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Informative Article | Science and Technology | Volume 11 Issue 6, June 2022 | Pages: 1969 - 1972 | India
Data - Driven Design Optimization: A/B Testing in Large - Scale Applications
Abstract: In the rapidly evolving landscape of digital interface design, A/B testing has emerged as a crucial tool for optimizing user experience and business performance. This paper delves into the methodologies and impacts of A/B testing in large - scale applications, providing a comprehensive analysis of its role in enhancing user interface design. Through empirical data and case studies, the paper highlights the significance of A/B testing in informed decision - making and improving user interaction. The research methodology encompasses a blend of qualitative and quantitative approaches, offering insights into the practical challenges and opportunities in implementing A/B testing strategies. The findings underscore the importance of A/B testing in driving data - driven enhancements and its pivotal role in the design and development of high - traffic web applications. This paper serves as a valuable resource for designers, developers, and business strategists seeking to leverage A/B testing for optimal user engagement and business growth.
Keywords: A/B testing, large scale applications, Data - Driven Decision Making, Controlled Experimentation
How to Cite?: Satish Kathiriya, Suraj Kumar, Mahidhar Mullapudi, "Data - Driven Design Optimization: A/B Testing in Large - Scale Applications", Volume 11 Issue 6, June 2022, International Journal of Science and Research (IJSR), Pages: 1969-1972, https://www.ijsr.net/getabstract.php?paperid=SR24212165200, DOI: https://dx.doi.org/10.21275/SR24212165200