Optimizing Digital Decision - Making: A Comprehensive Study on A/B Testing in Digital Analytics and Efficient Organizational Implementation

Sneha Satish Dingre

Abstract: This paper delves into the methods of A/B testing for organizations seeking to enhance and optimize the user experience of their digital products. The paper discusses A/B testing methods, including Multivariate A/B Testing, Bayesian A/B Testing, Personalized and Targeted Testing, and Sequential Testing. The interaction between various teams and the collaborative efforts required among them, such as product, data science and analytics, development, UX/UI design, marketing, and leadership, to successfully implement and interpret A/B tests is also described in this paper. Key performance indicators (KPIs) areproposed for measuring the successful execution of A/B testing processes throughout various stages.

Keywords: A/B, testing, digital, analytics, product