This article is devoted to the study of the use of data-based behavioral analytics models to optimize the activities of organizations in the context of digital transformation.

It considers examines how digital tools, behavioral models, and analytical methods can help improve employee productivity, optimize business processes, and make informed management decisions. The aim of the work is to identify the most effective behavioral analytics models and assess their impact on team performance using the example of Bereke Bank sales department. The study used two scientific methods: comparative analysis, which allowed us to compare different models of behavioral analytics, identify their strengths and weaknesses, and determine which tools use data most effectively to manage employee behavior; and systems analysis, which considers an organization as a complex interconnected system in which digital technologies, data, and behavioral The factors interact, creating a synergistic effect to increase overall productivity.

The article presents the results of a study that demonstrate that cluster and regression analysis make it possible to identify groups of employees with different levels of digital activity, predict the effectiveness of implementing digital tools and optimize the allocation of tasks.The system analysis showed that the integration of digital technologies, data and behavioral factors improves the quality of management decisions and contributes to the strategic development of the organization. The relevance of the research is due to the need for organizations to adapt to the digital economy, where data and behavioral analytics are becoming key tools for improving efficiency.

The article is of practical interest to the management of banks and other organizations interested in digital transformation and process optimization, as well as scientific value, providing a methodological basis for further research in the field of behavioral analytics and business digitalization.