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Research Paper | Data Knowledge Engineering | Volume 12 Issue 12, December 2023 | Pages: 1266 - 1268 | United States
Optimizing Digital Decision - Making: A Comprehensive Study on A/B Testing in Digital Analytics and Efficient Organizational Implementation
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
How to Cite?: Sneha Satish Dingre, "Optimizing Digital Decision - Making: A Comprehensive Study on A/B Testing in Digital Analytics and Efficient Organizational Implementation", Volume 12 Issue 12, December 2023, International Journal of Science and Research (IJSR), Pages: 1266-1268, https://www.ijsr.net/getabstract.php?paperid=SR231214233940, DOI: https://dx.doi.org/10.21275/SR231214233940