How To Use RFM Analysis Segmentation To Boost Your Business By 3X

 

 

 

RFM Analysis

 

 

RFM Analysis is a marketing technique used to quantitatively determine which customers are the best ones by examining their shopping behavior – how recently a customer has purchased (recency), how often they purchase (frequency), and how much the customer spends (monetary). RFM analysis is based on an extension of Pareto’s principle which says that “80% of your business comes from 20% of your customers.”

Customers who have purchased more recently, more frequently, and have spent more money, are likelier to buy again. But those who haven’t, are less valuable for the company and therefore, likely to churn. RFM stands for:

 

RFM Analysis

 

  • Recency – How recently did the customer purchase?

Recency is the most important predictor of who is more likely to show loyalty towards your brand. Customers who have purchased recently from you are more likely to purchase again from you compared to those who did not purchase recently.

  • Frequency – How often do they purchase?

The second most important factor is how frequently these customers purchase from you. The higher the frequency, the higher is the chances of such customers making a repeat purchase.

  • Monetary – How much money do they spend ( average basket value )?

The third factor is the amount of money spent by these customers on their purchases. Customers who have spent higher are more likely to buy again compared to those who haven’t. By giving points for various hierarchies, you can easily find out who your best customers are.

 

 

DID YOU KNOW?

 

RFM Analysis

 

 

RFM Analysis

 

How does it work?

 

To perform RFM analysis for your customers, each customer is assigned a score for their recency, frequency, and monetary value, and then a final RFM score is calculated.

Recency score is determined according to the date of their most recent purchase with your store. The scores are attributed based on the values of each parameter. Betaout’s RFM Analysis follows a category system of 0 to 9, score of 9 being the highest. In this case, customers who purchased within the last one month have a recency score of 9, customers who purchased within the last 1-2 months have a score of 8 and so on.

 

RFM Analysis

 

 

Similarly, the frequency score is calculated based on the number of times the customer has purchased in a given period of time. Customers with higher frequency receive a higher score.

 

RFM Analysis

 

 

Finally, customers are assigned a score based on the amount of money that they spent on their purchases. For calculating this score, you may consider the actual amount spent or the average spent per visit.

 

RFM Analysis

 

 

By combining these three scores, a final RFM score is calculated. The customers with the highest RFM score are considered to be the ones that are most likely to respond to your communication. In Betaout’s RFM Analysis, the RFM score range from 0 to 27. Customers with a score of 27 are your best customers.

Once you’ve calculated the RFM scores, you can create segments of customers based on their RFM scores to easily identify their relationship with your brand. Betaout uses the following framework to sort customers based on their RFM score:

 

 

RFM Analysis

 

 

TYPES OF CUSTOMERS AFTER RFM SEGMENTATION

 

 

RFM Analysis

Customer Segment Description
Champions Customers who bought recently, frequently and spent the most amount of money.
Loyal Customers Customers who have shown loyalty towards your brand by purchasing recently, frequently and spent a good amount of money.
Potential Loyalist Customers who have recently bought from you, but spent a good amount and made more than one purchases.
New Customers Customers with the highest of recency but made a purchase only once.
Promising Customers who made a fairly recent purchase, but haven’t spent much or made repeat purchases.
Customers Needing Attention Customers with above average frequency and monetary value but may not have bought from you recently.
About To Sleep Customers with below average recency, frequency and monetary score.
At Risk Customers who used to buy frequently with high monetary value, but haven’t made a purchase from a long time.
Can’t Lose Them Customers with high value attributing to their frequency and monetary score, but have very low recency score.
Hibernating Customers who purchased a long time back, spent low amount with a low frequency.
Lost Customers who have the lowest recency, frequency and monetary value.

 

RFM Analysis and Segmentation is a sophisticated technique, using which Betaout clients have been able to segment their customers and hyper-target their marketing efforts to these segments. RFM analysis as a customer segmentation technique can help retailers maximize the return on their marketing investments. Following are the overall results that Betaout has been successful in generating for its customers: Customer Segmentation is the bedrock of any successful and effective marketing campaign. It would be a waste of marketing spend if, for example, an ad campaign is targeted to all the thousands of your customers. Such an untargeted marketing promotion is unlikely to have a high conversion rate and may even hurt your brand value.

 

  1. Increase in frequency of purchase by 2.2X
  2. Increase in total revenue by 3X
  3. Increase in Average Basket Value by 3.1X

 

 

RFM Analysis