Shopify A/B Testing – Smarter Experiments for Higher Conversions [Advanced Users’ Guide]

So, you’ve been running A/B tests on your Shopify store, but not sure if you’re doing it right?

Or not getting the desired conversion rate despite finding the winner?

You need smarter experiments that deliver higher conversions. A/B testing is not just a technique that you simply set up on a tool and forget about it. You must develop a strategic approach at every step of the process.

So, in this blog post, we’ll walk you through the Shopify A/B testing guide that’s created for advanced users who are looking to optimize conversion rate.

[If you’re just getting started with A/B testing, we have a separate beginners’ guide on Shopify A/B testing.]

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What Makes Your A/B Test Reliable and Effective?

If you’ve already tried A/B testing but didn’t achieve the expected outcome, you need to revisit your A/B testing strategy.

So, first, let’s understand what makes a successful A/B test. The following are the necessary items that must go into your A/B testing recipe to make it successful:

Comprehensive and reliable analytics setup

If you’re not tracking your store’s analytics with a proper setup, it’ll be difficult to define your A/B testing goals in the first place. Apart from Shopify’s native analytics tools, you should have the following setups:

• Google Analytics 4 (GA4):  To analyze website & app traffic details.

• Heatmaps & session recording app: To analyze the customer behaviors and patterns. Here are a couple of Shopify apps in this segment: 1. Microsoft Clarity: AI Insights 2. Lucky Orange Heatmaps & Replay

• [Optional] Revenue & net profit analytics: To analyze your net profit numbers. Check out TP: True Profit Analytics

Learn more: 10+ Best Shopify Analytics Tools 

Tracking of the key metrics

What metrics are you tracking right now? In order to get to the root cause of the problem or even to identify the right problem, you must track and monitor all key metrics.

Here are the key metrics that you should consider:

• Conversion rate

• Click-through rate

• Bounce rate

• Goal completion

• Abandonment rate

• Active users

• Scroll depth

• Engagement rate

• Retention rate

• Revenue

Learn more: Key Metrics for A/B Testing Success: Strategies You Need to Know 

Combining quantitative data with qualitative data

Qualitative data helps you identify the core issue and make the right decisions.

Peep Laja, the founder of CXL and a well-known conversion optimization expert, advocates the importance of qualitative research in A/B testing. Peep suggests it’s an essential factor to understand the ‘why’ — and identify what exactly needs to be improved.

Here are some of the ways to gather qualitative research data:

• Ask your customers through feedback surveys.

• Monitor and analyze their behaviors through:

• Heatmaps

• Session recordings

• Past orders

• Broad research of the problem you’re solving.

Precise hypothesis

Whenever talking of A/B testing, we always emphasize building a strong foundation with a precise hypothesis. If your A/B testing is not giving you the desired outcome, you should revisit your hypothesis. We’ll cover more on this later in this article.

Reliable A/B testing tool

Shopify App Store has many A/B testing solutions. Choosing the right one might be a daunting process. However, we highly recommend GemX: CRO & A/B Testing app.

GemX is built with our years of experience in Shopify CRO and A/B testing. Thus, you’ll find all the important settings you need, whether you’re just a beginner or an advanced A/B testing user.

Patience

Yes, A/B testing can sometimes test your patience. If you give up or get frustrated within a week of starting the campaign, it’s of no point. Develop the mindset and patience to wait for the right time to end the test and choose “the right winner”.

When Should You Run an A/B Test on Your Shopify Store? (And when you shouldn’t!)

Every e-commerce brand wants to increase the conversion rate, and there are lots of different ways to do so. A/B testing is one of them.

That said, not every eCommerce brand necessarily needs to run A/B tests. So, the question is:

When to Run Shopify A/B Testing Campaign?

• You have identified a problem that needs to be solved.

It’s said that if nothing is broken, why fix it?

So, in most cases, A/B testing comes into play when your metrics are not performing up to expectations. For example, if your Shopify store is struggling with issues such as a low conversion rate, high cart abandonment rate, spike in bounce rate, etc., A/B testing is your solution.

• You have sufficient traffic to drive reliable results.

If your Shopify store has more than 10,000 monthly visitors, you can experiment reliably with that volume. On the flip side, if you haven’t managed to get sufficient traffic yet, it indirectly indicates that you need to put more effort in that direction instead of A/B testing.

• You’re introducing changes or new offerings to your site.

Now, here’s an exception to the first point we discussed. Here, you’re not trying to fix a problem but perform A/B testing as a preventive measure. Before spending thousands on paid ads, it’s better to run an A/B test and figure out what messaging would work better for your target audience.

When NOT to run an A/B Test?

• When you’re still figuring out the basics.

If you’ve recently launched a brand and haven’t built a solid foundation yet, e.g., creating a sales funnel, it’s better to focus your energy and resources on building the foundation.

• During an event that might influence customer behavior.

When you have ongoing special offers, holidays, or other events that may heavily influence the purchasing behavior of your target audience, don’t run A/B tests. 

For example, don’t plan an A/B test during BFCM week. It’s the phase where you should be capitalizing on the insights from your test results run before the holiday season.

• When you haven’t defined a precise hypothesis for the test.

The A/B testing process starts with a hypothesis. If you haven’t figured out your hypothesis yet, take some time to come up with a data-backed (qualitative + quantitative) hypothesis.

Step-by-Step Guide on Advanced Shopify A/B Testing

As an advanced A/B testing user, you already know the basics of A/B testing and how the traffic is distributed with two different variants.

So, here in this guide, we’ll cover more of the strategic aspects that you need to implement in your A/B testing practices depending on your business case.

#1. Be precise about your goal

What exactly are you trying to achieve? 

While increasing the conversion rate is a common goal most brands are aiming at, some brands are also looking to increase “profit per visitor”.

For example, if your main goal is conversion, you’d aim to change or enhance the elements that would entice users to take action. Things like improving the design or visibility of the CTA button, social proof, headline copy, and so on.

However, if you’re looking to increase your profit per visitor/order, you may test your offer with “free shipping” (original offer) vs. “paid shipping” (variant), which has a direct impact on your store’s profit.

Defining this goal sets a clear direction and vision for your campaign at each step.

#2. Understand the customer psychology

Before starting your A/B test, you must define a hypothesis. However, in order to nail your hypothesis, you must understand the psychology of your customers.

How do you do that?

Study the quantitative data with qualitative research that you’ve gathered and generate insights on customer psychology. You can even use external research and reports relevant to your target customers.

For example, if you’re a jewelry brand focusing on gift items, you need to study customer psychology around what matters most to them in their buying decision. Most likely, you’ll find that messaging will have a stronger influence, which sometimes may even exceed the pricing aspect.

#3. Define a robust hypothesis

Knowing the basics of the A/B test hypothesis is one thing, and implementing it in your business case is another. Invest time and effort into crafting the hypothesis that touches upon the pain point that’s affecting your conversion rate.

Here are the three crucial parts of your hypothesis and what you should consider in them:

• Theory — Is your observation in the theory formed with data? It shouldn’t be just an assumption.

• Validation — What exact change will validate your theory? When your focus is on conversion optimization, the change must impact the conversion metric.

• Outcome — What outcome or impact are you expecting from the change? This must be aligned with the goal you defined at the beginning.

#4. Define the type of A/B test

A/B testing is not a “one solution fits all” technique.

Different problems need different solutions. Once you’ve identified the problem statement and hypothesis clearly, the next decision you need to get right is the type of A/B test.

If you’re using GemX, you can perform “Template Testing” as well as “Multipage Testing”.

Template Testing:

In “Template Testing,” you can test elements like headlines, buttons, images, social proof, and so on, which are covered on a single-page template.

Multipage Testing

“Multipage Testing” takes your experiment to a whole new, advanced level.

Here, you’re able to compare two different store experiences within a single test. Traffic distributed to both versions (Control and Variant) remains in their respective journey, and thus, you’re able to differentiate and identify the best store experience for your customers.

In most cases, you don’t need to change the entire template or website. Identifying the required change that could have the biggest impact is the real task here.

“A radical redesign where you change all the website is extremely risky and often I would say 50% of time it backfires meaning in most cases, I would say 60, 70% of cases, there is no difference whatsoever in conversion rate.” - Peep Laja

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#5. Run your A/B test with advanced logic

When you’re running an A/B test at an advanced level, you must execute it with specific logic or conditions. To achieve this, you must use a powerful A/B testing tool like GemX because it provides all the advanced logic configurations:

5.1. Winning metric

With this setting, you define which metric will be your primary deciding factor for the winner. There are two options:

1. Conversion: Applicable if your goal is the conversion event, regardless of the order value.

2. Revenue: Applicable if your goal is to increase the revenue or average order value, and not just the conversion aspect.

5.2. Traffic split

Traffic split should ideally be kept at 50-50% only, so that each template gets an equal opportunity.

5.3. Device types

Here’s where advanced users should implement critical thinking along with the data analysis. 

According to KISSmetrics, the difference in eCommerce conversion rate by device types has been a consistent pattern:

• Desktop: 3.5% to 4.5%

• Tablet: 2.5% to 3.5%

• Mobile: 1.5% to 2.5%

Now, to understand the importance of device-wise traffic distribution, let’s consider this hypothetical example:

• Control template: Receives 80% traffic from desktops and the remaining 20% from tablets and mobile devices.

• Variant template: Received 70% traffic from mobile devices and the remaining 30% from desktops and tablets.

Which version do you think got an unfair advantage in gaining a higher conversion rate?

Obviously, the one that got more traffic from desktops, right? This is the reason you should consider device-wise traffic split in your A/B test.

5.4. Visitor types

There are two types of visitors in this setting: 1. New 2. Returning.

Deciding which types of visitors to select or exclude depends on your hypothesis.

For example, let’s say you’re conducting an A/B test for a promotional pop-up that showcases a $20 gift coupon offer on the first order. Thus, you’d want to exclude the returning visitors, because for them, the offer is not applicable.

5.5. Traffic sources

Just as we’ve seen the strategies to include or exclude device and visitor types, you should consider the traffic source with a similar thought process.

For example, let’s say you’re running an A/B test on your product page, and you’ve recently run a personalized email marketing campaign for the same product. In that case, you should exclude the “Email” traffic because their purchase intent may have been influenced by your email campaign.

5.6. Markets & languages

Set up these advanced conditions according to your business/product type, A/B test goal, and other factors that can influence the accuracy of the test.

#6. Consider a valid timeframe and statistical significance

These two are crucial aspects of your A/B testing fundamentals.

6.1. Timeframe or duration of the test:

How long should you run the test?

The short answer is a minimum of two weeks. But it can go longer than two weeks as well.

6.2. Achieving statistical significance:

What statistical significance should be considered before ending the test?

Ideally, 95% — it’s the industry standard statistical significance level. However, in some cases, a minimum of 90% statistical significance can be acceptable.

So, consider both of these aspects before you end your A/B test. For example, let’s say you’ve completed two weeks but still haven’t reached even 90% of statistical significance; you must not stop the test.

7. Analyzing your A/B test results

If you want to take your A/B testing game to the advanced level, you don’t just enhance the method; you should also look at the results from an advanced perspective.

7.1. Focus on the ‘WHY’

Whether your variant passes the test or fails, you still need to pay careful attention to the numbers as well as qualitative observations.

Don’t just take the result at face value. Try to understand the reason behind it. 

For example, if your variant with a different headline copy won over the control version, understand why that messaging resonated more with that set of audience.

7.2. Analyzing the numbers

Of course, we won’t disregard the importance of numbers. Consider the following key aspects:

• Sample size

• Impact on the primary metrics (e.g., conversion rate)

• Segment analysis (if the test was implemented on multiple segments)

• Device types

• Visitor types

• Traffic sources

7.3. What to do if the test fails?

Remember — even if your A/B test fails, it’s your gain in terms of insights you generated through the test. Also, you can analyze the observations of the failed test and reiterate with new changes.

7.4. Document test results, data, and observations

This applies to everyone, whether you’re a beginner or an advanced user. Documenting your A/B test data and observations creates a systematic approach in your marketing.

Quick Tips on Conversion-Focused A/B Testing Ideas & Strategies

A/B test your messaging

We talked about the psychology already. People need a strong reason to buy or subscribe to anything — and persuading your target audience requires compelling messaging.

A/B test your offer

The offer itself (with the discount or other incentives) influences your site visitors’ buying decision. Thus, A/B testing your offer can have a significant impact on your conversion rate and revenue.

Prioritize pages and high-impact elements

When talking of pages, landing pages have huge importance in boosting your conversion rate. But even within landing pages, you should consider conversion-focused elements such as:

• Title/Headline copy

• Social proof

• CTA button

• Hero section

• Primary image/video

Test the frictional areas in the buyer journey

If your goal is to increase the conversion rate, figure out what causes friction in the conversion event. Now, it’s imperative to note that this depends on your specific conversion goal.

• Purchase event: Test the add-to-cart flow, checkout form, etc.

• Signup event: A/B test different form layouts, number of fields, etc.

A/B test promotional pop-ups

Promotional pop-ups have a huge impact on your store’s conversion rate. Optimizing your store’s pop-up through A/B testing can lead to a better conversion rate and increased revenue.

Final Thoughts on Shopify A/B Testing

As a pro A/B testing user, you must develop a systematic and strategic approach.

Every decision and experiment must be aligned with your data insights and business goals. Keep experimenting as long as you know there’s a scope of enhancement.

Last but not least, install the power duo of Shopify CRO — GemPages and GemX, if you haven’t already. These two apps will help you boost the effectiveness of your store design, CRO, and A/B testing campaigns.

Learn more advanced eCommerce marketing strategies, tools, and best practices on the GemPages Blog. Also, join the GemPages Facebook community to network and learn from like-minded eCommerce entrepreneurs and experts.

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FAQs About Shopify A/B Testing

When should I run an A/B test on my Shopify store?

Here are some of the basic factors you should consider before starting A/B testing campaigns:

• You have identified a problem that needs to be solved
• You have sufficient traffic to drive reliable results (around 10K or more monthly visitors)
• You’re introducing changes or new offerings to your site

How to increase conversion rate with Shopify A/B testing?

To increase the conversion rate of your Shopify store through A/B testing, you should focus on conversion-focused elements in your hypothesis. For example, if you’re running an A/B test on your product or landing pages, headline copy, hero or primary image, CTA button, and social proof are some of the most crucial elements from a conversion standpoint.

What do I need to run a successful A/B testing campaign on Shopify?

Here are the most crucial aspects for a successful A/B testing campaign:

• Comprehensive and reliable analytics setup to ensure your foundation is data-driven
• Tracking of the key metrics to identify the problem
• Combining quantitative data with qualitative data to learn customer behavior and patterns
• A precise hypothesis that nails the theory, change, and expected outcome
• A reliable A/B testing tool like GemX: CRO & A/B Testing app

What are the best apps to set up robust A/B testing on Shopify?

We’ll cover the recommended apps for each area that plays a crucial role in Shopify A/B testing:

• Microsoft Clarity or Lucky Orange for qualitative data
• GemX: CRO & A/B Testing app for advanced A/B testing setups
• GemPages Landing Page Builder to easily create different versions of your store or landing pages

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Shopify Guide