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A/B Test Validation Using Google Analytics

There are several tools and techniques to improve the performance of a website. A/B testing is one of those techniques. In A/B testing, two or more page layouts are created for the same page address. They have similar core functionality but vary in how the website is viewed by the visitor.

In order to increase the number of visitors to a certain website, it has to offer the friendliest user experience. A/B testing contributes in attaining this, where the website can test and choose the most effective way to present its data. For added efficiency, Google Analytics can be used for the validation of A/B test.

Google Analytics

Google analytics is a tool for search engine optimization. It achieves this by providing essential statistics and data for websites. Anyone having a Google account has access to this service. It is the most extensively used web analytics software in the world. Merging this tool with A/B testing gives an enhanced performance growth mechanism that is tough to beat with anything else out there.

The idea behind A/B testing is sound and has been used for professional Internet marketing for a long time. Google Analytics can help you take the process of A/B testing to the next level by critically analyzing what works and what doesn’t.

A/B Testing

The first time you create an experiment, Google will ask you to select between multivariate testing and A/B testing. With an A/B setup you can check two different styles of the same page. For example, if you need to modify the header text and color of your upload button, or reposition some ad banners, then this method is for you. The multivariate technique is slightly easier where you can improve limited key areas of the webpage.

With Google Analytics Experiment, you are not restricted to just two hypotheses. Instead, you may set up several test cases. A controlled approach to refining your conversion rates needs to be a continuously progressive process. Its three most important phases are measurement, prioritizing and testing. Each stage has an objective and purpose that leads to the next stage in the cycle.

The winning hypothesis is ascertained algorithmically over a period of time, which usually ranges from about two to four weeks. The period varies depending on several factors including the traffic volume on the site, the performance of the hypothesis and the rate at which the primary hypothesis changes.

If the test comes up with a prominent winner and it’s not the original, a few steps need to be taken. Firstly, substitute the original template or data with the new variations and then erase the experiment code from the template. Doing this allows us to validate our data using Google Analytics.

Google Analytics Experiments is a free A/B split testing tool that can be easily set up to help you make confident decisions about your website’s design, messaging, and content. Google Analytics validates A/B testing to provide optimized SEO for your particular needs. It is a powerful tool that you can use to make your website better at achieving your organization’s marketing objectives.

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