Changes in customer relationships

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<Three axes of RFM analysis> Recency: Most recent purchase date Frequency: Purchase frequency/number of purchases Monetary: Purchase amount In RFM analysis, each of the above factors is scored, and customers with higher scores are judged to be more likely to purchase. RFM analysis is commonly used to identify customers who are likely to make the next purchase and to sell to them more effectively. What can you learn from RFM analysis? Purchase date, purchase frequency (number of times), and purchase amount are all information that can be easily confirmed from the most recent purchase data.


By scoring and quantifying these, it is possible to azerbaijan telegram database efficiently identify customers who are likely to purchase. This is an effective analysis method if you want to increase sales in the short term. What RFM analysis doesn't tell us While RFM analysis can identify "customers who are likely to make a next purchase," it is not suitable for analyzing "customers who are unlikely to make an immediate purchase." It can be said that this analysis method is not suitable for customer development from a medium- to long-term perspective.


For a company to continuously increase sales, it is necessary to bring back customers who are on the verge of abandoning the business. By valuing customers who make repeat purchases without the company's efforts, and by approaching customers who are abandoning the business, there is a good chance that the number of repeat customers will increase. In addition to approaching customers who are likely to make a purchase in the near future, a perspective that takes a bird's-eye view of the entire customer base and develops them is required.