Upload your order export, map customer, date, and amount — get every customer scored on Recency, Frequency, and Monetary value and mapped into Champions, At Risk, and six more standard segments. Free.
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Free analyses run on up to 10,000 rows. Larger files are randomly sampled to that size — sign up to analyze your full dataset.
Scoring customers on recency, frequency, and monetary value...
Sent to — segment sizes and revenue breakdown, the Recency x Frequency grid, average customer value by segment, R code, and AI insights.
Analyze another fileFor every customer the analysis computes Recency (days since their last order, measured from the most recent date in the data), Frequency (number of orders), and Monetary (total order value). Each dimension is scored 1-5 by quintile against the rest of the customer base, and the R and F scores map each customer into a standard industry segment — Champions, Loyal, Potential Loyalist, New Customers, At Risk, Can't Lose Them, Need Attention, Hibernating. Segment-level stats show size, revenue share, and average recency.
Use it on any raw order export when you want to know who your best customers are, who is slipping away, and where retention or win-back budget will pay off.
Not for pre-aggregated data (one row per customer), subscription businesses where 'orders' don't capture engagement, or when you need a forward-looking churn probability rather than a behavioral map.
Built for: E-commerce, retail, and CRM operators segmenting a customer base from order history
Typical data source: An order or transaction export with customer ID, order date, and order amount
A raw transactions table, one row per order. For example, an order export:
Minimum 30 rows · Best with 1,000-100,000 orders across 100+ customers spanning 6-24 months
Standard-library analysis: segment your customers by Recency, Frequency, and Monetary value straight from a raw transactions table (one row per order). Every customer gets quintile R/F/M scores and lands in a standard industry segment — Champions, Loyal, At Risk, Can't Lose Them, Hibernating and more — with per-segment size, revenue, and recency stats so you know exactly who to reward, who to win back, and how much revenue is at stake.
How your customer base splits across the eight standard RFM segments — the shape tells you whether the base is growing, loyal, or decaying.
Each segment's headcount, revenue, average customer value, and average days since last order in one table — the prioritization map.
Every customer placed on the Recency x Frequency plane: the top-right is your core, the lapsed high-frequency column is the win-back target.
What a typical customer in each segment is worth, so you can weigh the cost of a campaign against the value of the customers it targets.
Plain-English interpretation — what the numbers mean, what's significant, and what to do next.
Who should get the win-back campaign?
Upload your order export and map customer, date, and amount. The segment map separates At Risk and Can't Lose Them customers — historically valuable buyers who went quiet — and tells you exactly how much revenue is at stake.
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.
Run any analysis on your own data — validated R analyses, interactive reports, AI insights, and PDF export.
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