Upload order data, get customer segments — Champions, At Risk, Lost, and 8 more. Free.
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Running rfm customer segmentation analysis analysis...
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Analyze another fileScores each customer on three dimensions — how recently they bought (Recency), how often (Frequency), and how much they spent (Monetary). Combines scores to place customers into named segments like Champions, At Risk, or Lost.
Use this when you have transaction data and want to group customers by behavior to target marketing, retention, or win-back campaigns.
If you need dollar-value predictions per customer, use Customer Lifetime Value (BG/NBD). If you need to predict who will churn next, use Churn Prediction.
Built for: E-commerce marketer, CRM manager, email marketing lead, Shopify store owner
Typical data source: Order export from Shopify, WooCommerce, or any system with customer IDs, dates, and amounts
Order-level transaction data
Minimum 100 rows · Best with 1000-50000 transactions
Segments customers using Recency, Frequency, and Monetary (RFM) analysis. Assigns each customer scores 1-5 on three dimensions and groups them into 11 named segments (Champions, Loyal, At Risk, etc.) with revenue and behavioral metrics per segment.
How many customers fall into each segment. A healthy business has a thick Champions layer and a thin Lost layer. If At Risk is the biggest segment, you have a retention problem.
Revenue contribution per segment. Champions often generate 40-60% of revenue despite being 10-20% of customers. This justifies disproportionate retention investment.
The joint distribution of Recency and Frequency scores. Dense cells in the top-right = loyal repeat buyers. Dense in the bottom-left = one-time or churned customers.
Distribution of R, F, and M scores independently. Skew toward low scores means most customers are disengaged — a typical pattern for newer stores.
Your highest-scoring customers by combined RFM. These are your Champions — protect them with VIP treatment, early access, or loyalty rewards.
Each customer as a dot positioned by recency and frequency, sized by monetary value. Clusters reveal natural behavioral groups in your customer base.
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Need something simpler? Retention Analysis — Just need retention rates by cohort, not individual scoring
Need more power? Bg Nbd — Need dollar-value predictions per customer, not just segments
Similar: Rfm Segmentation, Rfm Analysis
See our FAQ for details on pricing, data privacy, and how the analysis works. Every report includes a Methodology section showing the statistical test, assumptions checked, and diagnostics run.
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