Artificial intelligence (AI) Powered Strategies for optimizing A/B Testing

Marketing landscape in the recent times, optimization of digital marketing tools and campaigns has greatly pushed major organizations to change their strategy from traditional marketing. A/B testing has been a trusted methodology for marketers to compare different versions of content, layouts, or provide as well as evaluate on the key elemental factors that resonates the best to the target audiences. However, traditional A/B testing has its own limitations and is likely to undergo changes with the influence of AI. This paper intends to do a comparative analysis of performance of AI powered A/B with that of traditional A/B testing. To compare the performance of the A/B testing tools, two sample landing pages were created for testing. Both the samples were of similar topics to ensure fairness of the test. In one of the sample landing pages traditional A/B testing was implemented and in another, the AI-powered A/B tester was implemented. Both the sample landing pages and their test variants were tracked for 10 days with the help of Google Analytics to ensure the correctness and reliability of the data. Each sample page were presented with a total of 3000 people via online medium’s aid. Upon following the parameters that were employed for assessing the performance of A/B testing tools such as- total number of viewers viewed; Bounce Rate; Time spent on page; Conversions and conversion rate. Results showed AI-powered A/B testing showcased significant reduction in bounce rate and conversely increased the conversion rate greatly when on comparison to that of traditional A/B. From the achieved results, it appeared evident that landing page using AI-driven A/B testing tool outperformed traditional tool with respect to assessment of all key metrics that were taken for consideration. Through deploying enhanced performance using AI-driven A/B tool clearly proved effective with the processes carried out swift and efficient. Some major metrics namely conversion rates and views were higher with AI A/B testing. In conclusion, the study demonstrated that AI-powered A/B testing provided effective optimization means for engaging visitors alongside with prompting desired actions, thus making it a superior tool for digital market optimization.