Red or yellow? Read More or Learn More? Send that email on Monday or Friday? When marketers create landing pages, design call-to-action buttons, or write email copies, it can be tempting to use their intuition to predict what will make people click and connect.
Running A/B testing in your marketing content assets is a great way to learn how to drive more traffic to your website and generate more leads. Just a few tweaks in your email copy or call-to-action button can have a significant impact on the number of leads your business attracts.
60% of businesses that do A/B testing say it’s highly valuable for increasing conversion rates. In fact, a substantial 70% of brands witnessed an improvement in landing page sales through the implementation of A/B testing. Remarkably, certain businesses even reported an impressive surge of up to 50% in average revenue per user.
Therefore, it is important to conduct A/B testing than basing your marketing decisions on feeling as this can be detrimental to your business.
Read this article to know how insights stemming from A/B testing can help you drastically improve the conversion rate of your landing pages, CTRs of your website call-to-action, and email campaigns.
What is A/B Testing and its Different Types?
A/B testing is a marketing experiment where you split your audience to test variations on a campaign and determine which performs better. To put it simply, A/B testing involves showing one version (A) of your marketing content to one group of people and a different version (B) to another group.
The primary purpose of A/B testing is to make data-driven decisions by objectively evaluating the impact of changes in your marketing strategies or elements. It helps marketers understand how different variations of their campaigns or assets affect user behavior, engagement, conversions, and overall performance.
A/B testing is a CRO technique, but it comes in a few varieties. To gain deeper insights into your customers, you may consider utilizing one of these A/B testing methods, depending on the specific insights you seek.
- Multivariate Testing:
Multivariate testing allows you to test multiple elements simultaneously within a single experiment. Unlike A/B testing, which focuses on comparing two variations of a single element, multivariate testing examines the interaction and combined impact of multiple variables. This approach is useful when you want to understand how different combinations of elements affect user behavior and performance. By testing various combinations, you can uncover valuable insights and optimize your marketing strategies more comprehensively.
- Sequential Testing:
Sequential testing, also known as adaptive experimentation or sequential hypothesis testing, is a strategy that optimizes the testing process by dynamically allocating traffic or sample size based on real-time results. Instead of waiting until a test is completed to analyze the data, sequential testing allows you to make interim decisions based on accumulating data. This enables you to allocate more resources to the better-performing variation during the testing phase, leading to faster and more efficient experimentation.
- Personalization and Segmenting Testing:
Personalization and segmented testing involve customizing tests based on specific audience segments or individual user characteristics. Rather than treating all users as a homogeneous group, you can tailor your tests to different segments based on demographics, behavior, preferences, or any other relevant criteria. This approach allows you to understand how different variations impact specific segments differently and make targeted optimizations. By delivering personalized experiences, you can enhance user engagement and increase conversions.
How Does A/B Testing Work?
To run an A/B test, you need to create two different versions of one piece of marketing content (landing page, CTA button, etc), with changes to a single variable. Then, you’ll show these two versions of two similarly sized audiences and analyze which one performed better over a specific time period. Two different types of A/B tests you might perform to increase your website’s conversion rates are:
- User Experience Test:
During this test, you may want to see if moving a certain call-to-action button to the top of your landing page instead of keeping it inside the sidebar will improve its CTR. To test this theory, you’d create an alternate landing page that uses the new CTA placement. Subsequently, you would test these two versions by presenting each to a predetermined portion of site visitors. It is important to ensure that the percentage of visitors who see each version is equal.
- Design Test:
In this test, you’d want to find out if changing the color of your CTA button can increase its CTR. To test this split theory, you would create an alternative call-to-action (CTA) button, with different colors, that directs users to the same landing page. For instance, if your marketing content typically features a blue CTA button, but the green variation garners more clicks in the A/B test, it would signify a need to switch the default color of your CTA buttons to green going forward.
For instance, you can use these types of A/B testing to discover how:
- Decreasing the number of form fields in the checkout process increase purchases.
- Your email CTRs increase when you add a video thumbnail to the email body copy.
- Adding testimonials to a product page improves conversions.
What Should You A/B Test?
A/B testing allows you to experiment with and analyze various elements of a page, app, or email. While the possibilities are vast, here are some key areas that are particularly crucial to test and optimize:
- Titles and Headlines
- Landing Pages
- Email Subject Line
- Email Copy
- Page Layout
How to Perform A/B Testing to Fast-Track Your Conversion Rates
A/B testing is not complicated. However, you need to follow a careful strategy to do it correctly. Here’s how you can perform A/B testing to improve your conversion rates.
- Test One Element at a Time:
As you optimize your email copies and landing pages, you’ll find there are many elements you want to test. However, to evaluate the effectiveness, you’ll want to isolate one independent element and measure its performance. Otherwise, you can’t be sure which element was responsible for changes in performance. To finalize an element, look at every variant in your marketing resources and their possible alternatives for wording, design, and layout. Remember, even simple changes like the image in your email or the words in your call-to-action can lead to significant improvements.
- Identify Your Goals:
Clearly define the specific conversion goal you want to achieve through your A/B test. It could be increasing click-through rates, improving sign-ups, boosting purchases, or any other measurable action that aligns with your business objectives.
- Create a Control and a Challenger:
Once you have your independent element, dependent element, and your desired result, you can use this information to set up the unaltered version of whatever you’re testing as your control scenario. From there, you’ll build a challenger (the altered website, landing page, or email). For instance, if you’re wondering if adding an image to an email copy would make a difference in conversions, set up your control page with no image. Then, create your challenger with an image.
- Split Your Sample Groups:
This step is not always required but sometimes you’ll need to watch your audience demographics during a split test. For instance, if you’re split-testing emails, you need to make sure you send the split test to two similar and comparable audiences to have conclusive results. If you send them to a segment of longtime customers and a segment of new leads, the results may be biased due to the significant differences between these two audiences.
- Decide on a Schedule:
A/B tests should have a defined start and end date rather than being conducted indefinitely. Since A/B tests are essentially experiments, it is crucial to establish specific time frames to gather data and analyze the results effectively. To obtain meaningful data, it is important to run your split test for a duration that allows sufficient data collection. Typically, a minimum of two weeks is recommended, although the specific duration may vary depending on factors such as the size of your audience or the volume of web traffic. In some cases, if you have a large audience or high web traffic, it may be possible to conduct the test within a shorter timeframe.
- Analyze and Take Actions Based on Result:
If one variation is statistically better than the other, you have a winner. Finalize your testing process by disabling the underperforming variation in your A/B testing tool. If neither variation yields statistically significant results, it indicates that the tested variable did not significantly impact the outcomes, resulting in an inconclusive test. In such cases, you can choose to retain the original variation or proceed with conducting another test. Utilize the insights gained from the previous test to inform your decision-making for the new iteration. Additionally, you can use the knowledge acquired from each test to enhance your future endeavors.
- Rinse and Repeat the Process:
A/B testing is not something that you do on a one-off basis. It should be a regular part of your marketing team’s CRO strategy. Maintaining the drive for improved conversions in all campaigns is a common goal, which is why it’s crucial not to lose momentum after the initial split test. The key is to consistently repeat the process and build upon it. As you conduct additional tests, you’ll accumulate valuable data and gain deeper insights into your audience’s preferences.
The Bottom Line
A/B test helps businesses understand their customers, improve the digital experience, and stay one step ahead of the industry trends. Remember to define clear goals, test one element at a time, and continuously iterate based on the data collected. With a strategic and data-driven approach to A/B testing, you can drive better conversions and achieve your business objectives.
Want to Unleash the Power of A/B Testing and Experimentation? Let’s Talk!
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