Automated A/B Testing to Improve Conversions

Opting for automated AB testing is worth the hype. Its statistical analysis is proven to significantly increase the conversion rate of any page or website. It leaves no room for guesswork and increases the overall performance of applications better than the remaining tools. What’s more? To know more, let us scroll down and grab more insights in this blog!

Mobile applications, websites, blogs, etc, are today's means of providing information. They look so simple, but behind the scenes, a lot of work goes into designing everything from a simple search bar to a complex mobile app. Yet the hard part is compelling the audience to utilize them. This process becomes easy if automated AB testing is the driving engine of your work.

The AB testing process in software quality assurance promotes a culture of experimentation when developing marketing strategies. Similarly, integrating such tools into the existing system also guarantees driving good traffic. Further, it also improves the conversion rates even with minor changes.

But how? To have clear insights, read our guide on automated AB testing below!

What is automated AB testing? How does it work?

A/B testing is an online experimenting process in web management services that helps determine the better version amongst two or more variations of an element. It statistically selects variants that drive good traffic. But comparatively, automated A/B testing works even more accurately.

The global AB testing software market has been predicted to be worth $1.08 billion by 2025 at a CAGR of 12.1%. In addition, websites and landing pages are at the top of the list for A/B testing areas.

Several companies, including small-scale and large-scale businesses, approach the automated testing process by following common workflow steps. First, they meticulously plan out the tests and platforms for the automation to be carried out. As the next step, they perform the required tests.

Following this, when all the A/B testing requirements are met, the results are displayed and analyzed to draw suitable conclusions. As the last step in A/B testing, the final call is made by the team to measure criteria for testing as per their market needs.

Now that you have understood the concept of automated AB testing, let us go through its different types and their usage.

What are the different types of automated AB testing?

As we move ahead, remember that each type of A/B test has numerous benefits. Certain types may work better for you, depending on your desired changes. So, here is a list of the various kinds of A/B testing in software engineering:

Split testing

In this testing, the user receives different URLs or web pages. However, the split factor is hidden from them, whereas in the other tests, it is not. So, this is why split testing is best for significant changes, whereas A/B testing works well for significantly small changes.

A/A testing

A/A testing allows you to test two twin versions of an element. The traffic to the website is divided into two groups exposed to the variation. If the conversion rate of the two groups is the same, it's ideal. For different results, it helps to identify hidden bugs and possible errors.

Multivariate testing

MVT, commonly called multivariate testing, lets you simultaneously test numerous variations of one or more elements during the experiment. For instance, you can test different combinations of headers and product videos together. However, only significant variations produce stable results.

Bandit testing

Multi-armed bandit testing, also called a dynamic traffic allocation algorithm, helps in consequently redirecting the audience to ideal variation. Hence, the winning variation is ultimately chosen after testing page variations against different metrics.

Want to know the popular tools used for automated AB testing? In the next section, we will give you insights that help you choose the right tools.

What are the set of tools used for automated AB testing?

Based on your testing requirements, you can consider tools. As a result, they should be able to meet the business objectives and complexity of tests to run. Also, we can’t miss that some tools can perform manual and automated AB testing.

Google Optimize

Google Optimize is a free-source A/B and multivariate testing tool for enterprises. It's a part of the Google marketing platform that helps you improve your website and create personalized tools for attracting the audience.

Optimizely

Optimizely leads the mobile AB testing tools list due to its feature discovery and re-engagement strategies. You can also change your app’s behavior in real-time to a great degree of personalization without any help from the app store.

Kameleoon

Kameleoon offers a unified optimization platform beyond manual capabilities. It also supports various platforms and integrations for full stack and web. Moreover, it's backed with AI personalization to satisfy the user experiences in real-time.

Abode Target

It’s a complex experimentation software explicitly tailored for the enterprise market. It shows how effective the combination of your content and UX is. With its AI-powered automation features, you can personalize and test, irrespective of scale.

A report by Statista projects that the number of mobile phone users worldwide will reach 7.49 billion by 2025. Therefore, businesses consider mobile optimization significant to make it easy for customers to browse their sites using mobile devices.

With this set of A/B testing tools, let us now move on to the steps involved in automated AB testing.

How to perform automated A/B tests?

Did you know that over 50% of marketers use A/B testing in software engineering to boost conversion? As a result, when it comes to automated A/B testing, it becomes an irreplaceable tool in many fields. The steps to perform AB tests are as follows:

Defining the test strategy

Before running experiments, have a clear and consistent idea for the testing strategy. It should align with business objectives and customer needs, too. For example, fixing KPIs, sample size, choosing A/B testing tools, and testing methods are all that define your testing strategy.

Manifest a testing culture

Proper rules of testing and objectives of an automated AB test should be established to enhance team communication, as well as obtain unbiased insights. The other point is that the inclusion of more perspectives through a feedback loop can aid in constructing an innovative approach.

Testing platform

Scaling and automated AB testing are major challenges when dealing with multiple tests across various devices and channels. Therefore, the right testing platform will enable you to handle the process in a more efficient manner, as it can be automated and integrated into reporting and other tools.

Opt for statistical methods

Validity and reliability issues are another when performing the A/B tests. Thus, it is appropriate to use the statistical methods of Power Analysis, Frequentist Approach, and Bayesian Inference in order to test the suites and calculate optimal sample size and duration.

Automate and optimize the test cycle

Finally, you can also use testing tools such as Selenium or Cypress, enabling you to automate the testing process to predefined criteria and triggers. Also, these tools assist in the quick detection and determination of errors. Lastly, they help streamline the testing cycle for meaningful insights and great user experience.

Lengthy process. Isn’t it? But what about the mistakes to avoid? In the next section, we will give you clear pointers to keep in check before performing automated AB testing.

What are the mistakes to avoid in automated AB testing?

The AB testing process is flexible and repeatable, encouraging experimentation to optimize elements. However, some common misinterpretations do create an impact on the test results. Such mistakes to avoid are:

Tracking more metrics

If you track more than one metric simultaneously, it creates a risk of unreliability or wrong judgment. Errors can be missed during these tests. In other words, testing too many elements needs significant traffic, which is challenging.

Inadequate test time

The timing usually differs based on product size and variants. If the tests are discontinued before their course time, the performance assessment has the chance of causing jeopardy. Here is where the accuracy of results becomes questionable.

Testing during the least traffic

Usually, automated AB testing during the most and least traffic times shows a significant change in results. Besides comparing site results, between weekdays and holidays is not suggested. As a result, it leads to wrong assumptions.

Wrong sample size

The testing time is essential, but if the sample size is low or too large. In that case, A/B testing doesn’t guarantee reliable results. Also, splitting the traffic for multiple variations becomes tough.

Real-life case studies of automated AB testing

In real-life marketing scenarios, many industries use A/B testing due to their ability to increase audience engagement. So, let’s explore some of such examples:

Zalora

Founded in - 2012

Location - Asia

Zalora is one of the fast-paced online fashion retailing eCommerce stores. After optimizing the product pages and highlighting their reward sections, the checkout rate for their brand increased by 12.3% - thanks to the automated AB testing technique they opted for.

Ubisoft

Founded in - 1992

Location - Paris

Ubisoft is a leading French video game company. Their conversion rate increased to 50%, and lead generation increased by 12%. After their research, the team opted for the AB testing process and worked for three months to change their complex purchase process to a simple one.

Conclusion

A reasonable conversion rate and compelling visuals with scalable applications are necessary for businesses to skyrocket in today's competitive market. Advertisements and SEO may pose as increasing the website traffic. But the real magic happens by using automated AB testing. It has established itself as a means of boosting income for various companies. You would be undoubtedly aware by now that the A/B testing procedure is the best in its industry.

Related Articles

Nginx And A/B Testing

E-commerce Testing For Online Shopping

Develop A SaaS Product

Mobile Testing Techniques