One of the main pillars of the customer journey is the personalized communication. Nowadays, we are all familiar with the essential importance of the phrase; “I know my customer”, which is the prerequisite for creating personalized consumer experiences.
Direct-to-customer (DTC) communication with the brand is a must for all the leading brands. Although before we begin with creating the marketing activities, it is important to have a clear view of the targeted customer.
RFM and MTV analysis are advanced segmentation methods through which you can target specific clusters of customers with communications that are much more relevant for their behavior. These methods make it possible to categorize customers into homogeneous groups.
The RFM analysis model stands for three basic metrics: Recency, Frequency and Monetary. It is an analytics technique used to determine quantitatively which customers are closest to a brand, so those are more profitable. It is based on an examination of the number of months since the last purchase, the number of made purchases, and the total amount of spent money, to predict which customers are more likely to make purchases again in the future.
RFM analysis is an important tool for understanding customers’ buying behavior. Overall, the RFM metrics are key indicators for marketers to realize if a consumer stays close to the brand and evaluates which customers are of highest and lowest value to an organization based on purchase recency, frequency, and monetary value.
The MTV (Multivariate) method is all about analyzing multiple variables from the customer database to get a deeper understanding of consumers’ behavior and categorize them into homogeneous groups. The knowledge of customer profiles can lead to targeted communications between brand and consumer.
Based on the MTV method, which precisely examines many variables, a marketeer can gain a holistic overview of the customers’ behavior and utilize it to predict their response to future actions.
For example, members of a rewards program can be categorized by analyzing their behavior based on different factors, such as spending on a particular product or in a particular period (that of discounts). Thus, groups of customers are created, such as “brand lovers”, who are characterized by their close relationship with the brand or a product. If as marketers we know which of our customers belong to this group, then it is more effective to offer them a specially designed experience, related to their favorite brand or product, rather than a regular discount.
RFM and MTV method analysis is preferred to be performed with automated data analysis. The Qivos Customer Insights solution provides business executives with valuable knowledge for the end consumer. Utilizing this model of analysis, it is possible to generate reports, even monthly, on the performance of the promotions, as well as to provide specific suggestions for the next steps.
Author: Fani Charmpi , Qivos’ Co Founder and COO