What is A/B Testing?

A/B testing (also known as split testing or bucket testing) is a method of comparing two versions of a webpage or app against each other to determine which one performs better.

A/B testing is the practice of showing 2 variants of the same web page to different segments of visitors at the same time and comparing which variant drives more conversions. Typically, the one that gives higher conversions is the winning variant, applying which can help you optimize your site for better results.

A/B testing is a way to compare two versions of a single variable, typically by testing a subject’s response to variant A against variant B, and determining which of the two variants is more effective.As the name implies, two versions (A and B) are compared, which are identical except for one variation that might affect a user’s behavior. Version A might be the currently used version (control), while version B is modified in some respect (treatment).

How does A/B testing works?

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 which 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:

Collect Data:

Your analytics will often provide insight into where you can begin optimizing. It helps to begin with high traffic areas of your site or app, as that will allow you to gather data faster. Look for pages with low conversion rates or high drop-off rates that can be improved.

Identify Goals:

Your conversion goals are the metrics that you are using to determine whether or not the variation is more successful than the original version. Goals can be anything from clicking a button or link to product purchases and e-mail signups.

Generate Hypothesis:

Once you’ve identified a goal you can begin generating A/B testing ideas and hypotheses for why you think they will be better than the current version. Once you have a list of ideas, prioritize them in terms of expected impact and difficulty of implementation.

Create Variations:

Using your A/B testing software (like Optimizely), make the desired changes to an element of your website or mobile app experience. This might be changing the color of a button, swapping the order of elements on the page, hiding navigation elements, or something entirely custom. Many leading A/B testing tools have a visual editor that will make these changes easy. Make sure to QA your experiment to make sure it works as expected.

Run Experiment:

Kick off your experiment and wait for visitors to participate! At this point, visitors to your site or app will be randomly assigned to either the control or variation of your experience. Their interaction with each experience is measured, counted, and compared to determine how each performs.

Analyze Results:

Once your experiment is complete, it’s time to analyze the results. Your A/B testing software will present the data from the experiment and show you the difference between how the two versions of your page performed, and whether there is a statistically significant difference.

Why Do You Really Need To Do A/B Testing?

A/B testing has a multitude of benefits to a marketing team, depending on what it is you decide to test. Above all, though, these tests are valuable to a business because they’re low in cost but high in reward.

Increased Website Traffic:

Testing different blog post or web page titles can change the number of people who click on that hyperlinked title to get to your website. This can increase website traffic as a result.

Higher Conversion Rate:

Testing different locations, colors, or even anchor text on your CTAs can change the number of people who click these CTAs to get to a landing page. This can increase the number of people who fill out forms on your website, submit their contact info to you, and “convert” into a lead.

Lower Bounce Rate:

If your website visitors leave (or “bounce”) quickly after visiting your website, testing different blog post introductions, fonts, or feature images can reduce this bounce rate and retain more visitors.

Lower Cart Abandonment:

Ecommerce businesses see 40% – 75% of customers leave their website with items in their shopping cart, according to MightyCall. This is known as “shopping cart abandonment.” Testing different product photos, check-out page designs, and even where shipping costs are displayed can lower this abandonment rate.

Common Mistakes While A/B Testing:

  1. Invalid hypothesis
  2. Taking others’ word for it
  3. Testing too many elements together
  4. Ignoring statistical significance
  5. Using unbalanced traffic
  6. Testing for incorrect duration
  7. Failing to follow an iterative process
  8. Failing to consider external factors:
  9. Using the wrong tool

A/B testing tools to help improve conversion

Unbounce:

Unbounce lets you build, publish and test responsive landing pages, without any knowledge of HTML. With its friendly, easy to use interface, working with elements is simple, with the ability to tweak any aspect of your page. Using the drag-and-drop tool you can drag in images, text, video and even maps into your pages and organize them.Collaboration is easy, with the ability to assign roles for team members, enable project feedback, and start capturing leads, embed video, maps, social feeds and widgets, to optimize conversions.

VWO:

VWO is one of the easiest A/B Testing tools, with the ability to easily change headlines, buttons, images or any other elements to create multiple variations of your website to test. You can track revenue, signups, clicks and other conversion goals and get real statistical data and results.. VWO works across mobile, tablet and desktop websites, and is a simple one-time installation, simply insert a small JavaScript code snippet on your website.

Five Second Test:

Five Second Test lets you fine tune landing pages and calls to action by analyzing prominent elements of your design, by finding out what a person recalls about your design in just 5 seconds. Using this method you can ensure your message is being effectively communicated, to test your brand message, and quickly find out what users like most and least about your website. It’s simple to use, just upload an image, setup your test and a URL is then generated, which you can share, with instructions on the test.

Google Analytics Experiments:

Google Analytics ‘Experiments’ makes it a complete A/B testing platform which utilizes Googles multi-armed bandit approach. The tool allows you to split-test up to 10 full versions of a single page, each delivered to users from a separate URL. You can compare different web pages’ performance using a random sample of users, with the ability to define what percentage of your users are included in the experiment. Using the Content Experiments API you can run tests sever side and implement different recommendations or search algorithms. There’s also no redirects, as the API allows testing changes to content without redirects, and is simple to implement.

Convert Experiment:

Convert Experiment offers multi-domain A/B and multivariate testing and tracking, development tools for jQuery, JavaScript and CSS, with comprehensive reports. Edit your content without your need for infrastructure, with a visual WYSIWYG(What You See Is What You Get) editor and easy style sheet editing for dynamic content experiments.Convert Experiment seamlessly integrates with Google Analytics for real-time data and extended segmentation. You have full test control with minimum and maximum test duration, traffic allocation, conversion tracking, automatic bounce and engagement measuring and behavioral and segmented tracking.

Maxymiser:

Maxymiser is a powerful solution to optimize customer experience and create sophisticated campaigns. Providing simple A/B tests right through to sophisticated multivariate tests, with the ability to quickly and easily create and launch tests on any public or secure page with just one line of code, using the easy to use visual editor.Maxymiser automatically builds a unique customer profile for every online visitor based on CRM data, historic and in-session behaviors and industry specific and customizable visitor attributes.

A/Bingo:

A/Bingo is a Ruby on Rails’ A/B testing framework deployed as a plugin, which can test display or behavioral differences using just one line of code. It can measure any event, test for statistical significance and is extremely fast, meaning it has minimal impact on page load times or server load. As the A/B tests are defined in code, there is no setup or configuration required, the first time code for a particular test executes, it does all the setup work for the test and logs the first participant.

KISSmetrics:

KISSmetrics is a powerful analytics platform to help increase customer acquisition and retention rates. The KISSmetrics JavaScript library provides a function to help you set up your A/B test, which has three major features; it randomly assigns the current visitor to one of the variations, ensures the subsequent calls return the same variation to the visitor and sets a property with the name of the your experiment.You also have the ability to track two completely different page designs, not just changes in individual elements, using a single URL for all of your landing page variants.

AB Tasty:

AB Tasty is an A/B testing tool to optimize your conversion rate, allowing you to modify pages using a visual editor, without writing any code and without any technical knowledge. You can measure which versions of your pages produce the best results for your objectives, such as page-views, registrations, purchases, and more. Create a any testing scenario you like, from simple to the most complex multivariate tests, and precisely define the pages and visitors to include. You can then take what you’ve learned to personalize customer experience and create segmented marketing campaigns.

Adobe Target:

Adobe Target provides an intuitive user interface to create personalized web experiences, quickly create A/B tests and confidently target content. Target provides a guided testing and targeting workflow and framework, with no coding or setup hassles, so it’s easy to see your visitor’s responses to content variations in real time and instantly adapt your site to meet their needs.Adobe Target features one-click optimized content delivery, multipage and cross-channel testing and interface customization, with a variety of filtering option, customizable graphs and reporting options.