What is A/B Split Testing?
A/B split testing is the process of creating one (or more) variants of a webpage with one element tweaked to identify which works better at driving sales or engagement. A/B tests are completed in a controlled manner, with the aim being to display each of the variants to an equal number of viewers. This allows for easy analysis of the results of the test afterwards, which empowers you to confidently decide which of the variants of the page performs better.
A/B split tests are similar to scientific experiments in the sense that they require a detailed hypothesis to be successful. A/B tests require a set goal, such as encouraging more conversions or achieving more newsletter sign ups. Once you have determined what you want your goal to be, you will need to identify which element of your website you want to alter to gain your goal, this could be anything.
What is a Good Method to Follow For Split Testing?
The method you use for any A/B test follows the same rough outline. It is important that you follow this plan for A/B split testing, as you will have every piece of information you need to identify whether or not your test was a success.
- Hypothesis – Every split test requires a hypothesis before you start the test. This is the backbone of your entire campaign, and the rest of your campaign should be set up revolving around your hypothesis. Your hypothesis is a prediction towards what you think your changes to the page will transfer over to in terms of your goal, an example of a hypothesis is “if I change the color of the background on my homepage then my bounce rate will decrease”.
- Variable – The variable is the element you change for each version of your page. This should always be one single element of the web page, as this allows for you to drill down on the exact factor that may or may not affect your hypothesis.
- Running Your Test – Here is where you take the different versions of your page or content and roll it out to your test groups. The test should be rolled out to an equal number of recipients, and then run for as long as it takes for you to get an appropriate amount of data on user action to come to a solid conclusion.
- Analysis – Here is where all that testing boils down to, the results. If your results show low conversions on both conversions then you should be looking towards identifying which element on your page is holding your users back from converting. There could be any element causing friction here, and this element will need updating when you run another campaign. Look at your results from the bigger picture, analyzing your campaign as a whole will allow you to identify any potential issues. If your results are sound, then you can get looking into the differences your different versions had on your hypothesis. If you have noticed that your updated element has created a positive effect on your hypothesis then implement the change, and if it hasn’t then re-run the test with a different variable.
- Re-Running The Test – If your split test was successful then you should always re-run the test again. This is to ensure that it was the element you changed that affected the hypothesis. If this test shows with the same results then you have been successful! Rinse and repeat this method regularly.
So How Can A/B Testing Perfect My Website?
A/B split testing allows you to identify which elements of your site are causing people to leave early, causing people to engage and helps you to identify what parts of your website make users convert the most effectively. With A/B testing you can radically, and cheaply improve your bottom line by a drastic amount. A/B testing leads to better content as to complete A/B testing you have to understand which of your content is more valuable, and why that content is more valuable.
You will be able to lower any risks in changing your pricing or strategy by testing consumer behavior before-hand to predict whether the change will be a success or not. You will be able to target your resources to their most effective locations, which will drive up your return on investment and success rates. The potential improvements you can get out of A/B testing go beyond monetary benefits, and the knowledge you will learn about your consumers and their behavior will be invaluable in years to come.
Finally, with a few years of A/B testing done on your website it will be an optimized goldmine of profit. Profits will be through the roof, and you will have to spend less to get more. When your site is at its most effective point any pay-per-click and display advertisements will be much more successful, and your cost per acquisition will be much lower than before. Your site will be much more customer centric, offering a superior user experience to your competitors. A/B testing opens up doors of opportunity to your marketing team, and any avenue of marketing they go down will have less risk and more success attached to it. You will get the most out of your web traffic and you will make better informed decisions on your marketing strategy, which is why A/B testing simply cannot be missed.
How Do I Go About Creating An A/B Test?
Google Analytic’s is one of the tools you can use to create an A/B test, and it is also extremely simple. Before you think about creating an A/B test within Google Analytic’s you will need to decide what you want to test. If you decide to test the effect of the background color on the bounce rate for example then going about creating this is simple. You will need to take a page (i.e homepage) and create a carbon copy of this, and change the background color to something other than the original.
From here you would set the variation page’s URL to something very similar to the control (/home1 instead of /home for example). When you have created this variant, you need to have Google Analytic’s tracking set up on your site and you will need to log into your Google Analytic’s account, and in the reporting area go to experiments within the behavior tab. From here you can create an experiment and name it what you like, and set an objective up for the experiment (bounce rate in this example). The next step will require both of the URL’s of the pages you want to test. From here the only other change you will need to make to your website is an experiment code that you will need to add to the header of the original control page.
After you have added this code then you can start the ball rolling! Google Analytic’s is simple to use and set up, plus it’s also free. If you have a website and want to increase your bottom line then you have all of the tools at your disposal, completely free of charge. You will be able to make your website better at achieving your goals with almost no technical know-how required.