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:
Attract
Sell
Close
Onboard
Order Frequency
Order Value
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 to take our word for it and use the data we've calculated for you.
RFM Analysis in the 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 the 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.
'See More' Links
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 a column to any Report to see this with your own custom reports!
Key Standard Reports in the 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 means and for some actionable tips for each.
How are these segments calculated?
Your entire customer base is analysed on the last 2 years of data, and is done on three dimensions:
Recency (how recent is their last order)
Frequency (how many times they've ordered)
Monetary (how much money they've spent)
Without getting too complicated, these dimensions are divided into fifths, and customers are positioned along them.
How your customer data is assigned to 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 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 of 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 all the customer lifetime value tools, including RFM 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!