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A/B testing: How to set it up on Shopify?

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A/B testing: How to set it up on Shopify?

As an e-merchant, you make sales, but can’t you yet determine which products work specifically on your site? With rising advertising costs, this is not always easy. This makes it increasingly difficult to spend more money and acquire a profitable customer. This is where A/B testing comes in to help you. A/B testing is a primary way or method that allows you to increase your store’s revenue without spending more money. What is a/b testing? How to do it on your Shopify store? What are the most important things to test? What A/B testing tools can help you increase your sales? Here is a guide that will address all of these concerns.

A/B testing – An effective test to improve performance

A/B testing is a method that allows visitors to present a website with two different versions of the same page. During the test, different elements can be analyzed to determine the best performing version that offers the highest number of conversions. So, by doing A/B testing on your Shopify store, you present version A of a certain page to half of the visitors and version B to the other half.

So this procedure allows you to make decisions based on the data you get in order to continuously improve the performance and growth of your Shopify store. In reality, without the data you get through A/B testing, you’ll just guess what’s really working for you. The objective of your test will therefore be to allow you to determine the version that allows you to make the most sales. So, based on this data, you’ll be better able to make smarter business decisions and generate more revenue from the traffic you already have.

What are the different types of A/B testing?

Now that we’ve seen the definition of a/b testing, let’s look at the different types of testing that exist.

Split testing

Here, it will be a matter of comparing two different versions of a page using different URLs. So, with this type of test, the visitor will be redirected to another page instead of staying on the same.

A/B/n testing

A/B/n testing is for the larger version of A/B testing. It allows you to test more than two versions of the same page from a single variant. As an example, you can choose to introduce three or four different variants during the test. Thus, it will affect how you divide your sample. Anyway, there is only one variant that will change from one version to another with respect to version A.

The multi-variable test

Multivariate testing differs slightly from A/B/n testing. It allows you to jointly compare multiple versions of a page by collectively testing all possible variant combinations. The multi-variable test is therefore more complete than the A/B/n test. You can use it to test changes to specific elements of a page, while A/B/n testing allows you to test completely different versions of a page against each other. This type of test allows you to determine the best performance of your different variant combinations. Note that this type of test is more suitable for shops that generate significant traffic.

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Why do A/B testing on Shopify?

A/B testing has many advantages. Using it allows you to test several variants to optimize your performance in general and your conversion rate in particular. Through comparative tests, you will be able to determine the combination that can effectively boost your business among those you have developed on your store.

On the other hand, it may happen that your test is not a success. Even if it is, it is still useful. This allows you to improve your progress because you discover new and essential information. You discover elements that escaped you in the inner workings of your shop. Thus, exploiting the information obtained from your results, you can do better, and obtain appreciable results in the future.

Example of A/B testing

A/B testing – Define a clear and precise basic objective

Let’s say you want to increase the number of signups on your Shopify store by testing click-action words. There will therefore be A and B, the two versions to be tested. You are therefore going to test the effectiveness of version A on a sample representing half of the visitors. Version B will also be tested on the rest of the store visitors.

For version A, you can therefore use an action word like ” free trial “. For version B, you can put an action verb such as ” Try it free “. The version of the page that will generate the most registrations is the one you will consider to be the best performer. It therefore wins the A/B testing, and it is it that you will install as a permanent version of the page in question.

In addition, to ensure the effectiveness of your test, it will be necessary to integrate a certain number of key indicators tags. For example, to analyze the version of the page generating the highest conversion rate, it will be necessary to include other factors. Among others, elements such as: the number of visits, the amount of purchases made, the average time spent on the page, etc. Likewise, you need to make sure to conduct the test for the long term.

What elements to test on your Shopify store?

There are no absolute items to test on a store. As an e-merchant, you do not necessarily face the same problems. Each case differs from another. The elements to be tested depend among other things on your customers, your data, and other elements on your store. Determining what goals you want to achieve and what metrics to analyze will also help you decide what to test. However, here are some suggestions.

  • User experience;
  • Headings and titles;
  • Call-to-Action;
  • Images ;
  • The homepage  ;
  • The Design or a particular feature;
  • contact forms;
  • Satisfaction questionnaires;
  • The page structure;
  • Photos or videos on a product sheet;
  • Etc.

A/B testing: How to set it up on Shopify?

A/B testing – Set up on Shopify

Here’s how to set up A/B testing on your store.

Choose the item to test

Which variants do you want to test? To check the effectiveness of an item you changed, perhaps you should choose a single variation to measure its performance. Otherwise, you will not know exactly the element which is at the base of the observed changes. It is true that you have the possibility to test more than one variation for a single page. However, you should make sure to test them simultaneously.

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Here are some variations you can include in your A/B testing:

  • The titles of your pages;
  • The images present on your Landing page or in your content;
  • The color of a call-to-action button;
  • Emails;
  • The position of the call-to-action buttons;
  • The prices;
  • The number of fields in your forms;
  • Etc.

Define your goal

What goal would you like to achieve by taking your test? It is true that with an A/B test, you can obtain several pieces of information. However, in order not to spread yourself too thin, choose a variation on which you concentrate. What element would you want to analyze for example if your objective is to modify the title of your page? Is it the number of visits or the conversion rate on this page? Hence the importance of precisely determining the objective you wish to achieve. Following this, you could set up a hypothesis or a scenario allowing you to analyze your results based on this approximation.

Do one test at a time

Testing multiple things for a single campaign can confuse your results. Suppose that for a campaign, you want to test a variation on a landing page. However, at the same time, you are running a test of an email campaign directing to said page. So how will you know exactly which parameter increases leads? It will be difficult for you to determine it.

Create version A and B of the test

With the previous steps, you can use the information at your disposal to configure the different versions you want to test. Version A represents the web page you are using right now. Starting from this version, you will create version B which is the one you want to test.

For example, if you want to know if a page’s design has an impact on user engagement, configure version A with a central call to action on the page, but with a not very attractive design. Next, create the variation that doesn’t aim for the call-to-action, but whose design captures the appeal of the product.

Determine sample volume

In order to determine your sample size, you will consider the tool you will be using as well as the type of A/B testing you have chosen. The division may vary depending on the tool you are using. However, some tools allow you to instantly split traffic between the different versions you have. Thus, each version receives a random sample of visitors. For example, if you want to create email campaigns, the A/B testing tool Sendinblue takes care of sending each version to exactly half of the sample.

Similarly, if you want to A/B test YouTube Thumbnails (YouTube video thumbnails), you can use the TubeBubby tool. This will let you know which version to use for best results to improve the click-through rate on your videos.

Specify test duration

Why is timing important with A/B testing on Shopify? The duration of the test can vary, but it is still important to specify it. Choosing too short a period could lead to obtaining limited and erroneous results for relevant analyses. Similarly, too long a cycle would have the disadvantage of being distorted. Ideally, it might be done for at least two full business cycles.

You also need to take into account that customers’ buying habits can change depending on the day of the week. Likewise, there are some customers who will only be able to make their purchases on specific days. Remember that some external factors like weather, seasons, events and others can have a significant impact on sales.

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Choose the method to define the winning version

On what basis will you choose the winning version? Is it by the best open rate? The best click-through rate? The number of pages viewed by visitors? Define that!

Statistical significance: Analyzing your test results

Checking the reliability of your tests using the a/b testing significance formula is important. Statistical significance is the probability that one variant will perform better than the other over the long term. The higher the percentage of statistical significance in a test, the less likely your results are to be random. You can use a tool to measure statistical significance. Achieving at least 95% statistical significance proves the relevance of your results.

Choose an A/B testing tool

As mentioned in the article, there are several tools that can help you conduct your test properly. Here are a few.

  • Google Analytics ;
  • Google Optimize ;
  • Optimizely ;
  • pre-university education;
  • AB Tasty ;
  • Nelio for A/B Testing WordPress;
  • Etc.

In addition, know that you can also do Facebook A/B Testing. There are several ways to create A/B tests on Facebook depending on the variable you are looking to test.

Implement winning versions

Once you have your tests in place, analyze your results, and if one of the variants definitely outperforms the original version, run it. Then, it will be necessary to ensure that the results obtained during the test are confirmed in the long term.

Why take A/B testing training?

A/b testing training offers several advantages. With training, you will discover the strategies and approaches that work. In addition, you will know the pitfalls and the procedures to avoid them. By following a training, you will know how to use A/B testing in order to decide which changes are worth implementing on your store. So you’ll base your decisions on real data rather than relying on intuition. It can be difficult to design good A/B tests and draw valid conclusions. You can almost never measure exactly what you want to know. It is therefore necessary to find good indicators, which you will learn in a training course.

Likewise, you should also use various statistical techniques to ensure that the results you get are not due to chance. Training will guide you through this process. Thus, you will be ready to make crucial decisions that could significantly affect your store in the future.

In summary

You should not take A/B testing as the absolute of any conversion strategy. For example, if you have a new store or the number of your visits is low, you do not have to perform A/B testing. That doesn’t mean A/B testing isn’t useful for a new business. You just risk getting less accurate and less relevant results. Either way, keep in mind that doing A/B testing will depend on the size and resources of your business. Each scenario is different and the objectives are not the same. It is therefore necessary to choose a solution adapted to your needs.

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