RFM (Recency, Frequency, Monetary) Customer Score & Retention Probability Calculator

Score customer cohorts using Recency (days), Frequency (orders), and Monetary value ($).

Expected 12-Month Customer Value
USD 405.70
Active Retention Probability P(Alive) 75.13 %
Composite RFM Health Score (0–100) 69 points
Average Order Value (AOV) USD 90.00
Inputs
⚡ Scenarios:
Amounts are treated in the selected currency; no foreign-exchange conversion is applied.
days
Days elapsed since the customer’s most recent order (Recency).
orders
Total historical orders placed by the customer (Frequency).
days
Days since the customer’s very first order.
$
Total cumulative revenue from this customer (Monetary).
Results & Graph
Expected 12-Month Customer Value
USD 405.70
Active Retention Probability P(Alive)
75.13 %
Composite RFM Health Score (0–100)
69 points
Average Order Value (AOV)
USD 90.00

Expected 12-Month Customer Value

Graph 1 • RFM Customer Segmentation • Domain Architecture & Live Telemetry Maps Days Since Last Purchase Recency, Total Repeat Orders Frequency, Customer Tenure Days through RFM Customer Segmentation Formula.
E-COMMERCE & UNIT ECONOMIC Expected 12-Month Customer USD 405.70 Active Retention Probabili 75.13 % RFM Customer Segmentation • Component Waterfall Expected 12-Month Customer Val USD 405.70 Active Retention Probability P 75.13 % Composite RFM Health Score (0– 69 points Average Order Value (AOV) USD 90.00
Graph 2 • Expected 12-Month Customer Value Across Days Since Last Purchase Recency Sweep (40% → 160%) Evaluates AvgInterval = TenureDays / PurchaseCount; P(Alive) ≈ 1 / [ 1 + (DaysSi across 7 operating points (current input highlighted).
0 $ 282.1 $ 564.1 $ 512.8 14days 482.5 21days 445.6 28days 405.7 35days 365.7 42days 327.5 49days 292.3 56days
Graph 3 • Joint Sensitivity: Days Since Last Purchase Recency × Total Repeat Orders Frequency Compares Expected 12-Month Customer Value when Total Repeat Orders Frequency is shifted +25% (solid) vs. −25% (dashed).
0 $ 272.2 $ 544.3 $ --- Total Repeat Orders Frequency @ 75% 430.8 -30% 393.1 -15% 355.9 +0% 320.7 +15% 288.1 +30%
Summary: With average purchase interval 60.8 days and 35 days recency, active retention probability P(Alive) is 75.1%, RFM health score is 69/100, and projected 12-month spend is USD 405.70.
Summary: With average purchase interval 60.8 days and 35 days recency, active retention probability P(Alive) is 75.1%, RFM health score is 69/100, and projected 12-month spend is USD 405.70.
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Formula & Mathematical Methodology: RFM Customer Segmentation Formula

AvgInterval = TenureDays / PurchaseCount
P(Alive) ≈ 1 / [ 1 + (DaysSinceLastPurchase / AvgInterval)² ]
Expected12MoValue = P(Alive) × AnnualRunRate$
AvgInterval = TenureDays / PurchaseCount; P(Alive) ≈ 1 / [ 1 + (DaysSinceLastPurchase / AvgInterval)² ]; Expected12MoValue = P(Alive) × AnnualRunRate$
  • daysSinceLastPurchaseRecency: Days elapsed since the customer’s most recent order (Recency).
  • totalRepeatOrdersFrequency: Total historical orders placed by the customer (Frequency).
  • customerTenureDays: Days since the customer’s very first order.
  • totalHistoricalSpendMonetary: Total cumulative revenue from this customer (Monetary).

Rounding: Internal floating-point calculations preserve full precision; currency and percentage outputs round to 2 decimal places.

Worked Example: RFM Customer Segmentation Worked Example

Score customer cohorts using Recency (days), Frequency (orders), and Monetary value ($).

  1. Enter your operational, financial, or physical measurement inputs.
  2. Apply the standard domain equation: AvgInterval = TenureDays / PurchaseCount; P(Alive) ≈ 1 / [ 1 + (DaysSinceLastPurchase / AvgInterval)² ]; Expected12MoValue = P(Alive) × AnnualRunRate$.
  3. Review the primary result, sensitivity metrics, and 3 interactive SVG graphs.
Result: Calculates RFM Customer Segmentation via AvgInterval = TenureDays / PurchaseCount; P(Alive) ≈ 1 / [ 1 + (DaysSinceLastPurchase / AvgInterval)² ]; Expected12MoValue = P(Alive) × AnnualRunRate$.

Frequently Asked Questions

How does the RFM (Recency, Frequency, Monetary) Customer Score & Retention Probability Calculator calculate results?

It computes AvgInterval = TenureDays / PurchaseCount; P(Alive) ≈ 1 / [ 1 + (DaysSinceLastPurchase / AvgInterval)² ]; Expected12MoValue = P(Alive) × AnnualRunRate$ directly in your browser and updates three custom SVG visualizations in real time.

Can I use Goal Seek to solve backwards for any input variable?

Yes. Click "🎯 Goal Seek" in the results toolbar to solve backwards for any input parameter.

Are my business and personal numbers kept private?

Yes. All calculations execute 100% locally in your browser with zero server transmission.

Business & Marketing · E-Commerce & Unit Economics

RFM (Recency, Frequency, Monetary) Customer Score & Retention Probability Calculator: inputs, method, and how to read the result

Score customer cohorts using Recency (days), Frequency (orders), and Monetary value ($).

Choose inputs for the case you are checking

The defaults are illustrative. Replace them with values for your case and keep the units shown beside each field.

  • Display Currency: Amounts are treated in the selected currency; no foreign-exchange conversion is applied.
  • Days Since Last Purchase Recency: Days elapsed since the customer’s most recent order (Recency).
  • Total Repeat Orders Frequency: Total historical orders placed by the customer (Frequency).
  • Customer Tenure Days: Days since the customer’s very first order.

What the calculation includes

With the default values shown, Expected 12-Month Customer Value is USD 405.70. The calculation follows RFM Customer Segmentation Formula; the formula and variable definitions above show how the inputs combine.

One-input check: With the other defaults held constant, changing Days Since Last Purchase Recency from 35 days to 39 days changes Expected 12-Month Customer Value from USD 405.70 to USD 382.71. This is a comparison inside the calculator's stated model, not a prediction.

Where to use caution

  • Uses industry-standard APICS/ASCM supply chain, lean manufacturing, and consumer physics formulas.
  • Actual commercial freight tariffs, marketplace commissions, and utility rates vary by carrier and contract.

Scope: Global Supply Chain, Business & Consumer Standard Check the assumptions and limitations against your situation before relying on the estimate.

More in Business & Marketing: ROI Calculator (Return on Investment), Percentage Calculator.