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Shopify A/B Testing: Tools and Techniques for More Conversions

  • Conversion
  • 6 min read

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You’ve got your Shopify store, it’s filled with plenty of brilliant products, and visitors are arriving…but they’re not converting. 

As a Shopify store owner, it’s got you thinking: “What am I doing wrong? Is there a way to test what’s working and what’s not?”

In this article, we’ll cover everything you need to get started with A/B testing on Shopify. We’ll check out the top tools, share some best practices, and help you prepare your store for A/B testing. 

Let’s jump in!

What is A/B testing?

A/B testing, or split testing, is a powerful method for comparing two versions of the same web page to see which one performs better. By showing version A to one group of visitors and version B to another, you can measure the effectiveness of different elements on your site.

It’s like a battle of the web pages, with data determining the winner.

A/B testing is a powerful method.

A/B testing benefits Shopify stores in several ways. It can help you:

  • Increase conversion rates: Fine-tuning specific on-page elements can help boost sales.
  • Enhance user experience: By discovering what your customers prefer, you can give them more of that for a better experience.
  • Reduce bounce rates: Optimizing your pages with A/B testing keeps visitors engaged longer.
  • Make data-driven decisions: You’ll gain a wealth of performance data that can help you make more informed choices.
  • Monitor conversion rate: Assessing which variations result in better performance helps drive sales or other desired actions.

Recommended reading: A/B Testing Terminology: A Glossary for Marketers

How to prepare for A/B testing in your Shopify store?

Don’t just throw yourself (and your Shopify store) into deep water! It’s essential to prepare first—let’s break down exactly how to do that.

Step 1: Set clear goals and hypotheses

Begin with clear objectives. Are you aiming to increase sales, reduce cart abandonment, or enhance the user experience? Once you know what you want to achieve, it’s time to create a hypothesis.

Your hypothesis might look something like this: “Changing the ‘Buy Now’ button color to green will increase click-through rates.”

A good hypothesis will involve tracking key metrics such as conversion rates, revenue generated, and user engagement. This will allow you to measure the performance of different variants.

Step 2: Identify the target audience and segments

Determine who will be part of your test. Segment your audience based on factors like demographics, behavior, and purchase history to ensure that your results are relevant and actionable.

Analyzing customer behavior can provide valuable insights into how different segments interact with your website, helping to identify areas for improvement before conducting tests.

Step 3: Choose the right elements to test

Select which elements in your Shopify store could impact your goals. Common elements to test include headlines, product descriptions, images, call-to-action buttons, and checkout processes.

For example, if your goal is to increase sales, A/B testing your product pages with different product images or tweaking the wording on your CTA buttons could make a big difference.

When selecting elements to test, prioritize those that are most likely to influence your desired outcomes.

Elements to test on product pages

4 AB testing Shopify apps

Now that you’ve prepared your store, it’s time to choose the right A/B testing tool to help you. We’ve compiled the 4 best options, and most of them can be installed easily from the Shopify App Store.

Let’s get started with the first A/B testing tool! 

1. OptiMonk

OptiMonk can help you A/B testing your Shopify store.

OptiMonk is an all-in-one conversion rate optimization toolset that provides popups, website personalization, and A/B testing. 

It’s built for ecommerce marketers and agencies looking for quick and affordable solutions to boost the performance of their campaigns and landing pages.

Let’s take a look at the top features that help with running A/B tests and improving your Shopify store’s performance.

Key feature #1: Visual editor

OptiMonk's visual editor is easy to use and you can test your landing page elements without coding.

OptiMonk’s visual editor is a game-changer for anyone looking to test landing page variations without coding skills.

The visual editor allows you to:

With the visual editor, even users with minimal technical expertise can implement changes and see results quickly.

Key feature #2: Targeting

Target different website visitors based on segments.

Advanced targeting is crucial for meaningful A/B testing, and OptiMonk excels in this area.

The tool enables you to create segments based on a variety of factors, including:

  • Traffic source, device type, and visitor type.
  • Operating system and browser.
  • Behavioral data and custom user events.
  • Data from third-party sources such as Klaviyo lists and other marketing tools.

Advanced targeting allows you to tailor your tests to specific audience segments, ensuring that your results are relevant and actionable.

By understanding and segmenting your audience, you can deliver personalized experiences that resonate with different user groups.

Key feature #3: Analytics

Analyze data in OptiMonks built in analytics.

Understanding the impact of your tests is crucial, and OptiMonk provides robust analytics to help you do just that.

With OptiMonk’s analytics, you can:

  • Track revenue, orders attributed, and custom metrics to gauge the effectiveness of your tests.
  • Drive traffic to the highest-performing variants as soon as a winner is identified.

These insights allow you to make data-driven decisions and continually refine your marketing campaigns for better results.

Pricing:

OptiMonk offers a free plan for smaller businesses just starting out. It’s also great for businesses that want to give A/B testing a try for the first time. Paid plans start at $39 per month.

For more details, visit our A/B Testing page.

2. Optimizely

Optimizely is a widely know and uses A/B testing tool used split testing.

Optimizely is a robust platform that offers advanced testing capabilities, including multivariate testing and personalization options.

Key features:

  • Collaboration: Shared workspaces provide your team with the tools needed to collaboratively craft hypotheses and test variations.
  • User-friendly editor: The editor is user-friendly and powerful, making design adjustments simple. You can target any element on your web page and preview changes with ease.
  • Speedy execution: Achieve the fastest, most statistically sound results by dynamically adjusting traffic to top-performing variations.

Pricing:

For pricing information, you’ll need to request a quote from their sales team.

3. VWO

You can test visual elements and test elements with VWO.

VWO (Visual Website Optimizer) is a powerful, all-in-one web experimentation platform designed to help businesses optimize their entire customer journey.

Key features:

  • Visual and code editor: Make swift edits through VWO’s intuitive visual editor or implement sophisticated changes using the code editor.
  • Fast, secure, and private: VWO is designed to be fast and secure, protecting user data while maintaining high performance standards.
  • Integration with external sources: For added precision, VWO integrates with external data sources like Customer Data Platforms (CDPs).

Pricing:

VWO offers a free plan. Paid plans start at $190 per month.

4. AB Tasty

AB Tasty is a comprehensive platform, you can run A/B tests, split test, or multivariate test within the app.

AB Tasty is a comprehensive Digital Experience Optimization Platform that combines advanced testing capabilities with simple experience-building tools.

Key features:

  • Variety of testing options: You can run A/B tests, split tests, multivariate tests, multi-page tests, and A/A tests.
  • Intuitive interface: The user-friendly interface ensures that you can focus on creating impactful experiences rather than getting bogged down by technical details.
  • Custom widgets: Create dynamic widgets that capture user attention and improve engagement.

Pricing:

To get pricing information, you’ll need to request a quote from AB Tasty’s sales team.

4 best practices for running A/B tests in your Shopify store

As experienced A/B testers, we’ve distilled things down into four essential best practices that will help you get the most out of your website testing efforts.

When you’re first getting started with A/B testing in your online store, consider these foundational steps to ensure your tests are effective and your findings are actionable.

1. Ensure randomization and an appropriate sample size

One of the most critical factors in A/B testing is ensuring that your test groups are randomized. This helps to minimize bias and increase the reliability of your results.

If your groups aren’t random, you could end up attributing differences in outcomes to the wrong factors, leading to misguided decisions.

Equally important is the size of your sample. Your test needs a large enough sample size to provide statistically significant results. Without a sufficient sample size, your findings may not accurately reflect user behavior.

Use online calculators to determine the appropriate sample size for your tests, considering your traffic and expected effect size.

2. Choose the right duration for your tests

Patience is key when it comes to A/B testing. Run your tests long enough to gather a robust set of data, typically at least a few weeks. The exact duration depends on your website traffic and the nature of the test, but a common mistake is ending tests too early.

Ending tests prematurely can lead to inaccurate conclusions. Allow the test to run its full course to capture variations in user behavior over time and ensure the results are not due to random chance.

3. Avoid common pitfalls

You shouldn’t run too many tests simultaneously, as this can complicate data analysis and make it difficult to isolate the impact of each change. 

For example, if you’re testing multiple changes to your product page simultaneously—like tweaking the headline, changing images, and adjusting the CTA—you won’t be able to tell which change is responsible for any shifts in user behavior.

Focus on one test at a time so you can clearly understand its effects. This approach makes it easier to pinpoint exactly which elements are driving changes in user behavior and gives you more precise control over optimizations.

4. Automate with AI

Leveraging AI tools can take your A/B testing to the next level. You can use tools like OptiMonk to automate and optimize your A/B testing process. AI can quickly analyze large datasets, identify patterns, and suggest adjustments to improve test performance.

AI not only saves you time but also enhances the precision of your experiments by rapidly processing data and providing actionable insights. This can significantly speed up your optimization efforts.

Automating with AI ensures that your testing process is efficient and accurate, allowing you to focus on strategic decisions and improvements.

How to analyze your test results?

Running an A/B test is only half the battle. The real value lies in how you analyze the results and use those insights to improve your Shopify store. 

Let’s walk through the key steps to ensure you’re making the most of your A/B testing data.

1. Ensure statistical significance

Before you start drawing any conclusions from your test, it’s crucial to check if your results are statistically significant. This means that the differences observed in your test outcomes are likely due to the changes you made, not just random chance.

Statistical significance helps you confidently decide whether the variation you’re testing (like a new headline or button color) is truly more effective than the original. 

Tools like OptiMonk or Optimizely usually have built-in calculators that show you when your results reach statistical significance. If your test hasn’t reached this point, it might be wise to let it run longer or increase your sample size before making any decisions.

2. Look beyond the winner

While it’s tempting to focus solely on which version won, there’s often more to learn from your A/B test. Dive deeper into other metrics and data points. 

For example, even if one version didn’t outperform the other in terms of conversions, it might still offer valuable insights into user behavior.

Let’s say you tested two different product images, and while Image A led to more sales, Image B significantly increased the time users spent on the product page. This could indicate that Image B engages users better, even if it didn’t directly boost conversions. 

Such insights can inform future tests or tweaks to your store, helping you refine your approach and better understand your customers.

3. Make data-driven decisions

The ultimate goal of A/B testing is to gather actionable insights that help you make better decisions. 

If your test results are statistically significant and one version clearly outperformed the other, it’s time to implement that change across your site. This is where A/B testing shines—it allows you to make informed decisions backed by real data, not just gut feelings.

But what if the results weren’t as conclusive? That’s okay too—testing is about learning. Use what you’ve learned to form new hypotheses and design your next test. 

For example, if changing the CTA button in your Shopify store didn’t boost conversions as expected, you might hypothesize that the button placement or wording could be the issue and test that next.

4. Leverage analytics tools

To get the most out of your split testing results, consider using analytics tools that offer deeper insights.

An analytics tool like Google Analytics can help you visualize user behavior, track performance over time, and understand the context behind the numbers.

Tools like Hotjar and Crazy Egg can show you heatmaps, scroll maps, and session recordings, giving you a clearer picture of how users interact with different elements on the page.

With these insights, you can refine your understanding of what’s working and what’s not, leading to more effective and targeted A/B testing in the future.

FAQ

How long should I run an A/B test?

Typically, you should run your A/B test for at least a few weeks to gather enough data for accurate results. The duration depends on factors like your website traffic and the specific changes you’re testing. Running the test too briefly can lead to inaccurate conclusions due to insufficient data.

Aim for a period that allows for a significant number of user interactions, ensuring that the results reflect genuine user behavior rather than random fluctuations.

Can I perform multivariate testing?

It’s generally best to test one element at a time to isolate its impact and understand which specific change drives the results. However, if you have advanced testing tools and a sufficient amount of traffic, you can conduct multivariate testing.

Multivariate testing allows you to test multiple elements simultaneously by showing different combinations of variants to users. This method can provide insights into how different changes interact with each other, but it requires a larger sample size and more complex analysis.

What if my test results are inconclusive?

If your split testing results are inconclusive, it’s essential to review your hypothesis, sample size, and the duration of your test.

An inconclusive result can occur if the test was not run long enough, if the sample size was too small, or if the changes tested were too subtle to make a significant difference. Here’s what you can do:

  1. Review your hypothesis: Ensure your hypothesis is clear and based on a solid rationale.
  2. Check your sample size: Make sure you have enough participants to achieve statistical significance.
  3. Evaluate test duration: Confirm that the test ran for a sufficient period to capture meaningful data.
  4. Refine and retest: Use the insights gained to adjust your hypothesis and design a new test. Even inconclusive results provide valuable information that can guide your next steps.

By carefully analyzing these factors, you can refine your approach and design more effective tests in the future.

Wrapping up

A/B testing is a powerful tool for improving your Shopify store’s performance.

By setting clear goals, selecting the right tools in the Shopify App Store, and following best practices, you can use A/B testing to make data-driven decisions that boost conversions and enhance the user experience. 

Ready to get started? Dive into A/B testing and watch your Shopify store thrive!

For more tips and insights on A/B testing, check out our video here:

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Written by
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Barbara Bartucz

Barbara is a Content Marketer at OptiMonk. She takes pride in creating different forms of content, whether it’s an article, a video, or an e-book.
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