In a time of intense competition and increasingly demanding customer expectations, it's crucial to seek ways to effectively enhance your website's performance. What if we told you there's a tool that can significantly assist you? This tool is AB testing. But what exactly is it, and how can it help you?
AB tests are experiments in which two versions of a webpage or element are compared to determine which one has a better impact on conversions. Variant A is considered the control, while variant B is the test. The goal is to find out which variant produces better results, such as increased sales, higher conversion rates, or other key performance indicators.
The AB testing process usually starts by selecting a specific element to test, such as a shipping information widget placed in a product description. Two different versions of this page are then created: version A, which includes the original element, and version B, which contains the new element (with the widget). Visitors to the website are then randomly divided between the two variants, and their performance is monitored to determine which variant achieves better results.
AB testing can be a highly effective tool for increasing conversions and purchase success rates. Imagine you're running an online store and you want to determine if certain widgets can boost sales. With AB testing, you can easily compare the original version of the page with a new version containing the widgets.
If you discover that version B (with the widgets) has a significantly higher conversion rate and purchase success than version A, you have clear evidence that widgets have a positive influence on customers and their purchasing decisions. This enables you to optimize the content and design of your pages based on real data and achieve better outcomes.
With Pobo Page Builder, we have conducted several AB tests with very interesting results. For instance, for the e-shop H2O-cool.cz, we launched an AB test where we streamlined the descriptions and added widgets in group B, such as shipping options, delivery speed, and contact possibilities with the seller. The result was a 21% increase in completed orders.
Even minor adjustments can have a significant impact. For example, on the e-shop Daka.cz, we conducted an AB test in a relatively short time frame, where we added information about self-delivery and communication options with the seller to group B. The e-shop subsequently experienced a +9% increase in completed orders.
Without conducting tests, it's impossible to definitively determine what works and what doesn't. AB testing represents a fundamental element of online business that helps us make decisions based on data, not assumptions. This practice not only reveals successful strategies but also proves that even small changes can have a substantial effect. AB tests, therefore, represent a crucial direction for the future of e-commerce.
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