How To Run A/B Testing: Split Testing Checklist

What is A/B testing?

An A/B test, also known as split testing, is an experiment for determining which of different variations of an online experience performs better by presenting each version to users at random and analyzing the results. It is used on websites, mobile applications, or ads, to test potential improvements in comparison to a controlled version. A/B testing can do a lot more than prove how changes can impact your conversions in the short term. 

Testing takes the guesswork out of website optimization and enables data-informed decisions that shift business conversations from “we think” to “we know.” By measuring the impact that changes have on your metrics, you can ensure that every change produces positive results. 

The best A/B testing tools like VWO, optimized, convert, omniconvert, and AB tasty all help marketers figure out which website design, line of copy, or product feature will produce the best results for your company. There are different types of AB testing, website a b testing, email a b testing, and content a b testing, and there are different methods of it as well like google analytics a b testing and testing using other a b testing software. 

A/B Testing Benefits

Here are some significant benefits of A B split testing:

It helps reduce bounce rates 

If your customers are bouncing off your website, in other words, leaving it without any clicks, website A/B testing can help.  Whether it is changing a headline, rewording a call-to-action, or tweaking the design layout, an A/B test can help identify what’s causing the bounces. After the test has run, you’ll be able to see some a b testing statistics and see which variation got the most interaction from customers and the least amount of bounces. 

It helps to increase conversion rates

An A/B test brings to light what’s converting customers and what’s not. By presenting two versions of your website, an A/B test can help to filter out what doesn’t resonate with your audience and show what does resonate and is bringing about more conversions. 

Results of an A/B test are easy to understand

The results of an A/B test are simple and relatively easy to understand. Examine the results and AB test statistics to see which page, A or B, got more customer clicks and conversions.

It is inexpensive

A/B testing is a fairly cheap and easy way to continue making improvements to your digital marketing. Think of A/B marketing as a way to continue validating decisions on your current website. In the long run, the ROI can be huge because the cost to test is relatively small but can result in significant increases in leads, sales, and revenue.

How to Run an A/B Test?

The idea of A/B testing is to present different content to different variants (user groups), gather their reactions and user behavior, and use the results to build product or marketing strategies in the future. 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:

Pick a Variable

As you optimize your web pages and emails, you might find there are a number of variables you want to test. But to evaluate how effective a change is, you’ll want to isolate one independent variable and measure its performance, otherwise, you can’t be sure which one was responsible for changes in performance.

You can test more than one variable for a single web page or email, just be sure you’re testing them one at a time. Look at the various elements in your marketing resources and their possible alternatives for design, wording, and layout. Other things you might test include email subject lines, sender names, and different ways to personalize your emails.

Set Your Target

Although you’ll measure a number of metrics for everyone’s test, choose a primary metric to focus on before you run the test. In fact, do it before you even set up the second variation. This is your dependent variable. Think about where you want this variable to be at the end of the split test. You might state an official hypothesis and examine your results based on this prediction.

Setup a Control

You now have your independent variable, your dependent variable, and your desired outcome. Use this information to set up the unaltered version of whatever you’re testing as your control. If you’re testing a web page, this is the unaltered web page as it exists already. If you’re testing a landing page, this would be the landing page design and copy you would normally use.

Split Your Test Group Hence A and B

For tests where you have more control over the audience, like with emails, you need to test with two or more audiences that are equal in order to have conclusive results.

Run Test

Kick off your test and wait for visitors to participate! At this point, visitors to your site or application 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.

How to Analyze Results of an A/B Test

Most experimentation platforms have built-in analytics to track all relevant metrics and KPIs. But before analyzing an A/B test report, it is important that you understand the following two important metrics.

• Uplift: The difference between the performance of a variation and the performance of a baseline variation (usually the control group). For example, if one variation has a revenue per user of $5, and the control has a revenue per user of $4, the uplift is 25%.
• Probability to Be Best: The chance of a variation to have the best performance in the long term. This is the most actionable metric in the report, used to define the winner of A/B tests. Whereas uplift may vary based on a chance for small sample sizes, the probability to be best takes sample size into account. The probability to be best does not begin calculating until there have been 30 conversions or 1,000 samples.

Is A/B Testing Dead?

While it is certainly powerful, A/B testing is fundamentally flawed in two specific ways:

1. The process of choosing a winner is manual. That’s both time-intensive and intellectually challenging. 
2. Half the visitors see the worst variation until you pick a winner.

Get Started With Your A/B Test Today

Marketing these days works on insights and A/B testing can help you to gain those insights. Although it is a helpful analytical method it can be slightly tricky to conduct an A/B test. Our expert marketers can help you conduct an A/B test on your website or any other media platform so you can get insights on how you can improve your insights and unlock your full potential.