Do you have an online website designed by professionals using all of the best SEO techniques known to man and it's still not working as intended?

Have you have built a good website, optimized landing pages, added CTAs but are struggling to get conversions?

If so, then you must be wondering what went wrong. Fortunately, you can get to the bottom of it.

The problem, sometimes, is not how well you’ve designed each element of your website, it’s how well they work together. Some combinations of elements make a web page more engaging than others. And, you will never know which combinations work best if you don’t experiment with different elements and create multiple designs.

This is where A/B testing comes into the picture. It can help you optimize your website and take your business to new heights.

What is A/B Testing?

In simple terms, A/B testing or split testing is a process by which you create two variants of your web page and test to see which performs better. This is done by directing half of your traffic to one variant and the other half to the second one. Then you look at metrics like conversion rates, time spent on the page, clicks, etc. to see which performed better.

You can use A/B testing to experiment with different elements of a web page like structure, colors, CTAs, etc. By running multiple A/B tests you can identify what works for your audience and what doesn’t.

This technique can also be used to test ad copy and mobile apps. However, in this post, we will focus only on the use of A/B testing to optimize websites. All the benefits and best practices for conducting these tests can be easily applied to other areas as well.

Why is it Important?

A/B testing is a technique used by most SEO experts to optimize their websites and landing pages and improve conversion rates. It is a proven tactic that helps improve your website’s performance.

Here are some of the benefits of using A/B testing that will convince you of its importance.

  • It can help reduce bounce rates for your web pages by making them more engaging and easier to navigate.
  • A/B tests can help improve conversion rates for your website. You can test different CTAs and their placements to find out which combination gets the highest conversions.
  • It helps improve user experience on your website by optimizing various elements of a web page and using the combination that your users like the best. This often leads to repeat visits by users if their initial experience was good.
  • Using A/B tests you can create better pages in the future, as you already know what works best for your website. This will save you time and effort when creating any new web pages.
  • It can help you optimize the checkout and payment pages and lower cart abandonment rates for your ecommerce website.
  • You can get a higher content engagement and improved dwell time for all pages that are optimized using A/B tests.

How to Conduct A/B Testing Using Google Analytics

Now that you know what A/B tests are and why you should use them, it’s time to shed light on how you can do them. There are several tools available online that you can use for conducting these tests. However, A/B testing using Google Analytics (Google Optimize) is one of the best for a lot of different reasons.

Google Analytics content experiments are a much better alternative than other split tests because they offer a lot more. Most tests change only one element at a time and test the results based on that. However, it is a time-consuming process to test each individual element separately. Moreover, changing just one element does not make much difference in the long run.

Google Analytics provides the option to change multiple variables at a time and analyze results based on that. Please note that this does not make it a multivariate test, but a split test that allows changing multiple variables.

It uses an A/B/n model that allows you to create different variations of the same landing page. The first page will have variant A, the original, and then you can create n variants where one or more elements differ from the original.

Now that we have covered the basics, let’s start with the actual process of how to conduct Google A/B testing.

Formulate a Hypothesis

Before you start experimenting with different variables, you should identify a problem and formulate a hypothesis that you want to test. Your hypothesis should be backed by historical data.

An example of a potential problem could be that you have witnessed a decline in conversions or a high bounce rate. You can identify such problems by analyzing your Google Analytics behavior reports. If you use any other website analytics tool, they can also provide you the necessary insights.

The next step is to discuss the problem with your team and form a hypothesis on how you can solve the problem. Maybe you think changing the color or placement of the CTA button might help or you might want to experiment with different headlines. Form a hypothesis that seems most feasible and then test it using Google A/B testing.

Create an A/B Test

Once you are clear on what variables you want to test, it’s time to create a split test and prove or disprove your hypothesis. Here is the step-by-step process of how to create a test.

1. Open your Google Optimize account. You can find it on the accounts tab in the main menu of your Google account.

2. Select the container for which you want to create an experiment (one account can have multiple containers).

3. Select the “Create Experience” option.

4. Write an experience name in the designated box.

5. Enter the URL of the web page that you want to test.

6. Select the A/B test option from the list of experiences that you can create.

7. Click on “Create.”

Image Source: Google

This will create the A/B test for the web page that you want to analyze. The next step is to customize your test and select the variables that you want to change. You will reach the following page once you create an experience. Here you can create the variants of your web page to test.

Variants
Variants are the changes to different elements of your web page that you want to test. It could be anything from a CTA to a headline to the layout. The different elements that you can test are discussed in more detail in the following section. In this section, we will discuss the process of creating and testing variants.

To start the process, click on the “Add Variant” option from the create variants tab. You will be prompted to add a variant name. Enter the name and click on “done” to add the variant to your variant card.

Repeat this process to add as many variants as you want. Once done, you will see a page with different variants with “0 changes” written next to each, as shown below.

You can start making changes to each variant by clicking on the edit option. This will take you to the visual editor that will have three components—the app bar, editor palette, and the current selection.

The app bar has different components like the experiment name and status, variant picker, change list, etc. The app bar will appear at the top of the page.

The next component is the editor palette that shows up at the bottom-right of the page. This shows all the elements of the current selection that you can edit. This is the panel where the actual editing takes place. You can change the text, typography, color, dimensions, and a lot more from this panel.

The third component is the current selection that basically refers to the part of the web page that you want to change. You can select any element of the page to make edits to it using the editor palette.

Below is a picture of what the visual editor tool looks like, along with the three components mentioned above.

You can repeat this process to create different variants of your page and change different elements in each. Once you are done creating variants, you can choose to assign different weights to each.

By default, Google assigns equal weights to all variants. This means that any website visitor will have equal chances of seeing any of the different variants that you have created. If you want to direct more traffic to a particular variant, then you can do so by assigning more weight to it.

However, it is better to assign equal weights to each variant as that keeps the test fair.

Once you have found a clear winner, you can assign 100% weight to that variant and direct all of your traffic to that.

Objectives

Apart from the variants card, you also have two other cards when you create an A/B test. One is the objectives card and the other is targeting.

On the objectives tab, you can select the goals you want to achieve from a particular test. You can select a maximum of three objectives for each test and see the data for those in your reports. You also need to add a description and hypothesis for each objective that you select.

Targeting

From the targeting tab, you can select who you want to target and when. The who part of it pertains to the percentage of website visitors that you want to include in your A/B test. You can either include all of your website visitors in the experiment or just some of them, it’s your call.

The when part of the process deals with the targeting rules that specify when a user should be made a part of the experiment. This lets you target people after they take certain actions or based on their location or when any other condition is met.

You can read about targeting in more detail here.

Start the Experiment

After you have finished adding variants, selecting objectives, and setting targeting rules, you can start your experiment. This will make the different variants of your web page live and will start directing traffic to each, based on your selected settings.

Ideally, you should run your A/B tests for at least two weeks to get a better picture. The only exception to this is if a variant has more than 95% chances of beating the original variant and achieving the desired objectives.

Measure the Performance

You can check the performance of your A/B test at any time when the experiment is live or after it is completed. You can see the relevant data from the “reports” section.

You can access these reports from the “reporting” tab of Google Analytics, under Behavior > Experiments.

There are a lot of insights that you can gain from these reports. The most important metric to measure is “improvement”. This shows the percentage improvement for each variant, for the set objectives.

For example, if your objective was to reduce the bounce rate, then the report will show how the rate increased or decreased for each variant when compared with the baseline. The baseline refers to the original web page and the percentages show an increase or decrease from the baseline. Here’s an example of one such “improvement overview” report.

Another important part of your test reports is the “objective detail” card. This shows detailed insights on how each variant performed on a particular objective. This helps you choose the best variant based on their respective probabilities to beat the baseline and be the best variants.

Things to Test via Google A/B Testing

Here are some of the most important variables that you should include in your A/B testing experiments.

Headline

Headlines are the first things that a user sees on your page and are crucial in determining whether the person will read further or leave. A good headline can generate curiosity, evoke an emotion, or use other tactics to generate a user’s interest to read further.

Using Google A/B testing you can test different headlines to see which type of headlines engage your audience the most.

CTA Button

There are several reasons why your CTA buttons might not be getting the desired conversions. It could have something to do with the placement of buttons. It could also be because the button color is such that it is not clearly visible and noticeable. The size of the CTA button also matters and could be a reason why people are not clicking on it.

You can use A/B testing to experiment with the size, color, placement, and number of CTA buttons to identify the combination that works best.

CTA Copy

Apart from the physical characteristics of the CTA button, the actual copy also matters. Sometimes the value proposition is just not strong enough to compel a user to take action. There could also be a situation when the text is too long and distracting and that’s why users skip it and don’t click on the CTA button.

You can try changing one aspect of the CTA copy at a time to see the impact on conversions. Google A/B testing will allow you to create multiple variants, each with a different change, and identify the best.

Design and Layout

You should test the way different elements are structured are other important variables that you should test. Design and layout should not be distracting and should be able to direct users to take the desired action. One thing we’ve tested is a static image vs. a video on the homepage. Similarly, you can test layout changes like using icons and bullets at a certain point above or below the fold.

A clean and minimal design is preferred by most experts, as that keeps the focus on important things like CTAs and sales copy. Crowded page design with too many distracting elements could prevent people from taking the desired action.

Sales Copy and Product Descriptions

These are two of the most important elements of any product or service page as they are responsible for closing the deal. Headlines might attract visitors, but sales copy and product descriptions are what helps them make the final decision.

Testing different copy and using the best one can be instrumental in driving conversions for your website.

Images

Images are very important for attracting and engaging your website visitors. But you should ensure that they are not distracting or directing people away from the more important elements of your page.

That is why any page should have a good mix of images and text, laid out in a way that keeps the focus on CTAs and sales copy. Images should aid in the process of directing users down the funnel and not away.

Forms

The sign-up or registration forms on your website also play an important role in driving conversions and generating leads. They should also be tested and optimized to get the best results.

The length, design, and copy of your forms are some variables that you should experiment with during Google A/B testing.

Conclusion

A/B testing is something that every website owner should do on a regular basis to improve their website’s performance. This provides multiple business benefits including an increase in leads and sales conversions.

Use this post as your guide and conduct regular A/B testing experiments on your website using Google Analytics. Write to us if you have any questions about how to use Google A/B testing for your business.