Forecasting in retention-marketing based on rfm-analysis

The article presents the results of a study on the features of forecasting retention marketing indicators using RFM-analysis as a behavioral customer segmentation tool. The relevance of Retention strategies in a highly competitive and digitalized business environment is substantiated, and their financial efficiency compared to customer acquisition strategies is demonstrated. Basic and derived retention marketing metrics are analyzed, and their role in forecasting and managerial decision-making is defined. It is shown that prior customer segmentation using RFM criteria enables the formation of relatively homogeneous customer groups and the application of differentiated forecasting approaches depending on the type of marketing strategy, including sustaining, stimulating, and developing marketing. Methodological approaches to forecasting based on time series analysis, seasonality adjustment, and A/B testing of marketing campaigns are proposed. Special attention is paid to the practical use of empirical data, industry benchmarks, and experimental results to improve the accuracy and reliability of forecasts. The obtained results can be used to enhance the effectiveness of marketing strategies aimed at customer retention and long-term business development.