A/B Testing For Beginners: Everything You Should Know To Get Started

20 min read

If you’re running a small business, then you know that every penny counts. You can’t afford to waste money on ad campaigns that don’t work, or settle for a website that’s not converting visitors into buyers.

That’s why A/B testing is so important—it helps you make decisions about your website, email campaigns, and ad campaigns that could lead to more sales with minimal investment.

In this article, we’ll explain what A/B testing is, how to get started, and some of the benefits of using this simple but effective marketing tool.

What Is A/B Testing?

A/B testing, also known as split testing, is a powerful method for testing variations of a marketing asset or web page to determine which one performs better.

It involves creating two (or more) versions of the same content, each with a specific variation, and then showing them to different segments of your audience to measure their performance against a predefined goal.

By comparing the results, you can identify the most effective version and use that insight to optimize your marketing efforts, boost conversions, and drive business growth.

In essence, A/B testing allows you to fine-tune your marketing strategies based on real-world data, ensuring that every element of your campaign is primed for success.

For example, you could create two different designs for a landing page and send traffic to both pages equally. By tracking how each version performs, you can determine which one is more effective. You can then make decisions based on the data you collected.

Image source: Towards Data Science

A/B testing helps identify the effective elements in your marketing strategies. From your website design to your email marketing, it is the best way to find what works for your target audience.

How to Conduct an A/B Test

The following steps will guide you on how to start A/B testing. You can use these steps to make your own tests and apply the results to your business.

Step 1. Define your variables

The very first step of an A/B test is clearly determining what you want to assess. The first question is, will this be an off-site or on-site test?

On-site tests include all the elements of your website that are sales-related. For example, you can test your CTA text, the placement of your CTAs, headlines, images, video content, pop-ups, potential domain names, and more.

Off-site tests look at the effectiveness of advertisements and sales emails. You will do this kind of test to determine if your ads and emails drive traffic and result in conversions.

Deciding what exactly you need to test depends on your current goals. What do you want to improve? For example, if you’re not satisfied with your last advertising campaign, you can test new ad creatives to improve the performance of your marketing campaigns. Or, if you’re redesigning your website, you can test different home pages to see which one makes visitors spend more time on the site.

Step 2. Come up with a hypothesis

Now that you know what variables you’re going to test, it’s time to create a hypothesis. Think about what changes you can make to get the results you want.

Make a list of everything you think you can do better and the ways you can improve. Should you write better CTAs? Can your emails use more images? Should your website have a different layout?

After you come up with different hypotheses, you need to prioritize them. Identify the best and most important ones. Think about how you can execute your A/B tests to test them. Also, consider how difficult they will be to implement and their potential impact on customers.

Finally, you need to decide how your A/B test will run. For example, when testing emails, you’ll need to send out two different versions and track which version gets the best results.

For this, identify which email elements you’re going to test, such as the subject line, copy, images, etc. Then consider measurement metrics like open rate or click-through rate (CTR) to differentiate and compare versions.

Step 3. Set a time limit

You also have to decide how long to run the A/B test. This isn’t something that someone else can decide for you — you’ll have to learn on your own intuition and find the time frame that works best for you.

Generally, A/B tests for email campaigns can run from two hours up to a day, depending on how you determine a winning version—typically based on opens, clicks, or revenue. It is recommended to wait at least two hours to determine a winner based on opens, one hour to determine a winner based on clicks, and 12 hours to determine a winner based on revenue.

An example of setting up a test in Mailchimp to compare what email content drives more revenue

For ads, you should run the campaign for a minimum of 7-day tests, because shorter tests may produce inconclusive results. For Facebook ads, you can run A/B tests for up to 30 days.

When it comes to websites, recommendations vary, suggesting you should run A/B tests for one week up to a month. Keep in mind the difference between shopping behavior during the weekend and weekdays before making a decision.

If you’re just getting started with A/B testing and are not sure how long your test should run, you can use an A/B test duration calculator. After you run a few tests, you will get a better idea of the ideal time limit for each type of test.

Step 4. Test each variable separately

Once you have determined which variables you want to test, you should narrow it down to only one. You will test the variable by creating two alternatives. You will test these against each other.

If you have multiple elements of a campaign or website to test, always run one test at a time.

It’s better to run A/B tests separately rather than running them all simultaneously. Testing too many variables at once will make it difficult to determine which parts were successful or not.

By only changing one variable while keeping the rest constant, the resulting data will be easy to understand and apply.

Step 5. Analyze results

Your goals will determine how you analyze the results of your A/B test. For example, if you want to test ways to increase your website traffic, you should test blog post titles and webpage titles. After all, titles should grab someone’s attention and make them want to learn more.

Every variable you test for will have different metrics, and produce different results. Here are a few examples of potential goals and variables to change in your A/B test:

Conversion rate improvement (you can change CTA text, colors, and element placement)
Bounce rate reduction (test product descriptions, fonts you use in listings, and featured images)
Website traffic boosts (change the placement of links)
Lower cart abandonment rates (use various product photos)

You can also break down your results by different segments of your audience. You can determine where your traffic comes from, what elements work best for mobile vs. desktop users, how new visitors are attracted, and more.

Your options are almost limitless:

Source: Right On Interactive

Not sure about the test results you got? One way you can see the accuracy of your tests is through customer feedback. After changing your marketing based on your findings, embed a survey form on your website to receive feedback from your audience to see if they enjoy the changes you made.

Step 6. Adjust and repeat

The work doesn’t stop once you’ve got all your analytics neatly laid out. Now, you have to test again. Make more changes, run more tests, and learn from the new data.

Of course, you don’t have to run A/B tests one after the other. Instead, give yourself time to learn from the data you’ve gathered and develop creative ways to adjust your approach before you release a new test.

What Can You A/B Test

Here’s a list of website elements that you can A/B test to optimize your ecommerce performance:

Homepage hero images: Capture attention with compelling visuals that align with brand identity and evoke curiosity.
Call-to-action button colors: Test vibrant hues to drive user engagement and motivate click-throughs.
Product page layouts: Experiment with different arrangements to optimize user experience and sales conversions.
Pricing display formats: Test various pricing structures for clarity and persuasive impact.
Checkout page designs: Optimize layout for streamlined navigation and frictionless user experience.
Testimonials placement: Assess the impact of positioning customer testimonials strategically for credibility and trust-building.
Navigation menu styles: A/B test menu designs for intuitive, user-friendly navigation.
Search bar positioning: Evaluate the optimal placement for easy access and enhanced user convenience.
Email opt-in form variations: Test different form designs to boost subscriber acquisition and engagement.
Footer content and layout: Experiment with content arrangement for enhanced visibility and user interaction.
Promotional banner designs: A/B test visually appealing banners for promotions to maximize attention and conversions.
Social proof elements: Assess the effectiveness of social proof in building trust and driving conversions.
Video content placement: Test video positioning for maximum impact on engagement and product understanding.
Trust badges presentation: Experiment with trust badge placement to enhance credibility and reassure potential customers.
Font styles and sizes: A/B test fonts for readability and aesthetic appeal across devices and platforms.
Mobile responsiveness: Optimize for seamless user experience and conversion on mobile devices.
Related product section arrangement: Test layout to drive cross-selling and increase average order value.
Shipping and return policy visibility: A/B test for prominence to instill confidence and reduce purchase hesitation.
Live chat feature display: Test placement and visibility for enhanced customer support and satisfaction.
Exit-intent pop-up variations: A/B test to capture attention and encourage conversions before visitors exit the site.

A long story short, you can test every element of you online store to improve the effectiveness of your online business.

A/B Testing Can Help You Get Better Revenue

A/B testing allows you to fine-tune your website and marketing materials to ensure that they are optimized for maximum impact.

Maximize revenue

A/B testing allows you to experiment with different versions of your website, product pages, or marketing materials, helping you identify the elements that drive higher conversion rates. By fine-tuning these critical touchpoints, you can effectively guide visitors through the sales funnel, increasing the likelihood of conversions and boosting revenue.

Refine user experience

Through A/B testing, you can assess the impact of various design, layout, and functionality changes on user experience. By pinpointing the elements that best engage and resonate with your audience, you can create a seamless and intuitive user journey that encourages visitors to convert, ultimately leading to improved revenue streams.

Enhance product presentation

A/B testing empowers you to test different product images, descriptions, and pricing strategies to determine the most compelling presentation for your offerings. This allows you to showcase your products in the best light, effectively influencing purchasing decisions and driving revenue growth.

Tailor marketing messages

A/B testing can also be applied to email marketing, ad copy, and other promotional content. By testing different messaging strategies, offers, and calls-to-action, you can identify the most effective approaches to capture your audience’s attention and drive them towards making a purchase, thereby increasing revenue.

An example of testing different subjects for a promotional email campaign

Pros an Cons of A/B Testing

As with each medal, A/B testing has good and bad sides. Let’s find them out.

A/B testing pros

Data-driven decisions: A/B tests provide concrete data for making informed decisions about changes, enabling businesses to base optimization strategies on real user interactions and preferences.
Improved user experience: By testing different variations, businesses can refine and enhance the user experience, leading to higher satisfaction and engagement with their ecommerce platform.
Increased conversion rates: A/B testing can lead to higher conversion rates by identifying and implementing the most effective design and content elements that resonate with the target audience.
Reduced bounce rates: Through iterative testing, businesses can pinpoint and rectify elements that contribute to high bounce rates, ultimately improving user retention and engagement.
Enhanced content: A/B testing allows for the evaluation and refinement of content, resulting in improved messaging and communication with potential customers.

A/B testing cons

Time-consuming: The process of setting up, running, and analyzing A/B tests can be time-intensive, requiring careful planning and execution to yield meaningful results.
Limited scope: A/B testing may have limitations in testing comprehensive site-wide changes, as it typically focuses on specific elements or variations at a time.
Risk of false positives: There is a risk of drawing erroneous conclusions from A/B test results, potentially leading to misguided optimization decisions if statistical significance is not rigorously upheld.
Technical errors: Implementation and execution errors in A/B tests can lead to skewed results, undermining the reliability of the testing outcomes.
Short-sightedness: Focusing solely on A/B testing may lead to an emphasis on minor design changes at the expense of holistic, big-picture improvements, potentially missing out on broader optimization opportunities.

3 Types of A/B Testing

There are three main types of A/B testing.

Split testing: This classic form of A/B testing involves comparing two versions (A and B) of a single variable to determine which performs better in achieving a specific goal, such as click-through rates or conversions. It’s ideal for assessing the impact of individual changes, like call-to-action button color or headline text, providing valuable insights into user preferences and behavior.
Multivariate testing: Unlike split testing, multivariate testing allows you to evaluate the impact of multiple variations of different elements simultaneously. By analyzing the combined effects of various changes, such as headline, image, and button color, you gain insights into how these elements interact to influence user engagement and conversion rates, helping you make informed decisions about holistic page optimizations.
Multi-page testing: This approach involves testing entire web pages against each other rather than specific elements. It’s valuable for evaluating the overall layout, content structure, and design of different page versions, providing insights into which page configurations resonate best with your audience and drive desired user actions.

These testing methods empower ecommerce businesses to make data-driven decisions, optimize user experiences, and maximize conversion rates by understanding the impact of changes on their websites or apps.

4 Most Common Mistake in A/B Testing

When it comes to A/B testing, steering clear of common missteps is pivotal to harnessing its full potential. Here are the four most prevalent mistakes to be mindful of:

Fault hypothesis: The most common mistake in A/B testing is having an invalid hypothesis. Every test begins with a hypothesis, and if it’s incorrect, the test is unlikely to yield meaningful results. It’s essential to formulate clear, data-driven hypotheses to ensure the validity and effectiveness of A/B tests. Without a solid hypothesis, the entire testing process may lack direction and fail to provide actionable insights for optimizing user experiences and driving conversions.
Ignoring statistical significance: Neglecting to ensure statistically significant results can lead to erroneous conclusions, jeopardizing the reliability of the testing outcomes. It’s crucial to rigorously assess the statistical significance of A/B test results to make informed decisions and avoid drawing misleading conclusions.
Testing too many hypotheses simultaneously: Engaging in multiple hypotheses within a single test can convolute the data and impede the ability to pinpoint the precise impact of each individual change. Focusing on too many hypotheses at once can dilute the clarity of insights derived from the testing process, hindering the ability to make well-informed optimization decisions.
Premature implementation of changes: Rushing to implement alterations based on preliminary or inconclusive A/B test results can be counterproductive. It’s imperative to gather robust and conclusive data over an appropriate duration before making significant alterations to your e-commerce platform, ensuring that decisions are rooted in sound and reliable insights.

Steering clear of these pitfalls can enhance the effectiveness of A/B testing, empowering ecommerce businesses to make informed, data-driven decisions and optimize user experiences with confidence.

You, Too, Can Run Effective and Comprehensive A/B Tests

There you have it—advice to get you started with strong A/B tests that will quickly help your business. Remember that your business is unique, and the knowledge shared here only gives you a template to work from. Use our steps to build the best A/B tests for you and your goals, even if you’re not a marketing guru.

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Marketing and Promotion

Oct 8, 2023

About the author

Max has been working in the ecommerce industry for the last six years helping brands to establish and level-up content marketing and SEO. Despite that, he has experience with entrepreneurship. He is a fiction writer in his free time.