Optimising your Webflow Website with A/B Testing

Introduction

As your business begins to grow, you may want to consider ways to keep customers loyal to your brand or product for longer! A/B testing is a great way to see the progress of your company, and effectively test any changes that could be beneficial to your customers.

Note: this post outlines A/B testing, when you should use it, and when you shouldn't. If you're looking for how to set up A/B testing, you can read that article here.

There are many tools that you can set up to measure and control how your website is performing, but none is more powerful than A/B testing.

Where analytics tools will give you tons of helpful information about how customers navigate your website, how long they stay on for, where they are from, and so on; you still have to take the time to figure out how that information translates into a meaningful change that will improve the conversion rate.

With A/B testing, every change or potential improvement can be put to the test.

In this way, you're not just guessing that a change in copy will convert more customers, you can test it, and prove it.

The leading companies in tech use A/B testing to tweak their websites and apps to slowly make their products stickier so customers will use them for longer. We can use it to see which changes are resulting in more sales or sign-ups, and overtime make our websites more and more effective.

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What is A/B testing

A/B testing is an analytics tool to help you see how two (or more) different designs perform against each other. It enables you to select a page on your website, make changes to that page, and see how the change performs against the original to see if you want to properly implement it.

These design changes can include changing text such as a title, including or hiding sections, swapping out images, or even just changing a button colour.

Both designs are measured against a goal such as signing-up, making a purchase, or reaching out via a form on the contact page. They can also be session based goals, such as how many pages they visit, how often they bounce, or how long they visit the website.

By comparing against a goal, you can see if more or less people are taking action to know whether your original design or new design is the better option going forward.

Why A/B testing is so powerful

Through normal analytics, it can be hard to know exactly what should be implemented off of the data you're collecting. Sure, you know that your sign-up rate is low on your pricing page, but what should you actually do to improve it?

Without A/B testing set up, there is too much guess work. You might update a page based on your analytics data, and then revisit the data a couple of weeks later to see if the page is better, but there are so many other factors that could change the data too.

Data fluctuates often and might not relate to your changes in the way you think it does.

You might find that the sign-up rate is now higher on your page you implemented the change on, but this could be caused by a completely different unrelated factor, such as a spike in a certain kind of traffic.

Drawing incorrect conclusions from your data is dangerous, as you might make changes that make your website less effective.

By using A/B testing, when you want to make a change to you website that you think could improve a page, you're not hoping that it improves the page, you're testing it against the old design.

This means that month by month, you can slowly make each page of your website more effective. You can constantly iron out the kinks of any page as you refine each section to become a conversion machine.

When you should avoid A/B testing

If you’re exploring the idea of A/B testing because you've heard or read about how effective it is, know that it might not be suitable depending on your business’ size.

The biggest problem with this kind of testing is that it thrives on large amounts of data, and struggles when you don't have enough data to test with.

This means that if your website isn't getting enough traffic through, you might not have enough visitors to know which design is performing better.

Data is more accurate when tested over larger sample sizes, so drawing conclusions based on 40 users is not enough to be certain.

Because of this, A/B tests are one of the last analytics tools I would recommend implementing until your business is big enough and you're getting enough website traffic.

As a rule of thumb, I would only suggest looking into using it once you are getting more than 1000 visitors to your website every week.

If you're not at the right scale for A/B testing yet, you still have plenty of ways to optimise your website based on heatmaps, user recordings, user surveys, and user testing.

Summary

A/B testing is one of the most powerful tools that you can use to improve your website overtime. The tech industry leaders use it excessively to refine their websites to be stickier through consistent analysis and optimisation, and you can too.

Remember though, this is one of the more advance techniques that you can use to improve your website, and one that should only be done once you're getting enough traffic.