The simultaneous onslaught of Internet and technology has changed the world as we know it. Today, data reigns as the king of it all and is the primary tool based on which key leaders make their decisions. Business instinct and opportunistic situations can only take you so far, and in this time of cutthroat competition, CEOs and business managers require concrete data to validate their findings. When it comes to most online situations, A/B testing tools are one of the best ways to receive access to actionable data insights within a quick time.
Today, A/B testing methodology is being used by savvy marketers around the world to gain unique insights into user behavior, increase website conversion rate, and generate better actionable data points based on which important changes can be made.
In the simplest of terms, A/B testing is a quick and sure-shot way to compare two different versions of a single product/service/element so as to figure out which one works better. According to most historians, the idea behind A/B testing is more than 100 years old. A/B testing is one of the main proponents in many life-changing hypotheses, and in its current form, the math behind the tests remain the same. Today A/B testing is mostly done online, in a real-time situation and on a much wider scale consisting of many different participants. A/B testing is also widely used by product developers and product designers to demonstrate how new features impact product onboarding, modals, user engagement, etc.
And yet, A/B testing is not as commonplace as it should be, especially when compared to other internet marketing techniques such as SEO, Web Analytics, etc. There are 3 types of A/B testing -
Before you embark on an A/B testing process, you need to decide what it is that you want to test. In case of a website, it is important to keep the goal of your website in mind. Different websites have different goals -
Once the goal has been set, you decide how the A/B test will help you evaluate performance. Since A/B tests are the simplest forms of randomized controlled experiments, you must estimate the sample size that will help you achieve any statistical significance. This would ensure that the results you see are actually viable and not just white noise.
The beauty about A/B tests is how easy they are to run, especially since one can run many simultaneous A/B tests so as to save time. Once the results are in, most companies use dedicated software to handle the calculations or assign someone with the know-how to perform the same. Most software programs give 2 results for the A/B testing methodology used: one for users who saw the test version, and another for users who saw the control version. The results may measure anything from clicks to page impressions and can be run many times in order to justify a major change.
The A/B testing methodology for the web is very simple to use and implement. Here we present the steps of A/B testing process which can then be implemented based on the variables you want to test for -
Begin by using tools such as Google Analytics to find the problems in your website conversion funnel. Whether you have exceptionally high bounce rate, or are facing issues with reduced number of clicks, background research can help you lay the foundation for the A/B test properly.
Once you have enough background data on your problems, you should go about collecting data from your website to find out all the possible hindrances to your website's performance. Try finding out pages with low conversion rates and calculate the number of visitors you will need to run the test effectively. Use tools such as visitor recordings, heatmaps, form analysis etc. to figure out why users are not converting. All this data would be helpful in running the test
You should take some time to set your conversion goals which in turn will help you define your objective clearly. Once done, you would have more clarity while determining whether the new version worked better than the older one. Your goals could be anything from checking how many people clicked your button to how many people checked an embedded product video.
So now both your goals and the metrics with which you will measure them have been set. The next step is to come up with ideas on how to improve your problematic feature or product. For example, if your website is currently without images, it would be good to test a variation of it with images to see how your customers accept it. Use insights from visitor behavior analysis tools as well to build your hypothesis for better conversions.
Begin your A/B testing process by presenting both the variations to your users and make sure to monitor the data generated closely. For example, A/B test your existing home page with a variation which has a larger CTA button which can be easily noticed by the user. Calculate the overall test duration based upon your total monthly users, current conversion rate, and the conversion rate you expect from the new variation.
Once the experiment has run the course, you need to analyze the results. Import the data generated into A/B testing tools which can easily tell you the difference in performance of both the variations. You can also easily find out if there was a significant difference in both the variations and how they were received by the user. If there was a clear winner based on the variations, you can actually go ahead and implement the same sitewide for better conversions.
Any website can benefit from the A/B testing methodology, as long as the reason you test for is quantifiable. When it comes to A/B testing for the web, more often than not, it is to increase conversion rates. Almost anything can be tested using the methodology for A/B testing, such as -
You can also run advanced tests such as testing for pricing structures, navigation and UX, etc.
A/B testing is the best way for individuals, marketing teams, and companies to make data-driven changes to their website which vastly change user experience for the better. A/B testing also allows one to think out of the box and understand why certain elements of a website's core experience work or do not work at all. Some of the many reasons why you should always A/B test include -
A/B testing allows you to see the effects of consumer preference in real time and allows you the luxury to roll back changes which were not accepted well. Some of the many benefits of A/B testing include -
At O2I, we have a proficient team of certified digital analysts and web optimization specialists who are specialized in a variety of different web analytics tools and testing methods including A/B testing, Visual web optimizer, UnBounce, etc. With more than 15 years of experience under our belt, you stand to benefit greatly from our continuous improvement philosophy and recognize your target audience in a better, more efficient way.
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