Optimizing User Experience in High-Traffic Financial Web Applications Using Analytics
DOI:
https://doi.org/10.15662/IJEETR.2023.0505008Keywords:
Analytics-Driven UX, Enterprise Web Systems, Financial Applications, User Experience Optimization, High-Volume Platforms, Behavioral Analytics, Data-Driven Design, FinTech ArchitectureAbstract
Financial web systems that operate on a high volume have tight performance, reliability, and regulatory limits and cater to large and diverse user base. To achieve optimal user experience (UX) in these settings, user experience refinement is not enough, but rather data and analytics-informed architectural choices. In this article, the authors analyze analytics-based UX optimization in large-scale financial web applications, where real-time behavioral data is used to discover the points of friction, decrease abandonment, and enhance the efficiency of the systems.
The paper discusses the implementation of event-based analytics into frontend processes to log interactions by the users, create behavior, and drop-off trends at scale. Such insights are converted into specific UX and performance enhancements, such as simplifying work flows, providing better validation feedback, and enhancing interaction flows. Implementations at the production level show significant improvements in submission accuracies, submission completion, and customer satisfaction and decreases operational loads in the support systems. The results indicate that analytics-based UX optimization is an important architectural feature to develop robust, user-centric financial systems in enterprise environments with high traffic.
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