RFM Analysis
Last updated
Last updated
Usually, we segment customers based on events they perform like Abandoned Carts, Did Not Purchase in the past few months, and so on. But when it comes to segmenting all your customers based on activities they perform on their entire life cycle, the best way to do it is using RFM analysis.
RFM (Recency, Frequency, and Monetary) analysis is a marketing technique used to rank and group customers into different segments based on how recently they have purchased, how frequently they are purchasing, and how much they are spending.
The RFM technique assigns each customer a numerical score based on these factors to provide an objective analysis. RFM analysis is based on the marketing theory that "80% of your business comes from 20% of your customers".
What Are the Benefits of an RFM Analysis?
RFM analysis helps you group your entire customer database and helps you improve customer retention while increasing the overall customer lifecycle value. With RFM analysis, you can get answers that matter the most to your revenue growth:
How many customers we may lose this month? How much revenue were they generating?
How many customers are close to being our loyal customers?
How much revenue our loyal customers are generating?
RFM analysis gives a score to each customer based on three factors: recency, frequency, and monetary.
Recency: How recent was the customer's last purchase?
Frequency: How often customer made the purchase in a given period?
Monetary: How much money did the customer spend in a given period?
Based on the above three factors, a score from 1 to 5 is given to each customer, with 5 being the highest. The collection of these three parameter values for each customer is called an RFM segment/group.
Instead of simply using an overall RFM average value to identify the best customers, you can use RFM analysis to identify segments of customers with similar values called RFM segments.
You can use these segments for targeted marketing campaigns on different marketing channels. Some examples of customer types include:
Can Not Lose Them: Users who were active at one point in your site/app, but haven’t been back recently - Strong candidates to re-engage.
At-Risk: Users having above-average frequency but low recency - Strong candidates to re-engage.
Hibernating: Users having the lowest recency and frequency scores. You may lose these customers.
Loyal Customers: Users with the highest frequency of use with strong recency.
Champions: Most active users, having the highest recency and frequency scores.
Need Attention: Most active users, having the highest recency and frequency scores.
Let's take a look at this uber-cool feature where you can automatically target a particular segment in your RFM analysis. In our example here we would like to send out communications to those customers who are in the 'Potential Loyalist' Segment. Now, why would we lose out on an entire group of customers who can become our loyal customers?
Here is how we create the Potential Loyalist Segment
Click on 'Customers' on the Menu Tab
Select 'RFM Segments'
Select the event for RFM analysis, in our example, we are going to click on 'Purchased' and change the timeline to 'last 6 months'.
You will now see the RFM analysis for that period
Hover your cursor over the required segment, in our example, we will hover over the 'Potential Loyalist' block
Click on 'Create Segment' on the pop-up and you are done!
Now that we have our segment, let's go ahead and automate it.
Click on 'Customer Enters/Exits Segment', and select the segment of your choice. In our example, we are going to use the 'RFM - Potential Loyalists' segment that we created from the RFM Analysis.
as per your requirement.
Now that you have your template in position, click on the .
You're all done! You just have to review the settings and .
