Wes McDowell is the head of content strategy at Deep End Website Consulting in Chicago. In addition, he loves to keep current on all things digital — web design, strategy, and usability — and sharing his newest findings through blogging.
Would you like to know how to A/B test your website? Read this article to learn how to improve your site conversion rate with A/B testing
A website’s long-term value depends on its outstanding performance, so it’s crucial to do everything you can with that in mind. An effective (but sometimes overlooked) way to ensure success is to implement A/B testing (split testing) into site development.
You can improve your marketing tool and your conversion rate by using A/B testing. It will assist you in evaluating your navigation and gaining insight into how users navigate the website. Additionally, you'll be equipped with the knowledge necessary to make smart corrections if there are issues.
What is A/B testing?
A/B testing commonly referred to as split testing, is a marketing experiment in which the performance of two variants of a web page, email, or other marketing asset is compared and measured.
Giving one version to one group and the other to a different group is how you go about doing this. The performance of each variant can then be observed.
Consider it as a contest. You are comparing two variations of your asset to find which one performs better.
Knowing which marketing asset performs best helps guide future choices for web pages, email copy, and other marketing materials.
How does A/B testing work?
A/B testing is a pretty simple concept. You have two versions of something (for instance, where you place the ‘Call to Action’ button on a web page), and you do simultaneous testing to see which version performs best — A or B.
The important thing is to test only one thing at a time and make sure you’re clear about what you want to accomplish (your goal). You form a hypothesis (if I do this, I expect this to happen). And you need to decide how you will assess the results of your testing (metrics).
You allow time for users to experience the two versions of the website, record data and then use it to make decisions for moving forward.
You give consumers enough time to explore the two versions of the website, collect data, and then utilize it to decide how to proceed in the future.
As per research, numerous factors are crucial for A/B testing websites. You must have a control group (think of it as users who will be exposed to the status quo, the web page as it exists) and an experimental group (those users who will see the changed element). This way you can see how the alternative measures up.
Note the above images from glendevonmotors.com. The color of the CTA button is a perfect variation for an A/B test.
You may find out which words, phrases, photos, videos, testimonials, and other aspects perform the best by using A/B testing. Conversion rates can be affected by even small adjustments.
The connection between champions, challengers and variations
The champions, challengers, and variations are where you find the information or data that you need for A/B testing. You can learn more about the people who visit your website by looking at each version of a marketing asset.
Your marketing asset's champion is one that you believe will perform well or has previously performed well, whether it be a blog, email, Instagram advertisement, or something else completely. You put it to the test against a challenger, a champion variant with one element altered.
You either have a new winner after your A/B test, or you find that the initial version outperformed the other two. Then you develop fresh versions to compare with your champion.
If you have an established website with regular visitors, you will want to set your test up to only reach new users. That is, you’ll be testing your existing site with new users and the variation with new users. That way you get data about what you’re testing without disrupting the experience of regular users.
You can employ traffic splitting to get the randomization that is essential for effective A/B testing. Traffic splitting allows the two versions of your site to be served to new visitors randomly, based on an algorithm. It’s important to collect data about your control (status quo) and variant (element you’re checking out) at the same time so that other factors that have nothing to do with the website don't cloud results. For instance, if sales are a metric, the time of the week or month may be a factor that has nothing to do with your website, so you don’t want that to influence your results.
Some valuable website metrics that can be measured include:
- Page views, as in the number of page views of an individual visitor during their session on the site.
- Website visitors, as in the number of unique visitors to the site or even to a particular page on the site.
- User type, as in desktop vs. mobile.
- The geographical location of your visitors.
- The acquisition, as in what channels sent traffic to your site.
You can also look at the number of pages per session visitors view, whether they are new or returning visitors and the average time your web visitors spend engaged with the site.
Learn from experimentation
You can learn a lot about the user experience from A/B testing. Experimentation will allow you to find out what users like, (or don’t like,) about the site. You can test things like the size of buttons, layout of menus and forms and visual elements such as color, logos, and images.
Useful information can come from understanding how visitors move around the website. You can even test headlines and content.
Your ultimate goal is for your visitor to convert. So you will want to look at what it takes for them to navigate through the checkout process. Are distractions interfering with conversions? A/B testing is an excellent way to identify such problems.
Navigation makes a big difference in bounce rate, so use A/B testing to check it out. Are there things you can do to improve the user experience?
What is your conversion goal? It may be acquiring leads or making actual sales.
You can calculate your conversion rate by dividing the number of completed goals by the total sessions.
Why is this important? Learning how long it takes to reach goals can help guide adjustments to your marketing plan. A/B testing can help you do this.
If the website makes direct sales, you will have information about the number of transactions and actual revenue. You can also calculate how long it takes a user to decide to make a purchase.
Strategic A/B testing can help you figure out what about the site assisted in making the conversion.
You may be surprised
It’s most important to split test the pages you rely upon for business-building. Landing pages and other high-traffic pages are likely to be the pages that drive the most conversions, so it makes sense to know how those pages are working and what changes you might make to help reach goals.
Planning your A/B test and letting it run long enough to gain meaningful results is crucial.
You also need to know that not all A/B testing yields helpful information. Your results may be inconclusive. Or they may seem to be inconclusive until you drill down into the data and discover that the change in the element you were testing did make a difference for a particular type of user. Then you will want to look at the value of that user group.
As an example, if you’ve stumbled onto a change that happens to resonate with a valuable demographic, you can do further experimentation to see how this information can be used to grow conversions.
Best 5 free A/B testing tools to choose from
1. Google Analytics and Google Optimize
With Google Optimize, a native Google Optimization Platform, you can run A/B, multivariate, and redirect tests based on previously gathered data. It also includes a direct connection with Google Analytics. From your Google Optimize platform, you can immediately create, modify, and alter landing pages for your Google Ads campaigns.
- Offers a 100% free plan
- Easy implementation
- Planning, scheduling, and administration of experiments
- Google BigQuery, Firebase, Google Ads, Accelerated Mobile Pages (AMP), and Google Analytics direct integrations which enable quick data delivery and exchange
2. Five second test
Five-second tests are a user research technique that allows you to assess the opinion that consumers form of a design within the first five seconds of viewing it. They are frequently used to determine if web pages effectively convey the message they are meant to. Participants are given five seconds to see a design, after which they answer some easy questions. Participants are given an overview of the format before the test begins and are urged to pay close attention. They may also be provided some context on what to watch out for, depending on the test's objectives.
3. Wasabi A/B testing platform
Wasabi A/B Testing Service is an enterprise-grade, real-time project that is entirely API driven. Users have the ability to experiment on the web, on mobile devices, and on desktop computers. It is quick, simple to use, packed with features, and requires little instrumentation.
- Wasabi operates on your servers, whether they are on-site, in the cloud, or both, giving you total control over your data.
- Uniform and consistent testing across mobile, desktop and web. The back-end and front-end integrations are also supported.
- Real-time user distribution will preserve traffic for parallel A/B tests. Any language and set are compatible with the Wasabi REST API.
Statsig offers a unified platform that integrates what you create with the effect you make in order to meet all of your experimental demands. On any device, in any layer of the application stack, at any size, we power A/B tests and trials. Statsig provides you with a thorough 360-degree assessment of your product's performance.
5. AB Tasty
AB Tasty offers a collection of products to optimize your conversions and provides a complete A/B testing solution. Heatmaps and session recording let you examine how your users behave (also known as user session replay). Additionally, you can customize your website by segmenting your audience and using a variety of targeting parameters.
Final thoughts :
A/B testing ultimately aims to get rid of subjectivity and speculation. Let the data show how users interact with the website and make modifications after determining their value. When you let your data tell you the real story about what’s happening on your website, you can start making the right changes to increase conversions, sales and ultimately revenue for your business.
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