- 1 What is A/B testing?
- 2 Why should you do A/B testing?
- 3 How to perform an A/B test?
- 4 Conclusion
What is A/B testing?
A/B testing (aka split testing) is an experimentation process – in which 2 or more versions of a web/app element (e.g: web page, button, color, etc.) are displayed to different segments of visitors at the same time. The purpose is to figure out which version creates the greatest impact and drives the most business metrics.
Basically, A/B testing is carried out to provide a solid, data-centric foundation for website/app optimization – and allows business owners to make data-driven judgments. The ‘control’ or original testing variable is referred to as A; whereas the ‘variation’ – the new version of the original variable, is B. The one with better business metric(s) is then chosen.
Implementing the proper variation adjustments is crucial to optimizing your website and increasing your business’s ROI. Each website’s conversion stats are not the same. Let’s say, for eCommerce, product sales may be important; while for B2B business, people may care more about qualified leads.
Why should you do A/B testing?
A/B testing is one of the components of the overarching process of Conversion Rate Optimization (CRO), using which you can gather both qualitative and quantitative user insights. You can further use this collected data to understand user behavior, engagement rate, pain points, and even satisfaction with website features, including new features, revamped page sections, etc. If you’re not A/B testing your website, you’re surely losing out on a lot of potential business revenue.
1. Determine users’ pain points
Users come to your website to achieve a specific goal that they have in mind. It may be to understand more about your product or service, buy a particular product, read/learn more about a specific topic, or simply browse. Whatever the visitor’s goal may be, they may face some common pain points while achieving their goal. It can be a confusing copy or hard to find the CTA button like buy now, request a demo, etc.
Not being able to achieve their goals leads to a bad user experience. This increases friction and eventually impacts your conversion rates. Use data gathered through visitor behavior analysis tools such as heatmaps, Google Analytics, and website surveys to solve your visitors’ pain points. This stands true for all businesses: eCommerce, travel, SaaS, education, media, and publishing.
2. Improve ROI
As most experienced optimizers have come to realize, the cost of acquiring quality traffic on your website is huge. A/B testing lets you make the most out of your existing traffic and helps you increase conversions without having to spend additional dollars on acquiring new traffic. A/B testing can give you high ROI as sometimes, even the minutest of changes on your website can result in a significant increase in overall business conversions.
3. Reduce bounce rate
One of the most important metrics to track to judge your website’s performance is its bounce rate. There may be many reasons behind your website’s high bounce rate, such as too many options to choose from, expectations mismatch, confusing navigation, use of too much technical jargon, and so on.
Since different websites serve different goals and cater to different segments of audiences, there is no one-size-fits-all solution to reducing bounce rate. However, running an A/B test can prove beneficial. With A/B testing, you can test multiple variations of an element of your website till you find the best possible version. This not only helps you find friction and visitor pain points but helps improve your website visitors’ overall experience, making them spend more time on your site and even converting into a paying customer.
4. Make low-risk modifications
Make minor, incremental changes to your web page with A/B testing instead of getting the entire page redesigned. This can reduce the risk of jeopardizing your current conversion rate.
A/B testing lets you target your resources for maximum output with minimal modifications, resulting in an increased ROI. An example of that could be product description changes. You can perform an A/B test when you plan to remove or update your product descriptions. You do not know how your visitors are going to react to the change. By running an A/B test, you can analyze their reaction and ascertain which side the weighing scale may tilt.
Another example of low-risk modification can be the introduction of a new feature change. Before introducing a new feature, launching it as an A/B test can help you understand whether or not the new change that you’re suggesting will please your website audience.
Implementing a change on your website without testing it may or may not pay off in both the short and long run. Testing and then making changes can make the outcome more certain.
5. Achieve statistically significant improvements
Since A/B testing is entirely data-driven with no room for guesswork, gut feelings, or instincts, you can quickly determine a “winner” and a “loser” based on statistically significant improvements on metrics like time spent on the page, number of demo requests, cart abandonment rate, click-through rate, and so on.
6. Redesign website to increase future business gains
Redesigning can range from a minor CTA text or color tweak to particular web pages to completely revamping the website. The decision to implement one version or the other should always be data-driven when A/B testing. Do not quit testing with the design being finalized. As the new version goes live, test other web page elements to ensure that the most engaging version is served to the visitors.
How to perform an A/B test?
A/B testing offers a very systematic way of finding out what works and what doesn’t work in any given marketing campaign. Most marketing efforts are geared toward driving more traffic. As traffic acquisition becomes more difficult and expensive, it becomes paramount to offer your users the best experience who comes to your website. This will help them achieve their goals and allow them to convert in the fastest and most efficient manner possible. A/B testing in marketing allows you to make the most out of your existing traffic and increase revenue inflow.
A structured A/B testing program can make marketing efforts more profitable by pinpointing the most crucial problem areas that need optimization. A/B testing is now moving away from being a standalone activity that is conducted once in a blue moon to a more structured and continuous activity, which should always be done through a well-defined CRO process. Broadly, it includes the following steps:
Step 1: Research
Before building an A/B testing plan, one needs to conduct thorough research on how the website is currently performing. You will have to collect data on everything related to how many users are coming onto the site, which pages drive the most traffic, the various conversion goals of different pages, etc. The A/B testing tools used here can include quantitative website analytics tools such as Google Analytics, Omniture, Mixpanel, etc., which can help you figure out your most visited pages, pages with most time spent, or pages with the highest bounce rate. For example, you may want to start by shortlisting pages that have the highest revenue potential or the highest daily traffic. Following this, you may want to dive deeper into the qualitative aspects of this traffic.
Heatmap tools are the leading technology used to determine where users are spending the most time on, their scrolling behavior, etc. This can help you identify problem areas on your website. Another popular tool used to do more insightful research is website user surveys. Surveys can act as a direct conduit between your website team and the end-user and often highlight issues that may be missed in aggregate data.
Further, qualitative insights can be derived from session recording tools that collect data on visitor behavior, which helps in identifying gaps in the user journey. In fact, session recording tools combined with form analysis surveys can uncover insights on why users may not be filling your form. It may be due to some fields that ask for personal information or users, maybe abandoning your forms for too long.
As we can see, both quantitative and qualitative research can help us prepare for the next step in the process, making actionable observations for the next steps.
Step 2: Observe and formulate hypothesis
Get closer to your business goals by logging research observations and creating data-backed hypotheses aimed at increasing conversions. Without these, your test campaign is like a directionless compass. The qualitative and quantitative research tools can only help you with gathering visitor behavior data. It is now your responsibility to analyze and make sense of that data. The best way to utilize every bit of data collated is to analyze it, make keen observations on them, and then draw websites and user insights to formulate data-backed hypotheses. Once you have a hypothesis ready, test it against various parameters such as how much confidence you have of it winning, its impact on macro goals, and how easy it is to set up, and so on.
Step 3: Create variations
The next step in your testing program should be to create a variation based on your hypothesis, and A/B test it against the existing version (control). A variation is another version of your current version with changes that you want to test. You can test multiple variations against the control to see which one works best. Create a variation based on your hypothesis of what might work from a UX perspective. For example, enough people not filling forms? Does your form have too many fields? Does it ask for personal information? Maybe you can try a variation with a shorter form or another variation by omitting fields that ask for personal information.
Step 4: Run test
Before we get to this step, it’s important to zero upon the type of testing method and approach you want to use. Once you’ve locked down on either one of these types and approaches based (refer to the above-written chapters) on your website’s needs and business goals, kick off the test and wait for the stipulated time for achieving statistically significant results. Keep one thing in mind – no matter which method you choose, your testing method and statistical accuracy will determine the end results.
For example, one such condition is the timing of the test campaign. The timing and duration of the test have to be on point. Calculate the test duration keeping in mind your average daily and monthly visitors, estimated existing conversion rate, minimum improvement in conversion rate you expect, number of variations (including control), percentage of visitors included in the test, and so on.
Use our Bayesian Calculator to calculate the duration for which you should run your A/B tests for achieving statistically significant results.
Step 5: Analyse results and deploy changes
Even though this is the last step in finding your campaign winner, analysis of the results is extremely important. Because A/B testing calls for continuous data gathering and analysis, it is in this step that your entire journey unravels. Once your test concludes, analyze the test results by considering metrics like percentage increase, confidence level, direct and indirect impact on other metrics, etc. After you have considered these numbers, if the test succeeds, deploy the winning variation. If the test remains inconclusive, draw insights from it, and implement these in your subsequent tests.
You may be interested in: A/B Testing With Google Optimize & ReactJS
We hope that the above analysis should give you a detailed overview of the importance of A/B testing in business and marketing – as well as how to do it correctly. If you are looking for a software development agency to help with your website/app development project, don’t hesitate to reach out to JSLancer – our team will be more than happy to provide a FREE consultation on how we can help you visualize your goals.