A/B Testing: A Systematic Literature Review

• URL: http://arxiv.org/abs/2308.04929v1
• Date: Wed, 9 Aug 2023 12:55:51 GMT
• Title: A/B Testing: A Systematic Literature Review
• Authors: Federico Quin and Danny Weyns and Matthias Galster and Camila Costa Silva
• Abstract summary: Single classic A/B tests are the dominating type of tests. The dominating use of the test results are feature selection, feature rollout, and continued feature development. The main reported open problems are enhancement of proposed approaches and their usability.
• Score: 10.222047656342493
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: In A/B testing two variants of a piece of software are compared in the field from an end user's point of view, enabling data-driven decision making. While widely used in practice, no comprehensive study has been conducted on the state-of-the-art in A/B testing. This paper reports the results of a systematic literature review that analyzed 141 primary studies. The results shows that the main targets of A/B testing are algorithms and visual elements. Single classic A/B tests are the dominating type of tests. Stakeholders have three main roles in the design of A/B tests: concept designer, experiment architect, and setup technician. The primary types of data collected during the execution of A/B tests are product/system data and user-centric data. The dominating use of the test results are feature selection, feature rollout, and continued feature development. Stakeholders have two main roles during A/B test execution: experiment coordinator and experiment assessor. The main reported open problems are enhancement of proposed approaches and their usability. Interesting lines for future research include: strengthen the adoption of statistical methods in A/B testing, improving the process of A/B testing, and enhancing the automation of A/B testing.

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