Customer Segmentation

20% of Your Customers Drive the Revenue.
RFM Tells You Which 20%.

Upload your order CSV and get every customer scored on Recency, Frequency, and Monetary value — mapped into champions, loyal, at-risk, hibernating, and lost, with the revenue each segment represents and what to do about it. A custom statistical analysis built by AI, not a spreadsheet template.

Validated statistical methods | R code included in every report | No credit card required

Treating Every Customer the Same Is Expensive

The same discount goes to the customer who'd buy anyway, the one who's already gone, and the one you're about to lose. RFM segmentation ends that.

Find Your Champions

The small group of recent, frequent, high-spend customers who carry your revenue. Protect them, reward them, and ask them for reviews — don't discount them.

Catch At-Risk Value Early

High-value customers whose recency is fading are your most urgent list. A win-back offer this month beats a churned customer next quarter.

Prioritize by Dollars

Every segment comes with its revenue total. Stop guessing which campaign matters — the report shows exactly how much money sits in each group.

Export. Upload. Segment.

From order history to named segments in minutes

1

Export Your Orders

Download your order history from Shopify, WooCommerce, Stripe, Amazon, or any POS as CSV. You need three things per order: a customer ID, a date, and an amount.

2

Upload Your CSV

Drop the file into MCP Analytics. The system auto-detects customer IDs, order dates, and monetary values. No manual column mapping or data cleaning needed.

3

Get Your Segments

An interactive report scores every customer, maps them into named segments, totals the revenue in each, and writes plain-English recommendations — with the exact R code included.

What's In an RFM Segmentation Report

Every analysis runs on your actual data and produces a shareable, re-runnable report

RFM Scores Per Customer

Every customer scored on Recency, Frequency, and Monetary value using quantile-based scoring on your actual distribution — not arbitrary cutoffs.

Named Segment Map

Champions, loyal, potential loyalists, at-risk, hibernating, lost — each customer lands in one actionable segment with clear definitions.

Revenue by Segment

How much revenue each segment generated and what share of your total it represents. Prioritize campaigns by dollars at stake.

At-Risk Value List

The customers with high historical value and fading recency — your win-back campaign list, sorted by how much they're worth.

Segment Distribution

How your customer base splits across segments — and whether your champions group is growing or shrinking.

Exportable Lists

Take the customer-to-segment mapping straight into your email platform or ad audiences. Suppress the lost, target the at-risk.

AI Recommendations

Plain-English guidance per segment: who to reward, who to win back, who to reactivate, and who to stop spending money on.

Reproducible R Code

The exact script that produced your segments is in the report. Run it yourself, get the same answer. No black box.

Re-runnable Monthly

The analysis is yours. Upload next month's orders and re-run it — same methodology, consistent segment definitions, migration visible over time.

See What You'll Get

Example output from an RFM segmentation analysis

RFM
RFM Segmentation — Customer Value Analysis
Order-based segmentation • example: online retail transactions • 12 months of data
6
Named Segments
11%
Champions
54%
Revenue From Champions
18%
At-Risk Share

Key Insights

11% of customers generate over half of revenue

The champions segment — recent, frequent, high-spend — is small but carries the business. A retention issue in this group is a revenue event; treat them accordingly.

The at-risk segment holds more recoverable value than any acquisition campaign

Customers with strong historical spend but no purchase in 60+ days represent a concentrated win-back opportunity — they already know the product and converted before.

A third of the email list is hibernating or lost

Continuing to pay to reach these customers in paid audiences wastes budget. Suppressing lost customers and moving hibernating ones to a low-cost reactivation track frees spend for segments that respond.

MCP Analytics vs Spreadsheet RFM Templates

What you gain beyond a quintile formula

MCP Analytics
Spreadsheet Template
Method
Validated statistical implementation in R, methodology documented in the report, code included
Method
Hand-built quintile formulas — ties, outliers, and skewed spend distributions are your problem
Consistency
Re-run the identical analysis on fresh data every month — segment definitions stay fixed, migration is visible
Consistency
Formulas drift as the sheet grows; last month's "champion" cutoff isn't this month's
Output
Interactive report with revenue per segment, at-risk lists, AI-written recommendations, exportable mappings
Output
A column of scores you still have to interpret and turn into campaigns yourself
Defensibility
Show-the-work analysis you can put in front of a team or client: method, assumptions, and code attached
Defensibility
"Trust my spreadsheet"
Time to Segments
Minutes from upload
Time to Segments
An afternoon of formula debugging, repeated every month
R
Real code, included
AES-256
Data encryption
Re-runnable on fresh data
Free
To get started

RFM Segmentation FAQ

What is RFM segmentation?

RFM segmentation scores every customer on three behaviors: Recency (how recently they bought), Frequency (how often they buy), and Monetary value (how much they spend). Combining the three scores maps each customer into a named segment — champions, loyal customers, at-risk, hibernating, lost — so you can treat each group differently instead of blasting everyone with the same message.

What data do I need for RFM analysis?

A CSV of orders with three columns: customer ID, order date, and order amount. That's it. Exports from Shopify, WooCommerce, Stripe, Amazon Seller Central, or any POS system work directly — MCP Analytics auto-detects the columns.

How is this different from an RFM template or spreadsheet?

A spreadsheet template makes you compute quintiles, handle ties and outliers, and maintain formulas as your data grows. MCP Analytics runs a validated statistical implementation in R on your actual data, documents the method in the report, includes the exact code, and lets you re-run the same analysis on fresh data next month — so segment definitions stay consistent over time.

What do I do with each RFM segment?

Champions: reward them and ask for reviews and referrals. Loyal: upsell and cross-sell. At-risk (high past value, fading recency): win-back offers before they lapse. Hibernating: low-cost reactivation campaigns. Lost: suppress from paid audiences to save ad spend. The report attaches revenue totals to each segment so you can prioritize by dollars, not counts.

How often should I re-run RFM segmentation?

Monthly for most stores, weekly for high-volume ones. Segments shift as customers buy or lapse. Your MCP Analytics report is a re-runnable analysis you own — upload fresh data and get the same methodology applied consistently, so you can track how customers migrate between segments over time.

Know Exactly Which Customers Deserve Your Next Campaign

Upload your order data and get named RFM segments with revenue totals in minutes. No credit card required.