The Guide to RFM Analysis Using ChatGPT (With Free Prompt)

If you've ever tried to run RFM (Recency, Frequency, Monetary) analysis for your brand, you've probably hit one of two walls:

1. You paid way too much for access to a dashboard that took too long for you to get the information you wanted, or was unclear how to put it into action.

2. You spent hours in Excel or in a data analysis tool, got a headache, and still weren't confident in your segments.

RFM is one of the most battle-tested ways to understand your customer base. But it's often buried inside expensive enterprise tools or analytics suites (lookin' at you, Klaviyo Advanced Analytics).

So we asked: Can you skip the cost, the time, and the headache—and just use ChatGPT to do your RFM analysis?

Turns out, you can. And it only takes a few minutes.

What is RFM Analysis (and why should you care)?

RFM stands for Recency, Frequency, and Monetary. It's a time-tested way to group your customers based on:

• Recency: How recently a customer made a purchase

• Frequency: How often they purchase

• Monetary: How much they spend

This simple model has been around since the 1990s, but it's still one of the most effective ways to understand customer behavior. If you need some light reading, there's a great scientific journal on RFM analysis at Research Gate. In fact, another study on RFM analysis showed that targeted campaigns could yield up to 77% increase in ROI.

It's because RFM analysis at its core is not just helping you segment, but:

• Identify your top-performing customer segments

• Create more relevant campaigns

• Maximize retention and LTV while reducing guesswork

• Understand lifecycle patterns and optimize cadence

• Spot long-term trends in purchasing power across your base

And it works. Brands that segment by RFM consistently outperform those that blast the same message to everyone.

The Problem: RFM is still too hard (or expensive)

Even though the math is simple, actually doing RFM is a pain. If you're not paying for a tool to give you an RFM dashboard, here's what usually happens:

• You export a CSV from Shopify, Recharge, or your CRM

• You clean and reformat the data manually

• You try to write formulas or SQL queries to calculate scores

• You end up doubting the output, because who really trusts a VLOOKUP at midnight?

And the challenge doesn't stop there. Once you have scores, what do they mean? Which thresholds make sense for your brand? Should someone who ordered twice last month get the same score as someone who's ordered monthly for a year?

Meanwhile, many email service providers put RFM behind a paywall. And third-party tools often require long onboarding, API access, or a chunk of your budget.

That's a shame because RFM even in its current form is becoming old school. While helpful, it's lacking the predictive power of AI. Even still, basic RFM is a great starting point for any brand and should be table stakes.

So we asked ChatGPT to do it for us.

The Prompt: RFM analysis with ChatGPT in minutes

We created a simple prompt that uses ChatGPT's 4.1 or o3 model to parse your data and generate an RFM model.

First, we need to get the data.

• Log in to your Shopify store

• Goto Orders

• Export your order data for the last 12 months

• The CSV should download

Next, let's get everything rolling in ChatGPT

• Start a new o3 or 4.1 chat with ChatGPT (o3 tends to perform better on this but 4.1 can work)

• Attach/upload your CSV to the chat prompt

• Replace <BRAND NAME> and <BRAND DETAILS> in the prompt below with your information

• Start the chat!

#ROLE
Take on the role of an expert direct-to-consumer email marketer for #BRAND. 

#BRAND
Using the attached data, you're performing an RFM analysis of data for our brand <BRAND NAME>. <Insert general details about your brand and product set>

Pro Tip: We intentionally keep the analysis straightforward. We didn't ask for segments because it requires true RFM scoring. LLMs today do a bad job of sequencing math, such as creating a score, and then using that score. It goes off the rails. As a result, this prompt is focused on quality insights. Each score is based directly on the raw data: how recently someone purchased, how often they purchased, and how much they spent.

Since RFM isn't just about grouping customers. The insights the AI generates are powerful:

• See how much of your revenue comes from high-frequency vs. one-time buyers

• Track how customer quality changes over time

• Measure the impact of a promotion on customer frequency

• Identify when a loyal customer base starts to slip

And of course, ChatGPT suggests tactical ways to treat each group differently, from winback campaigns to VIP rewards.

Is There Anything Better Than RFM?

RFM is great—but it's not predictive. It's a historical snapshot. That's why brands are shifting to AI-based segmentation that adapts in real time.

Instead of static rules, AI segments can:

• Predict which customers are likely to buy right now

• Predict what customers need in order to buy

• Adjust targeting dynamically as behavior changes

McKinsey puts it clearly: "Brands that personalize experiences using predictive analytics see a 5-8x return on marketing spend."

That's where Raleon comes in:

• Our AI segments go beyond static scoring models

• Everything syncs automatically with your store. No data wrangling, no time-consuming analysis

• Our automated analysis constantly learns and improves

You don't need to spend hours in a dashboard. You don't need formulas. Just plug it in and let the AI do the thinking.

RFM Is powerful, But It Doesn't Have to Be Painful

RFM analysis is one of the simplest and most effective ways to understand your customers. But it often either cost too much or takes too much effort.

Using ChatGPT (or Claude) you can:

• Skip the dashboards

• Skip the spreadsheets

• Run a clean, effective RFM analysis in minutes

If you're just getting started with understanding your customers, this is your entry point. If you're ready to go deeper, Raleon's AI segments and lifecycle automation take it to the next level.

Either way, no more guesswork. No more flying blind.