Why use RFM analysis for individual user profiling? Learn what it is and how it works in the context of customer segmentation and identifying the best ones by continuing to read our column User Profiling Pills .
Segmenting one’s user base, according to buying behaviors is critical to a winning marketing strategy. Even more important for a business is to identify the best customers and reward them through targeted and personalized actions of loyalty. RFM analysis, recency, frequency, monetary, is a well-known marketing technique to segment one’s customer base quickly and easily, and identify the most “valuable” customers. Many times, the focus within companies, is more on finding new customers than retaining current customers, neglecting and forgetting the value they generate for their business.
RFM analysis for user profiling: how does the model work?
The RFM model rests its foundation on the Pareto model, according to which 80 percent of revenue is generated by 20 percent of its customers. Therefore, it is important to identify the best customers and retain them. According to the RFM method, much more responsive and responsive to promotions and communications, and consequently to purchase, are those customers who have bought recently, more frequently and spent more in a particular time period. Using this method, it is possible to identify a small but more qualified number of users to contact. In this way it is more likely to achieve equal or greater revenue than if the entire Audience had been involved, significantly reducing marketing costs. With the RFM method, an individual score is assigned to the customer, calculated on the basis of three metrics:
- Recency: the time since the last purchase; according to the model, customers who have purchased more recently are more sensitive to promotions than users who have purchased less recently.
- Frequency: the number of purchases made by a customer; repeat customers are more receptive than occasional customers.
- Monetary: the customer’s total spending in the reference period; those who spend more are more receptive than those who spend less.
Once the various RFM thresholds have been identified, the planning and configuration of the various marketing activities customized by segment can proceed. The marketing and sales strategies will have to be different according to the segment they belong to. If the user is on the “Top Users” cluster, loyalty activities and campaigns will have to be planned and implemented. Conversely, if they are “At-Risk Users,” they will have to be solicited through re-engagement campaigns.
RFM matrix: conclusions
f we go deeper into what profiling is in marketing, we will find out how the RFM matrix is a great tool to put it in the field. With a good rfm analysis on your customer base, you can improve your relationship with your most loyal customers, as well as optimize expenses and costs used in non-personalized marketing strategies.
