Use data gathered through visitor behavior analysis tools such as heatmaps, Google Analytics, and website surveys to solve your visitors’ pain points. This increases friction and eventually impacts your conversion rates. Not being able to achieve their goals leads to a bad user experience. It can be a confusing copy or hard to find the CTA button like buy now, request a demo, etc. Whatever the visitor’s goal may be, they may face some common pain points while achieving their goal. It may be to understand more about your product or service, buy a particular product, read/learn more about a specific topic, or simply browse. Visitors come to your website to achieve a specific goal that they have in mind. Let’s see why you should do A/B testing: 1. These core conversion metrics are affected by some common problems like leaks in the conversion funnel, drop-offs on the payment page, etc. Meanwhile, media and publishing houses are also dealing with low viewer engagement. If B2B businesses today are unhappy with all the unqualified leads they get per month, eCommerce stores, on the other hand, are struggling with a high cart abandonment rate. If you’re not A/B testing your website, you’re surely losing out on a lot of potential business revenue. You can further use this collected data to understand user behavior, engagement rate, pain points, and even satisfaction with website features, including new features, revamped page sections, etc. Meanwhile, for B2B, it may be the generation of qualified leads.Ī/B testing is one of the components of the overarching process of Conversion Rate Optimization (CRO), using which you can gather both qualitative and quantitative user insights. For instance, in the case of eCommerce, it may be the sale of the products. The metrics for conversion are unique to each website. The version that moves your business metric(s) in the positive direction is known as the ‘winner.’ Implementing the changes of this winning variation on your tested page(s) / element(s) can help optimize your website and increase business ROI. Whereas B refers to ‘variation’ or a new version of the original testing variable. In A/B testing, A refers to ‘control’ or the original testing variable. A/B testing, also known as split testing, refers to a randomized experimentation process wherein two or more versions of a variable (web page, page element, etc.) are shown to different segments of website visitors at the same time to determine which version leaves the maximum impact and drives business metrics.Įssentially, A/B testing eliminates all the guesswork out of website optimization and enables experience optimizers to make data-backed decisions.
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