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A/B Testing To Increase eCommerce Conversion Rates - Everything You Need To Know

Co-founder, CEO
A/B testing
Tags :
5 min

Before getting into the details of what is A/B testing and how it boosts eCommerce conversion rate, let us start with an example.

How A/B Testing Helped This eCommerce Brand Achieve A 2X Increase In Total Purchases..

Grene, a Poland-based eCommerce brand that sells agriculture-related products, was looking to reduce cart abandonment and increase conversions. They wanted to find out if redesigning the mini cart page (an in-page cart popup) would help them achieve this and increase cart page visits. In order to do that, they had to A/B test the original and the proposed design.

This was the original design:

Grene A/B testing before

They revamped the design to something like:

Grene A/B testing before

Comparing the two, the new design had the following changes:

  1. An extra 'Go To Cart' CTA was added to the top of the mini cart page.
  2. The 'Go To Cart' CTA at the bottom of the mini cart page was made larger.
  3. The 'X' option to remove individual products from the cart was moved to the right and made more prominent.
  4. The total price per product was included.

Without making any other changes to the site or marketing campaigns, they got the following results from the new mini cart page design:

  • An increase in visits to the cart page.
  • The conversion rate increased from 1.83% to 1.96%.
  • Total purchase quantity increased 2X.

The conclusion was that design B, the new proposed design, was positively impacting conversions and was made the final design. (Case study source)

A/B testing is an incredibly powerful strategy for identifying issues and identifying which assumed solution is the right one. In this article, we dive deep into A/B testing and cover:

  • What A/B testing is.
  • The impact of A/B testing on eCommerce sites.
  • 5 elements of an eCommerce store that can be optimized through A/B testing.
  • How you can boost conversions through A/B testing.

What Is A/B Testing?

If you notice, in the case study we explained above, the changes made to the mini cart page were just minor design changes, but the results were huge. Some store issues are not obvious and are difficult to pinpoint. That's when A/B testing comes in handy.

A/B testing, or split testing, is a process where two or more versions of a variable (CTA size, sales copy position, ad creative, etc.) are shown to an audience segment at the same time to determine which version has the most impact and yields the best results for a measured business goal (like clicks or conversions).

A/B testing is an incredibly powerful way of weeding out bad designs and processes and identifying impactful ones. Did you know:

  • Improving UX design by A/B testing user flows can increase a business's conversion rate by 400 percent. (Entrepreneur, 2018)
  • 1 out of 8 A/B tests results in significant improvement for companies. (Invesp)
  • In the year 2000, Google ran an A/B test to determine the optimum number of search results to display per page. (Marketing Mag, 2018)
  • Microsoft's search engine Bing increased yearly revenue per search from 10% to 25% through A/B testing. (Harvard Business Review, 2017)
  • In 2012, Microsoft Bing increased revenue by 12% by making just a single ad display change that was identified through A/B testing. (Harvard Business Review, 2017)
  • The Obama campaign raised an estimated $75 million more through marketing decisions resulting from A/B testing. (Wired, 2012)

A/B testing is especially important for eCommerce sites that rely completely on the website for sales (unlike other businesses that have a sales team to convert leads). Optimizing the store and other marketing/advertising campaigns to the fullest is critical for growth and can be done through A/B testing.

The Impact of A/B Testing & Why It Matters

Here is why A/B testing matters for eCommerce stores:

Improves Customer Experience

When people visit an eCommerce store, they have a purpose in mind. They are looking to find the availability of particular products, to get more information about each product, and to finally purchase the product. Any hurdles along this journey from intent to purchase will result in poor customer experience and ultimately cost the store sales.

eCommerce stores can identify user pain points using tools like heatmaps, analytics, and surveys, but how do they identify the right solution? Through A/B testing.

By running multiple variations simultaneously, an eCommerce store can quickly identify which one solves customers' pain points and thus improve the overall customer experience.

Helps Reduce Bounce Rate

One of the biggest challenges in building a thriving eCommerce business is beating the competition. Customers today have numerous options for purchasing the same product, and they will not hesitate from bouncing across stores until they find the best one for them.

Acquiring quality traffic is expensive, and eCommerce stores must make sure they are making the best of this traffic. One important metric to measure how well the store is catering to traffic is bounce rate. A high bounce rate is indicative of bad CX.

The reason for a high bounce rate varies for each store, and there isn't a one size fits all solution they can apply. The best way to identify what is causing users to bounce off and how to make them stay is by A/B testing different UX and UI layouts.

Increases eCommerce Conversion Rate & Marketing ROI

A/B testing is a data-driven process. It gives you a clear 'winner' and a 'loser' based on data and lets you select a solution that is proven to work based on measured business metrics. There is no ambiguity when it comes to A/B testing.

A/B testing is also an incremental process. You tend to test small changes, implement the best one, then move on to the next small change. This allows you to gradually and surely improve your store while not affecting what is already working.

All of this helps you optimize your store for conversions in a gradual and consistent way while ensuring all decisions are backed by data. When the store is optimized for conversions, it obviously results in an increase in conversion rate, and since you are experiencing a big impact through small changes, your ROI on A/B testing is also higher.

5 Elements Of An eCommerce Store That You Can Measure and Optimize Through A/B Testing

Here are the major elements of an eCommerce store that you can experiment by implementing A/B testing in your store:

Call-To-Action, CTAs

A CTA, or Call-To-Action, is an element on your site that encourages a user to take action. Buttons and forms are examples of CTAs. CTAs take a user forward in their purchase journey, and as such, have a direct impact on conversions.

Different aspects of a CTA could encourage or discourage a user from interacting with it - its position, size, color, design, animation, and text copy. While there are some best practices for CTAs, what works best for your audience and store can only be determined by testing different features mentioned earlier.

You can do this through A/B testing. You can either place different variations of CTAs on different pages or use tools like Google Optimize to serve the same page but with different variations of the CTA displayed to different people. Through metrics like button clicks and user behavior and heatmaps and screen recordings, you can identify which variation is working the best.

Site Content

Your visitors get all their information from the content on your site. Is it giving them the information they need? Are the font style and color easily readable? Is the tone and writing style attractive to the reader? All of these factors impact the user. Here are some things you should A/B test:

Headings and subheadings

Hegood heading should be concise and deliver relevant information, and should not be redundant. Headings are larger and shorter, so they quickly draw users’ attention. It's not just what the heading says that matters; its position, size, style, and color also impact users who read it. You can A/B test all these factors to see what works best.

Body content

The content under each heading/subheading should be written with the purpose of adding value to the reader, and not for fluff. The writing style and tone will also play a role in nudging the user forward in their purchase journey as people from different regions react to different styles. You should A/B test different styles before fixing a particular tone and writing style for your store.

Email content

You can run A/B tests to see which email subject lines lead to the highest open rate, CTR, and conversions. 

Store UX

A website's UX has a major impact on customer experience and their purchase journey and is probably the most important element to get right. The UX involves:

  • The sitemap - different pages that the user can navigate to.
  • The layout and position of elements like CTAs, images, headings, text, etc., on each page.
  • The number of interactive elements and options per screen.

The UX is basically a map that defines how the user will move across the store and what they will interact with. Perfecting the UX can be a long-term process because of the number of elements involved, but it is definitely a worthwhile one. By A/B testing different parts of the UX, you can gradually work towards building a fully optimized store.

Testimonials & Reviews

In a survey conducted by Fera, 93% of consumers said online reviews influence their purchase decisions, and 60% of consumers said they read product reviews before making a buying decision. 

Social proof through testimonials and reviews of both the brand and individual products will greatly impact conversions.

Since consumers are actively looking out for social proof, an important question to ask is where do you place them, how many do you reveal at a time, and what is the best design to use. You can A/B test each of these elements to find the best location and design for testimonials and reviews.


Images have a big impact on the eCommerce conversion rate because anyone looking to buy a product online can only judge the product through its images. This is why A/B testing the size, positioning, and design of images on the site is important.

Since product images play a big role in attracting customers, start by optimizing images on product pages. Some things to keep in mind are the location of the image gallery, the size of the thumbnails and the active image, and the number of images to add.

How eCommerce Stores Can Use A/B testing To Boost Conversions?

A/B testing is powerful because it is a strategy that is easy to implement and yet has a big impact. However, there is a right way to go about A/B testing.

Do Your Research, Define Your Goals

Before you run any strategy, you need to do your research. In the case of A/B testing, you need to first have a complete understanding of how the element being tested (the website, a landing page, campaign, ad, etc.) is currently performing. Track all relevant metrics, so you have a benchmark to measure against.

Research the audience you are targeting. What are their likes and dislikes, what are their interests, and how can you incorporate these into your website or campaign.

Set concrete goals for your test. What metrics will you measure, and what will decide which variation is better? For example, if you are A/B testing CTAs, the click-through rate will decide how well each variation is performing, and if you are A/B testing, the checkout page layout conversions will decide how well each variation is performing.

Select the Variables you Want to Test

Implement user behavior measurement tools like Google Analytics (or any other analytics tool of your choice), heatmaps, and session recorders before you decide what to test. Study the results to find out what is driving users away, where they exit from, and what are their pain points. These will be the elements you need to change through A/B testing.

Run A/B Tests

Once you have selected the variables you want to test, you can create your A and B (or more) versions. A few rules you can follow for best results:

  • Tailor the variations by keeping your audience in mind. Each variation should be relevant to your target audience.
  • Create a repeatable process. You will be testing one variable per iteration, so you will need to run multiple A/B tests as you go forward.
  • Constantly measure results against the benchmarks you have set.

With this in mind, you can start A/B testing your store.

Analyze Test Results

With A/B testing, set a realistic timeline for testing and analyzing results. Depending on the amount of traffic you get per day, the duration will change. You want to make sure that you have collected a good number of samples before you analyze the results.

Once each variation has accrued enough numbers, you can compare the metrics that you already defined and select the winner. 

The Limitations of A/B Testing 

A/B testing comes with a set of limitations too! Before you embrace it, also think of the situations in which A/B testing make the most sense. . Here are a few to begin with: 

A/B testing is ignorant of users’ preferences 

A/B testing should not be applied when it comes to experimenting with different combinations of products for users, because it does not take user preferences into account. In this context, a personalized product recommendation engine like Argoid that understands users’ preferences and offers relevant, conversion-boosting product recommendations, may be more helpful. 

A/B testing may improve CTR but not conversion 

You can apply A/B testing to determine where to place your CTA  on your webpages, and optimize CTR. But, higher CTR doesn’t necessarily mean higher conversion. To convert from your product pages, you will need relevance. Else, users may click on the various recommended products, but your Average Order Value (AOV) will continue to be low. 

A/B testing limits the scope of personalization 

A/B testers may not understand the target audience deeply. While tests may reveal which categories or subcategories get the most attention, and could be highlighted via banners or ribbons, the display is mostly static and is based on the majority. It does not take into account an individual customer’s intent or interest. In this case, personalized product recommendation engines, make it easier to hone in on individual customers’ preferences through tailored recommendation ribbons like “Recommended for you”, “Products bought together” and so on. 

A/B testing may mean attractive UI but poor relevance 

Building an eCommerce website based on A/B testing can definitely make it aesthetically pleasing. However,  relevance may take a hit. ! A customer shopping for baby clothes may be presented with banners promoting the latest mobile phone, losing out on the opportunity for conversion. . 

Amazon UI

For instance, notice the UI of Amazon above. It might not be the best looking but it does try to aligns products and categories in such a way that user experience is not compromised, while catering to the user’s preferences.

A/B testing email variations are effort-intensive

Running split tests for email campaigns, changing subject lines, body copy, CTA, etc, can definitely improve the chances of conversion, but once again, it’s based on numbers, and does not take into account the person behind the email ID. The choice of variation is limited. Instead, an AI-based email personalization solution can tailor the email for each individual customer. While subject lines may still need manual intervention, it wouldn’t be advisable to leave the choice of category, brand and price preferences, cross sell and upsell options, to A/B testing.

Wrapping Up!  

eCommerce A/B testing is all about comparing different sets of on-page elements, email copies, product descriptions that enhance customer engagement and boost conversion. A/B testing can also be your go-to tool to understand the target audience, dig deeper into their requirements and finally convert them into your paid customers. With the right set of strategies and execution, A/B testing can bring record-braking results for eCommerce stores. 

A great alternative to A/B testing is personalization. That’s because, with personalization, you already have enough information about your customers and you can plan more effective strategies that boost conversion easily. 

To know more about AI-powered personalization, talk to us

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