To operate most effectively, contemporary companies need to understand their customers as thoroughly as possible, including their preferences, readiness to purchase, purchasing methods, loyalty, and so on. Therefore, research related to assessing customer lifetime value (CLV) is highly relevant. The main goal of this study was to develop an effective methodology that would enable companies to determine the value of their customers, make reasonable marketing decisions, and optimize customer relationships. RFM-analysis and its modifications were chosen as the research method, as it allows for classifying customers based on their purchasing behavior history, rather than solely on their social status, field of activity, psychological characteristics, and other factors. It was found that classic RFM-analysis is not always effective when customer relationships are more complex and long-term. As a result, the developed methodology involves the implementation of a modified approach to assessing CLV (MRFM-analysis) which takes into account such factors as purchase frequency, average order size, customer relationship duration, as well as customer satisfaction, loyalty, and engagement. The methodology was tested using an analysis of two-year purchase data from a B2B company. This resulted in the identification of homogeneous groups of the company's customers (segments) for each of which qualitative descriptions were provided, their lifetime value was assessed, and the most beneficial interaction methods were developed. A study for consumer dynamics was also conducted, which allowed to assess the effectiveness of cooperation with customer groups, identifying the most stable and volatile groups, and proposing measures to regulate interactions, including improving personalized service offerings.