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RFM in Business Strategy


RFM Analysis For Successful Customer Segmentation


Analysis RFM in Big Data
RFM (Recency, Frequency, Monetary) analysis is a proven marketing model for behavior based customer segmentation. It groups customers based on their transaction history – how recently, how often and how much did they buy. RFM helps divide customers into various categories or clusters to identify customers who are more likely to respond to promotions and also for future personalization services. RFM analysis evaluates which customers are of highest and lowest value to an organization based on purchase recency, frequency, and monetary value, in order to reasonably predict which customers are more likely to make purchases again in the future.

What are Recency, Frequency and Monetary?
·       Recency      : How much time has elapsed since a customer’s last activity or transaction with the brand.
·       Frequency         : How often has a customer transacted or interacted with the brand during a particular period of time.
·       Monetary           : Also referred to as “monetary value,” this factor reflects how much a customer has spent with the brand during a particular period of time.
RFM analysis is popular for three reasons:
  • Utilizes objective, numerical scales that yield a concise and informative high-level depiction of customers.
  • Simple, marketers can use it effectively without the need for data scientists or sophisticated software.
  • Intuitive, the output of this segmentation method is easy to understand and interpret.
RFM work system
RFM analysis classifies customers with a numerical ranking for each of the three categories, with the ideal customer earning the highest score in each of the three categories. So, for example, depending on the purchase cycle of your company's product or service you might evaluate customers for recency on a scale of 1-10, with a score of 10 indicating the customer had made a purchase from your company within the last month, and a score of 1 indicating that their last purchase was 10-12 months prior.
Once a company has decided on its 1-10 scale for each of the three categories, it can review its CRM and give each customer a score for each category. Then, by adding up the three combined scores, companies can run an RFM analysis to determine which companies are most likely to buy again soon, and use that information to prioritize how they're reaching out to and creating value for those high-value customers.
  
Recency
Frequency
Monetary
R-Tier-1 (most recent)
F-Tier-1 (most frequent)
M-Tier-1 (highest spend)
R-Tier-2
F-Tier-2
M-Tier-2
R-Tier-3
F-Tier-3
M-Tier-3
R-Tier-4 (least recent)
F-Tier-4 (only one transaction)
M-Tier-4 (lowest spend)

An RFM analysis helps you find commonalities and differences between customers who repeat purchase and customers who don't to help you learn where there are gaps in your customer experience.

SYLVIA DIVARDA
106218079
https://www.optimove.com/learning-center/rfm-segmentation
https://www.putler.com/rfm-analysis/



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