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What is A/B Testing and how it impacts business?

What is A/B Testing and how it impacts business?

A/B Testing or split testing is an approach to have a comparison between two versions of a concept to understand which one is better and more effective. In this digital age, it has turned out to be a useful option for businesses. It is used in the implementation of two versions of the same marketing asset such as social content, display ad, marketing emails, or web pages, bearing just one variable element. This helps in choosing the option that stands out . It will then become easier for an entrepreneur to take the right steps, by selecting the right choice.

Let’s take an instance – a landing page can be provided with two versions of the call-to-action (CTA) content. As they are run at the same time for data collection, the performance quotient will help in choosing the right version. If appropriately implemented, its impact is the reason for 10,000 A/B experiments are performed every year by business tycoons like Google, Facebook, Amazon, and so on.

How the A/B Testing Process Works?

It is essential to set the baseline properly as you start.  A hypothesis needs to be created based on the current appearance of the app or the web page. For example, if the CTA tells “Buy Now” then in the hypothesis, you can change it to something like, “Click to Proceed” to see if it yields better results. As the hypothesis is created, a second version of the app or the web page should be made.

As the two variations are created, the baseline and the hypothesis are ready for testing. The next step would be segregating the audience. There are a few approaches to this. If you have decided to test it over your mailing list, then two segments of users should be created, and then the list should be split randomly and share among the users in the two sections. Next, the results should be captured and analysed to check if the hypothesis is valid or not.

5 Reasons Why A/B Testing Is an Essential for Every Entrepreneur

1.      Minimised Bounce Rate

A/B testing is a great option to find a solution for reducing the scary bounce rate of your website. The main reasons for bounce rate include irrelevant content and poor user experience. The visitors open your content page from search results finding the title relevant to their search. If they are unable to find useful information, they search pages again and your page bounces.

The tastes and preferences of customers keep changing, so A/B testing is needed. It will help you to test the different landing pages to see which one engages a user better. Based on the analysis, you can improve the pages so that it resonates with the audience well. It also helps in determining the audience behaviour in a better way.

2.      Improvement of Engagement in the Content

A/B testing helps in the evaluation of the content and offers an option to detect which version yields a better result. It will be in terms of more clicks, likes, shares, and visitors converted to customers. The winning version impacts content engagement in a positive way.

3.      Enhanced Conversion Rate

A/B testing helps in reducing the bounce rate; it helps in optimising the conversion rate as well. Multiple versions of the same element in the website can be tested to zero in on the best version.  User experience improves, bounce rate diminishes and conversion rate increases with a successful A/B testing approach.

4.      Ease of Analysing Date

A/B Testing is the most convenient, effective, and accurate way to evaluate the results as it offers straightforward metrics.

5.      Minimised Risk

A/B Testing leads to decisions made based on accurate data and not subjective opinions. The risk factor is eliminated to a great extent. The testing also opens up an approach to make a change in the page, other than modifying every detail in it. So, even if the test doesn’t yield favourable results, the whole page and the conversion rate won’t get hampered much.

An entrepreneur can tweak the business website to its full potential by implementing the A/B testing approach.  So, try it, and it is well worth your time and effort.