A/B Split Test is a method of comparing two different webpages or app to determine which one performs better for a specified conversion goal. It is also called A/B Testing or Bucket Testing.
The testing enables you to make data-focused decisions through a statistical engine, in order to have positive results with change producing. This change may be a headline, a button, or a complete redesign of the webpage.
A/B testing framework to process A/B Testing is given below;
Data Collection: Provide data for webpages with low conversion rates or high but decreasing conversion rates to improve those pages.
Goal Identification: Point out your conversion goals (such as increasing click rate, email signups or clicks to product purchases).
Hypothesis Generation: Explain why you thnink they would be better than the current versions.
Variation Creation: Make the wanted changes in your website or in your mobile app (such as changing colors, elements on the page, revealing navigation elements or customizing).
Conduct Experiment: Create your experiment and encourage your visitors to participate. These interactions will be then used to measure the performance of each page.
If you run a split test with multiple URLs, use rel="canonical" to prevent Googlebot from getting confused by similar versions of the same page.
If you run a split test that redirect the original URL, use 302 (Temporary) Redirects rather than 301s (Permanent) to enable Google keep the original URL.
You need to avoid conducting experiments that are unnecessarily long and that do not seem necessary.
1. A media company might want to increase readership, increase the amount of time readers spend on their site, and amplify their articles with social sharing. To achieve these goals, they might test variations on:
Email sign-up modals
2. A travel company may want to increase the number of successful bookings are completed on their website or mobile app, or may want to increase revenue from ancillary purchases. To improve these metrics, they may test variations of:
Homepage search modals
Search results page
3. An e-commerce company might want to increase the number of completed checkouts, the average order value, or increase holiday sales. To accomplish this, they may A/B test:
4. A technology company might want to increase the number of high-quality leads for their sales team, increase the number of free trial users, or attract a specific type of buyer. They might test:
Lead form components
Free trial signup flow