Identification of user behavioral patterns in UI/UX design based on user log analysis

DOI: 10.31673/2412-9070.2025.040867

Abstract

The article presents an analysis of user log types that can be utilized to identify behavioral patterns in UI/UX interaction. A correspondence between characteristic user behavior models and relevant log data is established, along with a justification for their use in building objective UX analytics. The relevance of the study is driven by the need to shift from subjective interface evaluations to metrics based on digital interaction traces. The paper proposes a systematization of key user behavior patterns, each grounded in neuropsychological mechanisms — from scanning and cognitive economy to habit formation, frustration avoidance, and the pursuit of control. For each pattern, appropriate types of logs are identified that enable the detection or quantitative modeling of specific behavioral traits. In particular, login logs, activity duration, click paths, time to next action, scroll depth, and help-seeking events are described.
Tables mapping patterns to log types are provided, which support the structuring of behavioral analysis. The mechanisms of pattern formation are also justified at the level of the user's cognitive architecture. The proposed approach enables UX analysis based on actual interaction scenarios in digital products and lays the groundwork for implementing adaptive interfaces that respond to real user behaviors. The results of the study can be applied in the development of automated UX monitoring systems, behavior-driven design, and personalized interaction in information systems.

Keywords: user behavioral patterns; user interface; information system; user logs; UX/UI design.