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RFM Analysis
RFM Analysis & Customer Analysis
RFM Analysis & Customer Analysis

RFM (Recency, Frequency and Monetary Value) Analysis is a segmentation technique that's invaluable for growing your product business.

Jessica Nash avatar
Written by Jessica Nash
Updated over a week ago

What is RFM Analysis? 

RFM (Recency, Frequency and Monetary Value) Analysis is a well known and well-loved technique for segmenting customers by their spend pattern. It segments customers using three key dimensions; Recency, Frequency and Monetary Value.

RFM Analysis is an established tool amongst Marketeers, but is increasingly being used by Sales and Account Management teams too. In fact, it helps with all 7 key strategies for growth and profitability in Wholesale, Distribution & Manufacturing businesses:

  1. Attract

  2. Sell

  3. Close 

  4. Onboard

  5. Order Frequency

  6. Order Value

  7. Retention

The key to successfully growing a profitable Wholesale, Distribution or Manufacturing business is not just to attract new customers and get them to place their (first) order with you, but to then retain them for as long as possible, and to upsell them and so maximise their re-spend (increase their average order value and order frequency). In fact, a customer's first order in isolation often results in a loss (typically the Sales & Marketing cost of gaining a new customer is greater than the value of the first order, and you might need 3, 4, 5, 10 or even more orders to break even), so retaining and reactivating each customer is critical to ensure you grow profitably and don't fall into the trap of having a "leaky bucket". 

Looking for more advice on RFM Segmentation, Strategy & Growth?

You can read more about RFM, how it's calculated and how to use it in our blog article here.

But, for now, we're going to assume you're familiar with the technique, or that you're simply happy take our word for it, and use the data we've calculated for you.

RFM Analysis in Prospect CRM

Now you know a little about what RFM Analysis is, and why it's important for your Wholesale business, let's take a look at some of the analysis on your own customers within Prospect CRM!

At a Glance Tiles on a Customer Record

On a CRM Customer record (a Company or Company with an associated active Account or Sales Ledger), you can see the RFM Segment, along with a little extra supporting detail (such as recent turnover comparisons and most recent order date) on the At a Glance tiles in the top right-hand corner.

Sales Analysis Page on a Customer Record

If you click that tile, or navigate to the Sales Analysis page on the left-hand side, you'll then see the RFM Sales Analysis page. This page shows the customer's RFM Segment, as well as other key Sales and RFM information.

For example, you can also see which products they tend to buy with you and how frequently they buy them - all on the Sales Analysis page. 

The Last Order date appears in red if it's been longer than when the customer usually places an order with you. This allows your team to be proactive and targeted about getting this customer to re-spend with you e.g. by sending out a win-back campaign.

In the top right-hand corner of each chart, you'll also find a 'See More' link. Clicking this will open a Report that shows the detailed information behind each of the charts.

RFM Segments in Reports

On various Reports, colour coded labels against Companies allow you to see which customers fall into which segment. Simply add 'RFM Segment' as as a column to any Report to see this with your own custom reports!

Key Standard Reports in Prospect CRM

But, to get you started, we've created some standard Reports in the CRM so you can get started with RFM straight away.

Customers by RFM Segment

This Report divides customers into the RFM segments automatically for you, and can be found in the Marketing Report Group here.

Predicted Churn Alerts

This Report allows CRM users to instantly see which customers are likely to slip away, and can be found in the Sales Report Group here.


What are each of the RFM Segments and how are they calculated?

Here's a list of all the RFM Segments:

  • Champions

  • Loyal Customers

  • Potential Loyalist

  • New Customers

  • Promising

  • Needs Attention

  • About to Sleep

  • At Risk

  • Don't Lose Them

  • Hibernating

  • Lost

Make sure you check out our article here to learn what each mean and for some actionable tips for each.

How are these segments calculated?

Your entire customer based is analysed on the last 2 years of data, and is done on three dimensions:

  1. Recency (how recent is their last order)

  2. Frequency (how many times they've ordered)

  3. Monetary (how much money they've spent)

Without getting too complicated, these dimensions are divided into fifths, and customers are positioned along them.

The way in which your customer data is assigned into the RFM Segments is relative to other customers in your dataset. For example, a Loyal Customer is:

  • Anyone in the top 60% of the combined monetary and frequency values, and

  • Anyone in the top 40% of recency.

Here's a working example...

Example Company Ltd rank:

  • Recency: 3

  • Frequency: 4

  • Monetary: 5

For this business, Example Company Ltd are in the top 20% of highest spenders in the last 2 years, and top 40% of most frequent spenders. Even though their last purchase was 9 months ago, they've ordered more recently than 40% of the rest of the dataset we're comparing them to, making them a Loyal Customer.

To ensure the segmentation is dynamic, scales as your sales/data changes, and works for different Prospect CRM customers, we don't implement hard-coded thresholds and limits. This does mean that the calculations work dynamically and are unique to your profile.

How do I exclude anomaly accounts?

You can exclude certain accounts from the overall RFM Analysis if required. For example, you'd perhaps want to exclude the account that represents your owned direct-to-consumer sales, or ePos systems. Or, maybe 98% of your customers purchase orders regularly, whereas the remaining 2% might, for some reason, place very high value orders just once a year - something you're aware of, and not out the ordinary, but skewing your analysis.

Although our RFM Analysis is super clever and handles general outliers automatically (e.g. big customers such as distributors and small customers such as one-off transactional customers), it doesn't take into account edge case examples like this, so in this instance, you can choose to exclude those customers from the overall analysis.

Examples of when to exclude a customer:

  • Accounts that aren't real customers and represent your own Direct-to-Consumer activity e.g. your own Amazon/eBay/Shopify store

  • Accounts that are only there to account for and represent your own ePos system - your owned retail outlets or trade counters

  • Accounts where you have no control over their spend (e.g. large, and genuinely anomalous, accounts that only ever place one large order with you, once a year)

  • Accounts where there's a reason why they're hibernating (e.g. their business is seasonal, so they temporarily shut down at various points in the year)

  • Accounts whose spend is just very different to the majority of your customers

How do I exclude a customer?

Simply go to the account/Company that you want to exclude. The "Exclude from CLTV" option is now by default on the Company record layout. This allows you to easily exclude any obvious outliers in your data.

Please note: Changing the "Exclude from CLTV" option to 'Yes' will remove the customer from the all customer lifetime value tools, including RFM Analysis PAIGE, the Sales Analysis and the Magic Matrix.

What about excluding B2C Contacts?

You may wish to exclude all B2C Contacts from your B2B sales data and RFM Analysis - simply follow the steps here!

B2B Product Sellers using RFM Analysis


Looking for More RFM Info?

Learn more about RFM Analysis on our dedicated RFM Hub here!

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