentation model in Excel for [COMPANY NAME] with [NUMBER] customers and [PERIOD] months of transaction history.\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Tab 1 — Transaction Data:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Columns: Customer ID, Transaction Date, Order Value, Product Category, Channel\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Source: export from [PLATFORM: Shopify/WooCommerce/ERP]\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Tab 2 — RFM Calculations:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Recency: Days since last purchase (TODAY() - MAX(Transaction Date) per customer)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Frequency: Total number of transactions per customer (COUNTIF)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Monetary: Total spend per customer (SUMIF)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Score each dimension 1-5 using PERCENTILE or NTILE logic:\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - Recency: 5 = most recent, 1 = least recent\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - Frequency: 5 = most frequent, 1 = least frequent\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - Monetary: 5 = highest spend, 1 = lowest spend\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Tab 3 — Segment Classification:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Combine scores into RFM code (e.g., 555, 111)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Segment rules:\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - Champions: R>=4, F>=4, M>=4\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - Loyal: R>=3, F>=4, M>=3\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - At Risk: R<=2, F>=3, M>=3\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - Hibernating: R<=2, F<=2, M<=2\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - New Customers: R>=4, F=1\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n - Potential Loyalists: R>=4, F=2-3\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Customer count and revenue by segment\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Tab 4 — Marketing Actions by Segment:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- For each segment: recommended campaign type, channel, offer, frequency\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Estimated revenue impact per segment\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Priority ranking for campaign execution\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n**Tab 5 — Dashboard:**\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Segment distribution pie chart\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Revenue by segment bar chart\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Segment migration over time (if historical data available)\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n- Top 10 customers per segment\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\n\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\\nUse SUMPRODUCT, INDEX/MATCH, and conditional formatting.
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