RFM analysis is a customer analysis method, and simply put, it is a technique for grouping customers using three indicators. The
reason for grouping is that by organizing customers into groups and understanding the characteristics of each group, it becomes possible to take a marketing approach that is appropriate for each group .
I think you can understand that taking an approach that suits the characteristics of each customer will naturally increase the chances of turning customers into loyal customers, and is more efficient, rather than taking the exact same approach to every customer.
The ” RFM ” in RFM analysis is an acronym of three English words
That is what it means.
In RFM analysis, we use these three whatsapp number list indicators to classify customers.
For example,
- Recently purchased the product, has purchased it many times in the past, and the total purchase amount is high
- I use the service frequently, but the amount I pay each time is low
- I previously purchased a high-priced item, but haven’t used it for over two years.
Using such customer information, we will set specific criteria for dates, periods, and amounts, and group customers accordingly
. As a result of grouping, there are various what are the new features in google consent names for each customer, such as “good customers,” “loyal customers,” “recurring customers,” “dormant customers,” and “new customers,” but it is important to label them with names that are easy for everyone to understand.
Benefits of performing RFM analysis
As mentioned above, the biggest benefit of performing RFM analysis is that it allows you to approach customers according to their type and characteristics
. For example, the approach method will naturally be different for customers who purchase products repeatedly, spend a large amount in total, and contribute significantly to sales, compared to customers who have not used the service for a long time.
In order to get customers to purchase products, various marketing measures are implemented, such as mailing direct mail and catalogs, email marketing such as newsletters and step emails, push notifications such as app push and betting data web push, running campaigns, etc. However , if the same measures are implemented for everyone regardless of the customer’s purchase history, the response will decrease, and a lot of money and effort will be wasted, resulting in a significant drop in cost performance.
Therefore, by clarifying who are “good customers,” “new customers,” and “dormant customers” through RFM analysis, it becomes possible to prioritize spending and time on customers who are likely to lead to increased sales and new customers .
