Are you displaying the most important content of your site as soon as the page loads? Have you ever thought about revamping your website to improve conversation rates and reduce bounce rates? In this article, we will cover ways to improve your site’s conversation rates in just a few steps using A/B testing.
How to conduct an A/B test?
What is A/B testing?
A/B testing, also known as split testing, is a marketing technique that involves comparing two versions of a web page or application to see which performs better in terms of user interactions. These variations, known as A and B, are presented randomly to users.
A portion of them will be directed to the first version, and the rest to the second one. A statistical analysis of the results then determines which version, A or B, performed better, according to certain predefined indicators such as conversion rate. In other words, you can verify which version gets the highest number of clicks, subscriptions, purchases, and so on. These results can then help you to optimise your website for conversions.
When to implement an A/B test?
Before creating your first A/B test, you need to identify any issues with your web pages, then create a hypothesis based on existing data, and think about what changes can be made to improve or eliminate those issues.
Certain things to keep in mind should include:
- What is the problem that you want to solve?
- Have conversions dropped off?
- Have traffic patterns changed?
- Have your demographics shifted?
A close examination of trends in your analytics reports (Google Analytics etc.) is a great place to start gathering those information.
Once you have identified a problem, assemble a team within your organisation and solicit their opinion about the cause of the problem. Use feedback from your team to come up with a hypothesis, which you will validate or invalidate with the A/B test.
Case study
Situation
There is no call to action (CTA) in the hero area of the Aberlour and Malfygin homepages. Bounce rate sits around 50% and from users we have viewed in Hotjar lots scroll up and down the page looking for a range button. Eventually, they see it in the mega menu as “Buy Online” on Aberlour and in the “Menu” on Malfygin. Users then continue the journey from there or drop off from frustration.
Hypothesis
By adding a relevant call to action (CTA) above the fold to drive users into the product range, we should see an improvement of 15% in users viewing product pages and subsequently purchasing.
Result
Version A – Original
Version B (winner) – Addition of “Buy Online” button
Result: 61% more users reaching collection page from homepage
Version A – Original
Version B (winner) – Addition of “View Our Gins” button
Result: 34% Increase In Gin Range Views
How to implement
There are several tools that allow you to conduct an A/B test, such as:
- Optimizely.
- Adobe Target.
- Oracle Maxymiser.
- AB Tasty.
- Google Analytics and Google Optimize.
- Wasabi A/B Testing platform.
- Five Second Test.
In our case, we will use the Google Optimize (formerly, Google Wesbite Optimizer) to implement our A/B testing and measure the conversion rates.
We assume that you already have a container on your Google Optimize account. If this is not the case, you can follow the steps in this article to create your first container on Google Optimize: https://support.google.com/optimize/answer/6211930?hl=en (“Create an A/B test” section)
The next step is to add the Google Optimise script on every page before closing “head” tag, ex.
If your goal is to add a call to action (CTA) button, you can insert the basic HTML element with a custom CSS classname, like:
Sometimes we need to customise the styles of this button. If there are no styles applied by default, we should use the default styles of the website’s primary for the CTA buttons to keep it consistent.
Once you create the button, you can go to your Google Optimise dashboard and follow these steps: https://support.google.com/optimize/answer/6211957 and then read the section “Who to target” here: https://support.google.com/optimize/answer/6211930?hl=en to define the percentage of visitors to target for your tests.
To have clearer explanations on the Google Optimize part, we suggest the video below, but of course there are others that you can find on YouTube or elsewhere. Once you understand the value of A/B testing, there are no limits to what can be done.
