Tool · Updated May 2026

RFM Analysis Tool — Segment Customers from Any Excel or CSV File

Upload your transaction data. Get Recency, Frequency, Monetary scores. Export champions, at-risk, and churned customer lists — in under 5 minutes.

Run RFM Analysis Free → Watch 2-min demo
No credit card   Free tier, no time limit   No SQL or Python needed

How It Works — 4 Steps

DataHub Pro handles the full RFM pipeline automatically. You provide the raw transaction data; the tool does the rest.

Step 1

Upload your file

Upload your CSV or Excel file — transactions with customer ID, date, and order amount. No schema required.

Step 2

Auto-score R, F, M

DataHub Pro detects your columns automatically and scores each customer Recency, Frequency, and Monetary value on a 1–5 quintile scale.

Step 3

Segment assignment

Customers are mapped to all 11 industry-standard RFM segments — Champions, At-Risk, Hibernating, and more — instantly.

Step 4

Export and act

Download per-segment CSVs for your email tool, or generate an AI-written insights report as DOCX or PPTX.

What Data You Need

RFM analysis only requires three columns. Most e-commerce and CRM platforms can produce this export in seconds.

Required columns

  • Customer identifier — customer ID or email address
  • Transaction date — date of each order or purchase
  • Order value / amount — the revenue amount for each transaction

That's it. DataHub Pro auto-detects column names and handles common date formats. One row per transaction; one customer can appear many times.

Works with exports from Shopify, WooCommerce, Stripe, Amazon, Salesforce, HubSpot, Zoho CRM, and any other platform that exports transaction history as CSV or Excel.

The 11 Standard RFM Segments — Explained

DataHub Pro maps every customer to one of the 11 industry-standard RFM segments based on their combined R, F, and M scores. Here's what each segment means and how to act on it.

Segment RFM profile What it means Recommended action
Champions High R, F & M Bought recently, buy often, spend the most VIP rewards, early access, referral asks
Loyal Customers High F & M Frequent buyers with solid spend Loyalty programme, upsell higher tiers
Potential Loyalists Recent, mid F Recent buyers showing repeat behaviour Onboarding emails, subscription offers
Recent Customers High R, low F Bought very recently but only once Welcome series, second-purchase incentive
Promising Recent, low F & M New customers with potential Engagement campaigns, product education
Need Attention Mid R, F & M declining Above-average customers going quiet Reactivation offer, product recommendation
About to Sleep Below average R, F & M Engagement dropping, at risk of lapsing Win-back discount, survey to understand why
At Risk High F & M, low R Previously your best customers — now gone quiet Urgent win-back campaign, personal outreach
Can't Lose Them High M, very low R Big spenders who have stopped buying Direct outreach, exclusive re-engagement offer
Hibernating Low R, F & M Low-value customers who have lapsed Low-cost reactivation or suppress from list
Lost Lowest R, F & M Churned — unlikely to return Remove from active list, save on email costs

Why Use DataHub Pro for RFM Analysis?

Who Uses This Tool

🛒

E-commerce teams

Running Shopify or WooCommerce order exports to identify VIP and at-risk customers.

📊

Marketing agencies

Delivering customer analysis to e-commerce or retail clients as part of a reporting package.

💻

SaaS teams

Analysing subscription and usage data to identify expansion and churn risk accounts.

🏪

Retail teams

Working with POS transaction exports to drive loyalty and re-engagement campaigns.

RFM Analysis Options — Compared

There are several ways to run RFM analysis. Here's how the approaches compare on time, skills needed, and cost.

Method DataHub Pro Excel manual Python / R Segment / Klaviyo
Time to results 5 minutes 2–4 hours Days Built-in (live data only)
Skills needed None Advanced Excel / Power Query Data science None
Cost From $14.99/mo (free tier available) Time cost only Developer cost $100s/mo
Works from CSV / Excel Yes Yes Yes Requires live integration
AI narrative Included No Manual Limited
DOCX / PPTX export Yes No No No

Frequently Asked Questions

What data do I need for RFM analysis?

You need three columns: a customer identifier (ID or email), a transaction date, and a transaction value. Most e-commerce platforms — Shopify, WooCommerce, Stripe — can export this as a CSV directly from their orders or reports section. DataHub Pro handles the rest automatically.

How long does RFM analysis take in DataHub Pro?

Typically 2–5 minutes from upload to segmented output. The tool auto-detects your columns, runs the quintile scoring across all three dimensions, and produces the full 11-segment breakdown — no configuration required. For larger files (100,000+ rows) it may take a few minutes longer.

What are the standard RFM segments?

The 11 standard segments are: Champions, Loyal Customers, Potential Loyalists, Recent Customers, Promising, Need Attention, About to Sleep, At Risk, Can't Lose Them, Hibernating, and Lost. DataHub Pro maps your customers to all 11 automatically using the industry-standard RFM matrix. See the segment table above for RFM profiles and recommended actions for each.

Can I export my RFM segments for email marketing?

Yes. Each segment exports as a separate CSV with customer IDs and email addresses, ready to upload to Mailchimp, Klaviyo, HubSpot, or any email tool. The Champions segment CSV is ideal for VIP campaigns; the At-Risk and Can't Lose Them CSVs for win-back campaigns. You can also export all segments in a single file with a segment label column if your tool supports filtering.

How does DataHub Pro calculate RFM scores?

DataHub Pro uses quintile scoring (1–5) for each dimension. Recency is scored by days since last purchase — a score of 5 means the customer bought most recently. Frequency is scored by total order count. Monetary by total lifetime spend. Final segment assignments use the industry-standard RFM matrix, which maps score combinations to the 11 named segments.

Run Your First RFM Analysis Free

Upload your transaction CSV or Excel. Get Champion, At-Risk, and churned customer lists in under 5 minutes. No SQL. No Python. No credit card.

Free tier, no time limit   No credit card   Cancel any time

Related: RFM Segmentation — educational guide · AI Excel Analysis · RFM Analysis in Excel — step-by-step tutorial