As a marketer, imagine you’ve crafted the ultimate ad. The copy is concise and engaging; the visuals are clear and enticing. Your keyword strategy is data-driven and immaculate, your landing page is designed for maximum conversion.
Or… is it? The truth is, you can believe that you’ve got the best possible ad for a brand, but you won’t know until it’s out there and real potential customers are using it every day. The success of any ad campaign hinges on how well the elements in your campaign – from ad copy to landing page design – resonate with your audience. Yet, without strategic testing, it’s hard to know what really works.
A/B testing, also called split testing, lets marketers make data-driven decisions by comparing two versions of a digital asset (or more, but ideally just two at a time). This enables informed optimizations that, over time, will help you increase conversions, improve engagement, and boost your ultimate return on investment (ROI).
In this guide, we’ll cover everything you need to know about A/B testing in marketing, including ways to optimize your A/B testing, some A/B testing best practices, and some more advanced techniques like multivariate testing, multi-armed bandit testing, and more.
What Is A/B Testing in Marketing?
Imagine you’re designing a landing page, and your two brand colors are blue and orange. When you add the CTA button, you think blue looks better with the other colors on the page, but orange might “pop” more and stand out. Which should you choose?
Well, with A/B testing, the answer is “you choose both.”
In marketing, A/B testing is comparing two versions of an asset, like an email, ad, or landing page, and seeing which one performs better. This simple technique provides you with invaluable concrete data on which variation resonates most with your audience. You don’t need to guess; you know, for a fact, that one performs better than the other. This helps avoid sometimes costly random trial and error in your marketing campaigns – rather, A/B testing gives you data that lets you make informed decisions that you can use to refine campaigns over time.
So, in this case, you would launch both versions of the landing page, one with a blue button and one with an orange button, and direct 50% of all visitors to one and 50% to the other. You would let the campaign run for some time and measure the results as to which button had a higher conversion rate; then, you would sunset the loser and direct all your traffic to the winner.
Here’s another A/B marketing example: Imagine you’re running an email marketing campaign to encourage abandoned-cart shoppers to come back. You have two subject lines that you think might perform well. Using A/B testing, you’ll send Subject Line A to half of your audience and Subject Line B to the other half. (That’s why they call it A/B testing!)
By measuring the open rates for each subject line, you can determine the more effective variant and use that version moving forward. This targeted approach allows for continual development, which ensures your marketing assets evolve and are always improving.
A/B Testing: Why It’s Indispensable for Marketers
The benefits of data that can drive steady improvements and refinements in a campaign are many – arguably too many to list in a single blog.
First and foremost, that is the primary benefit of A/B testing: It allows marketers like you to base your decisions on data and facts, rather than intuition or guesswork. Today’s digital landscape gives marketers countless pieces of data with how users are interacting with their content across multiple channels. It can be almost overwhelming to pick the signal out from the noise. A/B testing simplifies this, and helps brands and marketers understand what most effectively draws attention, captures interest, and encourages action.
A/B testing helps you:
- Make incremental optimization. Rather than overhauling entire campaigns to start from scratch, or redesigning whole websites based on assumptions, A/B testing lets you make small, incremental changes to improve campaigns little by little. This approach is less disruptive, more manageable, and ultimately more effective, with each test building on the results of the last.
- Improve the customer experience. Testing different elements of your website or your marketing materials helps you refine the customer journey, making it easier and less of a hassle for users to interact with your brand and eventually purchase the product or services that they want. For example, testing different landing page layouts or form fields can reveal what makes users bounce off in frustration, and what makes the user experience more seamless.
- Maximize efficiency for better ROI and Return on Ad Spend (ROAS). Every marketing dollar counts. By testing and committing only to the best-performing elements, you ensure your resources are allocated toward strategies that yield effective results. This, simply put, saves you money and makes your marketing campaigns more profitable. Who doesn’t want that?
- Mitigate risk. A campaign with suboptimal results is frustrating. Blowing it all up to start all over again is worse – and there’s no guarantee that starting from scratch will actually deliver any improvements. What if you start over but you don’t perform any better, or actually perform worse? A/B testing lets marketing business and teams test small changes to drive better performance without committing to full-scale adjustments or campaign overhauls. This is fundamentally a much lower risk way to validate ideas and gather valuable data before you alter a campaign.
Where Should You Use A/B Testing in Marketing?
One of the great parts of using A/B testing as a technique is that it’s incredibly versatile – it can be applied across nearly any marketing channel or asset, from emails and landing pages to ads and product pages. However, there are some parts of your marketing campaign that will be more obviously helped by A/B testing than others. Here are some of the most optimal contexts and places to apply A/B testing for your marketing campaigns.
Email Campaigns
Email marketing, even in this age of social media, remains one of the most efficient and direct ways to reach customers, and A/B testing can help you optimize many different aspects of your email – leading to higher open rates, click-through rates (CTR), conversions, and more.
Some of the elements you can improve with A/B testing include:
- Subject lines. These are the first things users see, most of the time, and so this is a great way to improve open rates.
- Layouts. You can experiment with different formats – text-only emails vs. ones with images, for instance – or try different layouts, like deciding which content goes “above the fold.”
- CTAs. Try variations in button color, placement, and wording – these can all enhance click-through rates.
Here’s an example of A/B testing in emails: Imagine you’re an online retailer testing different email layouts for a seasonal promotion. One version might feature a bold CTA immediately at the top, while the other integrates the CTA into the body text. Depending on which variant gets a better CTR, you can move forward with a better understanding of which approach resonates more with your audiences.
Landing Pages
Ah, the landing page. The gateway to conversion, so to speak. These are prime candidates for A/B testing. Seemingly simple changes, like adjusting the layout, CTA, or imagery, can lead to significant gains by improving conversion rates.
- Headline variations. A great headline entices a reader to keep reading; a poor, uninteresting, or confusing one means they might bounce then and there. Since headlines are so important on a landing page, testing different messaging styles (e.g., question-based vs. benefit-driven) can be extremely effective.
- Form fields. Lengthy forms with too many input boxes can be discouraging and can be another common bounce point. Test different field requirements or even the order of arrangement in which you put the fields to try to increase sign-ups.
- Visuals and design. You can adjust image styles, color schemes, and the placement of elements like videos or infographics to test how these impact user engagement and conversions.
A SaaS company, for instance, might test the wording of different CTAs on their landing page for a free demo. On version A, they could use the phrase “Start Your Free Trial,” while on Version B, it could read “Ready to Get Started?” They can then see which CTA drove more users to take action.
Ad Copy and Visuals
An extremely well-polished landing page doesn’t do you much good if nobody is visiting it, however. Given that every click on a paid ad has a direct cost associated with it, using A/B testing for your PPC campaigns is a great way to optimize ad spend and boost ROAS.
You can test things like headlines – should you use catchy headlines or straightforward ones? – to determine which variants capture attention. You can adjust the ad copy in subtle but meaningful ways, like trying to see if “limited time” is more effective than “exclusive offer” or vice versa.
In platforms like Facebook and Instagram with significant visual elements, the choice of image can heavily influence ad success or failure. Especially on these platforms, image A/B testing is a great idea to boost the success of your paid campaigns.
For example, a travel business might test two versions of a Facebook or Instagram ad for their new travel package, one featuring an image of a beautiful tropical beach and another a majestic mountain scene. The success of these ads in driving clicks and engagement can help this business identify what sort of imagery appeals more to their target audiences.
Setting Up Your A/B Testing: Best Practices
All right, so we’ve convinced you that A/B testing is worthwhile for your marketing brand. Great! The success of any A/B test hinges on planning and execution both. Let’s go over the step-by-step guide to how to set up an A/B test, keeping an eye on some important best practices along the way.
A/B Testing Step 1: Establish a Clear Objective
You can’t just start changing things at random on your landing pages and ad messaging. The first step in setting up an A/B test is to define a specific, measurable goal. Think about the key performance indicators (KPIs) that are most relevant to your business and this campaign – increasing sign-ups for demos, improving sales, and so on – and align your objectives with success in this area.
A well-defined goal gives your test purpose and direction, helping you design an experiment that will yield real insights.
For instance, take the A/B testing example from earlier of the travel business. The purpose of using an image of the beach vs. the mountains was to determine the sort of imagery appealed more to their audience. They can use this to inform their advertising moving forward, i.e., they will use more beach images.
This A/B test would not be to determine the sort of messaging that improves clicks. That would be for a separate test entirely.
A/B Testing Step 2: Develop a Hypothesis
After you’ve identified your goal, create a hypothesis based on your understanding of the current performance and your audience. As with the scientific method, a good hypothesis is three things: Clear, testable, and grounded in logic.
For example, if you’ve noticed low conversions on a product page with an overly wordy description, an effective hypothesis might look like this: “If we simplify the product description to make it more scannable, conversions will increase.”
A/B Testing Step 3: Choose the Element to Test
In A/B testing, isolating a single variable is key to obtaining reliable results. Imagine if you have Page A, with one headline and a CTA button in a certain location, and Page B, with a different headline and a new location for the CTA button. If Page B performs better, was it the headline or the CTA placement? You won’t know!
Testing only one element at a time is a vital A/B best practice to ensure you adhere to at all times. Some common elements to test include:
- CTA: You can test the CTA placement or the CTA text itself. Try experimenting with action-oriented language vs. curiosity-driven language.
- Images: Images play a huge role in evoking emotions. Testing different styles, such as purely product-focused versus lifestyle-oriented, can be illuminating.
- Layout: The arrangement of elements can impact how users navigate a page or email, which in turn influences engagement.
A/B Testing Step 4: Set a Sample Size and Test Duration
You could leave your A/B test running into infinity, but would that actually help? You need an adequate sample size, but just as important is turning your test off to assess the results. Based on your expected traffic volume and desired confidence level, you can use an A/B testing calculator to determine if your results are statistically significant.
It’s crucial to avoid stopping a test too early; this can lead to misleading results.
A/B Testing Step 5: Run the Test
With your test prepared, it’s time to go live. Tools like Google Optimize and Optimizely can help you dramatically simplify the process, letting you run effective A/B tests with minimal technical expertise.
A/B Testing Step 6: Analyze Results, Draw Conclusions, and Implement the Winner
After your test has reached statistical significance, analyze the data to see if there’s a real meaningful difference between the variations. Your chosen A/B testing software can help you identify which variation is the winner, but you’ll need to use some critical thinking about what the results could mean.
If a different CTA increased clicks, why did it perform better, and what lessons can you take into future marketing efforts?
Either way – implement the winning version for better results across your campaign.
A/B Testing: Other Things to Know
Here are some other concepts and foundational terms you’ll see when discussing A/B testing. (They didn’t make much sense to put anywhere else).
- Split testing vs. A/B testing: What’s the difference between A/B testing and split testing? The terms can be used interchangeably, but generally speaking, you’ll see “split testing” referring to testing two entirely different versions of a page, while A/B testing typically focuses on altering just one variable – like the CTA or headline – in the same overall layout.
- A/B/n testing: This is an extension of A/B testing where multiple variations are tested simultaneously, e.g., A, B, C, and D. This is great for exploring several different approaches at once, but it requires a significantly larger audience to produce statistically significant test results.
- Multivariate testing: Between split testing, which tests entirely different pages, and A/B testing, which isolates one variable at a time, multivariate testing examines multiple elements simultaneously. For example, you could test different combinations of headlines, images, and CTA buttons on a landing page to see which performs best. However, this type of testing requires substantial traffic for a clear result.
- Multi-armed bandit testing: This method dynamically adjusts traffic distribution among the varied sites in real time. It’s useful for high-traffic sites where rapid optimization is necessary – such as during a Black Friday sale – as it prioritizes the better-performing variations early on, rather than waiting until the end of the test.
What Can A/B Testing Tell You?
It can be tempting to run an A/B test, choose the winning variation and move on. But as a marketer, you will get far more value from your hard work by more thoroughly analyzing the results.
Consider secondary metrics. For example, your main KPI to consider might have been CTR, but did the change impact any other metrics, like bounce rate or time on page?
Look at long-term or time-based trends. While some changes may yield immediate returns, looking at how a variation performs over time can provide more insight. For example, take the travel business from earlier. Maybe the beach variant performs better than the mountain variant in the winter, but the mountains perform better in the fall when people are excited about autumn foliage?
Lastly, identify patterns in user behavior over multiple A/B tests over time. If user engagement improves every time you simplify a page layout, for instance, this trend could indicate that the audience you attract prefers straightforward, no-nonsense designs.
A/B Testing – Start Marketing Like the Pros
When you use A/B testing as a foundational tactic in your marketing efforts, you ensure that your campaigns are consistently in alignment with your audience’s preferences. Each test you run brings in new data, which leads to new insights, helping you refine your approach and reach a customer experience informed by data and optimized for success.
Want help A/B testing your marketing efforts? Talk to SevenAtoms today! We’re an expert digital marketing with mastery over things like landing page design and A/B testing – and that’s just a start. Get in touch for a free consultation for your marketing efforts.
