What is RFM Analysis and how can you use it to grow your business?
RFM (Recency, Frequency and Monetary Value) Analysis is a segmentation technique that's invaluable for growing your product business.
This article delves into what RFM analysis is and how you can leverage the power of RFM Analysis to target the right customers, at the right time, with the right message.
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 Segmentation 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 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 maximize 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".
What are the RFM Segments?
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
How are RFM Segments calculated?
RFM Analysis can be based on a data range of your choice but to get the most value out of your customer data, the ideal data range for RFM Analysis is 2-years worth of customer data. The entire customer based is analyzed 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.
The way in which customer data is assigned into the RFM Segments is relative to other customers in your dataset. For example, a Loyal Customer could be:
- Anyone in the top 60% of the combined monetary and frequency values, and
- Anyone in the top 40% of recency.
RFM 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.
How to derive actionable insights from RFM Analysis
Automated RFM Analysis constantly recalculates and re-examines your customer base, providing instant answers to questions like:
- Who are my best customers?
- How many customers are close to churning?
- Which customers should I targeted with a win-back offer?
- How many new customers have I generated recently?
With these answers to hand, businesses can leverage the power of RFM Analysis, targeting the right customers, at the right time, with the right message.
5 practical applications of RFM insights
- RFM Analysis helps you monitor your customers' spending behavior in real-time, allowing customer-facing teams to be more proactive and effective in their targeting and outreach.
- Automated RFM Analysis identifies new customers, so you know exactly who needs to be onboarded and converted into loyal customers.
- Predicted churn alerts help your team prioritize activity, allowing you to act quickly before it's too late.
- Marketing teams can leverage RFM Analysis to target customers with pinpoint accuracy - from win-back campaigns, to special offers.
- RFM Analysis takes the guesswork out of upsell and cross-sell, presenting relevant opportunities against each customer.
RFM Analysis creates predictable and repeatable growth every time.
RFM Analysis in Access CRM
Once integrated to an accounting, ERP or inventory system, businesses can better understand their RFM Analysis immediately using pre-built reports in Access CRM. These include:
Customers by RFM Segment - This automatically assigns your entire customer base to the most appropriate RFM category in real-time, so you know which customers to prioritize first, and how to focus your outreach.
Predicted Churn Alerts - Get a full list of which customers are most at risk of slipping away based on their spending behavior.