A/B testing vs multivariate testing

If you work in the eCommerce industry, you have probably heard of the terms A/B testing and multivariate testing.

These testing methods are tools that eCommerce business owners, marketers, and website designers can use to provide consumers with better online shopping experiences through experimentation.

All eCommerce business owners have the same goal: to boost their bottom line. Using these tests, they will be able to pinpoint the specific issues that are getting in the way of this goal so that they can find and implement a solution.

In order to make the most of these A/B testing and multivariate testing and determine which one your business should use regularly, you should know the features and advantages of each of these methods.

What is A/B testing?

A/B testing, or split testing, is a tool that eCommerce business owners can use to optimize their websites and maximize their potential for revenue. With A/B testing, you can compare two different versions of your website, a control version and a variant version, and see which leads to the greatest number of conversions or purchases. This way, you can see if any changes you make to your website will have a positive or negative effect on your bottom line.

How A/B testing works

A/B tests use your live traffic in order to compare one version of your website to a different version. When you run an A/B test, some visitors that visit your website will see Version 1 while other visitors see Version 2. Data collected during this test will show you whetherVersion 1 or Version 2 of your website is the most effective.

This test eliminates all guesswork when it comes to the changes you make for your website, and it can help you pinpoint exactly what you need to adjust on your site to boost your conversion rate and other metrics.

Running A/B tests regularly can work wonders for your eCommerce business. In order to run an effective A/B test, you need to follow a few simple steps:

1. Research

Before you run an A/B test, you need to have an idea of what goals you want to accomplish and the metrics you want to improve. Look at your current metrics and see if there are areas that need work.

For example, if you have several website visitors viewing your email subscription form without completing it, you might need to adjust your form. If the exit rate or bounce rate for your website is high, you may need to change your webpages.

The first step toward successful A/B testing is to find out what you would like to improve on your website.

2. Develop a potential solution

Once you have determined an area that you would like to improve, you need to create a hypothesis to test. This hypothesis will serve as a potential solution to your issue, and you will use A/B testing to determine whether or not this solution is viable.

Your hypothesis should be measurable and specific. For instance, you might form a potential solution like:

• If I decrease the fields in my contact form from three to two, then more visitors will complete the form.
• If I make my “Add to Cart” button larger, then more visitors will click-through
• If I move my navigation bar to the upper right-hand corner, then my bounce rate will decrease

Once you have come up with an idea for a solution, you are ready for the next step.

3. Create versions of your website

In order to test your solution, you need to create a version of your website where you implement your hypothesis.

So, if your potential solution was to decrease the number of fields in your contact form, you need to create a version of your website where your contact form is shorter than it is on your website.

This allows you to have a control page and a variable that you can test with your website traffic.

4. Test your solution

After you have two versions of your website, you can run an A/B test. This will present the different versions of your website to your website visitors so that you can figure out which version will be best for your business.

Use an A/B calculator to determine the appropriate window of time to run your test.

5. Use your testing data

When your A/B test has concluded, you should have data that you can use to see which version of your website was the most effective.

For example, if the conversion rate forVersion 2 is higher than the conversion rate for Version 1, then you should implement the changes in Version 2 to your website.

Using the specific data you receive from A/B tests, you will be able to make the changes that best help you increase your conversion rate and revenue.

Advantages and disadvantages of A/B testing

There are many advantages to A/B testing:

• A/B testing allows you to test niche aspects of your website.
• A/B testing does not require you to have a large number of website visitors, making it a great tool if your business is small.
• A/B testing provides clear data that you can use to implement changes to your website. Rather than speculating about ideas, you can quantify their effectiveness.

While the A/B testing is certainly useful, there are some limitations to this tool:

• A/B testing only allows you to test a limited number of variables. You cannot use A/B testing to test several different features of your website at once.
• A/B testing does not create data to help you determine the relationship between different variables. You will have to analyze this data on your own, which is time-consuming.

If you want to optimize your website and gain the benefits of A/B testing while avoiding these limitations, you should consider multivariate testing.

When to use A/B testing

The short answer? When you have something to learn. 

A/B testing is all about learning. Properly conducted and analyzed, A/B tests will teach you more about your customers than you could learn otherwise — which form they’ll prefer, what they’re willing to pay, when they want certain types of information or when they don’t — You’ll learn all this and more through your A/B testing.

This type of testing is typically used to test minor changes in order to optimize the user experience. This is usually done when a website already has a steady traffic flow and a high number of users have already seen the website in its original form. This ensures that any change made will not drastically affect the user experience, so you won’t lose too much search or referral traffic. 

A/B testing can be a big help in your site’s journey to success. But you should never hit the launch button without some thought. A/B testing requires careful planning, and it’s easy to get tripped up if you don’t know where to start.

At the end of the day, A/B testing is about finding out what works for your business and appealing to a wider audience. Test something new and different from time to time to get a better idea of what works best for your business.

What is multivariate testing?

Like A/B testing, multivariate testing allows you to create multiple versions of your website so that you can optimize your site to provide a great experience to your website visitors.

However, the key difference lies within the specified number of variables you can change. Unlike A/B tests which allow you to test two different versions of your website, multivariate testing allows you to test several different versions or features of your website

How multivariate testing works

Multivariate testing allows you to test the effectiveness of multiple different changes to your website, and it provides data that shows the relationship between these changes and which individual changes will be most beneficial for your site.

Here’s how multivariate testing works:

1. Research

Like A/B testing, multivariate testing requires you to understand the metrics that you would like to change and improve. Study your current metrics and determine your goal for the multivariate test.

2. Develop several hypotheses

Multivariate testing allows you to test more than one hypothesis. Instead of creating two different versions of your website that make one dramatic change, you can make several different versions to test on your live traffic.

For example, you can see which hypothesis will have the best results: changing your contact form fields from four to three, changing your contact form fields from three to two, and changing your contact form fields from two to one. You can also test hypotheses that will require you to change additional features on your website.

Rather than finding one potential solution, you will be able to test multiple potential solutions at once.

3. Create versions of your website

When you run a multivariate test, you will be able to present several different versions of your website to your website visitors. Create different versions that implement the various potential solutions you came up with for the previous step, and allow multivariant testing to work its magic.

4. Test your solutions

Using what is referred to as full factorial testing, run your multivariate test and allow your website traffic to interact with the different versions of your site. These versions will be randomly“assigned,” and will provide invaluable data for you to use.

5. Use your data

When your multivariate testing window is closed, you will have data explaining which specific features of your site performed the best during the test. Your multivariate test will compare each variable on each version of your website to one another and determine not only which version is most effective, but which features of the winning version are most effective.

This provides you with very specific and accurate data that you can use to support changes to your website.

Advantages and disadvantages of multivariate testing

Like any tool, multivariate testing has certain advantages and disadvantages.

Advantages of multivariate testing:

• Multivariate testing allows you to pinpoint specific elements of your page that perform well.
• Multivariate testing provides more detailed data that you can use for your website.
• Multivariate testing allows you to test more than one hypothesis at a time.

Limitations of multivariate testing:

• Multivariate testing works best when you have a lot of traffic visiting your website. In order to test multiple pages, you need a large number of website visitors.
• Multivariate testing is not as fast as A/B testing.

Before you run a multivariate test, you should keep these factors in mind.

When to use multivariate testing

When should you use multivariate testing? It’s simple: when you’re trying to measure interaction effects between independent elements in your optimization goal.

Just like the name suggests, multivariate testing is a way to test with multiple variables. Multivariate tests are about measuring interaction effects between independent elements to see which combination of elements works the best.

Multivariate tests can be used for any purpose where you want to test multiple elements together, such as seeing which colors complement each other best, or how text styles and colors affect readership. The benefit of running a multivariate test is that it can provide more information than an A/B test.

For example, you could run two different A/B tests in parallel, then run a third multivariate test that tests the four variations against each other. This would allow you to figure out whether there was an interaction effect between the two different elements.

Multivariate tests are also very useful in situations where you want to know which features have the biggest impact on your conversion rate. You could use multivariate testing to check which video works best on your website, what format you should use for prices and product descriptions, whether sales will increase if you show extra social media buttons, etc.

In the end, multivariate tests can make your optimization process more efficient by giving you a solid idea of what features you should keep and which ones you should remove from your site.

What are the key differences between the two?

Although A/B testing and multivariate testing often overlap in their fundamentals, there are some key differences between the two.

1. Primary Purpose

With A/B testing, you can compare two different versions of your website, a control version and a variant version, and see which leads to the greatest number of conversions or purchases. On the other hand, multivariate testing allows you to test several different versions or features of your website

2. When to Use

It is best to use A/B testing when choosing between two extremely different types of messages for conversion optimization. On the other hand, multivariate testing is most appropriate when experimenting with multiple versions of page elements on one particular message for conversion optimization

3. Resources Required

While A/B testing is simple, easy to execute, and can work with smaller traffic, multivariate testing is more advanced, needs a larger volume of traffic, and may require a specialized skillset. For that reason, A/B testing is best suited for smaller websites while multivariate testing is what larger websites should opt for.

4. Insights Offered

Since A/B testing only looks into two versions of a webpage, the results it offers are limited and easy to decipher. Whereas, since multivariate testing looks into multiple versions, the results here take longer, are more detailed, and hence often more difficult to decipher.

TLDR; quick summary of the differences between A/B testing & multivariate testing

Which method should I use?

Instead of seeing A/B testing and multivariate testing as absolutes, try using these tests in conjunction with one another to produce results that will help you improve your business.

ConvertCart is a website optimization solution that can help you run A/B and multivariate tests for your eCommerce business. When you use ConvertCart, you will be able to significantly boost your conversion rate and revenue by enhancing the different features of your website.

For more information about how ConvertCart can help your business, please visit our website.