GirGut: An AI-powered, developer-First AB testing platform mimicking natural selection for web application
1 CEO and VP of Engineering, scale.jobs 537 Payne Rd, Woodstock, GA, USA 30188.
2 CTO, scale.jobs 1-84, Beside Venugopala Swamy Temple, Rayanapadu, Vijayawada, AP 521241, India.
Research Article
World Journal of Advanced Research and Reviews, 2024, 21(02), 2035-2044
Publication history:
Received on 15 January 2024; revised on 23 February 2024; accepted on 28 February 2024
Abstract:
A high-quality product experience is becoming more important to consumers as a whole as a result of societal progress. The competition is constantly raising the bar for product specifics in their pursuit of a high profit conversion rate. Rapid, high-quality product iteration is essential for product providers looking to increase user viscosity and activity, which in turn increases the profit conversion rate. By inserting logs and analysing statistical data, A/B testing can determine which iterative strategy is more effective by conducting experiments on target users. This paper introduces GirGut, an innovative, open-source AB testing platform designed specifically for web developers. GirGut leverages artificial intelligence to generate and evolve test variants, mimicking the process of natural selection to optimize user engagement and conversion rates. By combining ease of use with powerful AI capabilities, GirGut aims to revolutionize the way developers approach experimentation and optimization in web applications.
Keywords:
AI-Powered; AB Testing; Web Applications; Product
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Copyright © 2024 Author(s) retain the copyright of this article. This article is published under the terms of the Creative Commons Attribution Liscense 4.0