A/B testing tools, compare the two versions (control and variant) of webpage or content to determine the better performing and appealing version. These tools aim to optimize engagement and conversion goals by deploying multiple versions of digital content in real time. Traffic is split at random so that each group sees either version of A/B. By dividing the traffic into two groups, marketers can measure the impact of a change on a predefined goal, such as click-through rates, conversion rates, or any other key performance indicator. Statistical analysis combined with segmentation data is used to improve actions taken by visitors/users across the customer life cycle. A/B testing tools are used by marketers and web developers to make data-driven decisions for product and marketing strategy.
Gartner defines personalization engines as technology that enables marketing professionals to identify, set up, conduct and measure the optimum experience for an individual based on knowledge about them, their intent and context.