Are your marketing campaigns performing as well as they could be? Whether a campaign isn’t meeting expectations or is providing satisfactory results, there’s always the potential to improve it. The challenge, though, is figuring out which tweaks will boost performance. The only way to know for sure is to test them. That’s where A/B testing comes in.
What Is A/B Testing in Marketing?
Before we get into how to use A/B testing, let’s define it. A/B testing, also called split testing or bucket testing, is a method for testing which version of an ad, landing page or any other element of a marketing campaign performs better. To conduct an A/B test, you change one aspect of your campaign and run both variants, collecting data on performance. You can then implement the change that got the better results.
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For example, you might write two different phrases for your call-to-action (CTA) button on a landing page. You would then run both these versions at the same time and collect data about which led to more conversions. You can use this same process to test an ad, social media post, email or any other element of a campaign, as well as to refine different aspects of that same landing page.
When Can You Use A/B Testing?
A/B testing can be valuable anytime tweaking an element of an online property or ad could improve performance and help you achieve the campaign’s goal. As mentioned earlier, you can’t know for sure if a change will improve your campaign’s performance until you test it. You may be able to use general best practices to get you started, especially for broader strategies. When it comes to the details, though, you need to test different ideas to determine what will work best for you.
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That’s why split testing is important. It allows you to test your actual campaigns with your real audience and gives you data to back up the decisions you make. Optimizing your marketing in this way can help you meet your campaign goals, whether you’re looking to boost sales on an e-commerce site, increase engagement on your social media channels or achieve some other objective.
You can test these elements at any point during your campaign. A/B testing can be useful at the start of an initiative, but you should also use it to fine-tune your strategy as you go. The more testing you do, the more you can refine your campaign. Over time, you can improve your campaign’s performance drastically. You should also periodically come back and re-test elements, since what works best can change over time.
A variety of media types might play a role in achieving these objectives. Some of these channels include:
- Marketing emails
- Banner ads
- Social media posts
- Website pages
- Mobile advertising
- Marketing campaign strategies
Choosing Campaign Elements to Test in A/B Testing
You can use A/B testing to evaluate the effectiveness of any element that may influence customer behavior or impact conversion rates. Some examples of items to test are:
- CTA text
- CTA button
- Email subject lines
- Product descriptions
- Ad copy
- Color scheme
- Free trial lengths
- Pricing structures
With so many options, how do you decide which elements to test? To get the maximum benefit from your testing, it’s best to have a structured method for choosing what to assess. In a recent survey by Econsultancy and RedEye, 74 percent of respondents who used a structured approach to conversion increased their sales.
First, you’ll want to conduct some research. Look at your data from past campaigns to get an idea of what you might want to improve. Use web analytics and mouse tracking analysis to find out how visitors use your site. If you’re considering A/B testing email marketing, look at data such as open rates, click-through rates and conversions. You can also use qualitative research such as surveys and interviews to get people’s opinions on your site, emails or whatever you’re considering testing. Finally, don’t forget to compare elements of your campaigns to known best practices. This research should provide you with a list of factors to test.
Next, you need to choose which elements to test first. Prioritize them based on how much value a potential improvement could provide. You can estimate their value using research methods such as those listed above. Also, evaluate how difficult it would be to make the necessary adjustments and consider aspects such as how long it would take, how complex making the change is and any risks involved.
Finally, test the elements in the order in which you prioritized them. You can assess every component of a campaign if you want, but make sure you only run one test at a time. That way, you know for sure which element led to the improved or worsened performance you find through your testing.
How to Do A/B Testing for Marketing Campaigns
So, how do you run A/B tests for your marketing campaigns? Here’s a basic process you can follow.
- Determine which campaign elements you want to test: First, you need to decide what to test. Look for landing pages, ads or other aspects that are underperforming, or evaluate past campaigns. Then, use web analytics and other research tools to develop a hypothesis for why it is not performing well. You might be wondering, for example, whether your CTA button is too small. Rank the elements you’re considering testing, and start with the top-priority item.
- Create two variations of that element: Once you decide what you want to test, choose or create the two variants. For example, you might design two versions of a banner ad — one with an image and one without. Alternatively, you can test a new version of an element against an existing one. For instance, you could leave one landing page as-is and compare it with the same page, but with a larger CTA button.
- Establish a plan for measuring your results: Make sure you have a strategy in place for tracking the metrics of your campaigns. Know what indicators you’re measuring, whether that’s more sales, more newsletter signups, more comments on your Facebook posts or something else. Also, define how big of a change would be statistically significant. If you’re testing something for an existing campaign element, you can use its current performance as a baseline.
- Set a timeline for your test: Determine how long you will run the test. Make sure your testing period isn’t too short or too long, as this can lead to inaccurate results.
- Run the test: Now, it’s time to run the test. Make sure you test one element at a time, so you know which element influenced the results. To avoid factors that may skew the results, run the two variations simultaneously and try to keep the groups seeing each version similar in size, demographics and other variables. If running a large test on a website page, you may randomly split your visitors between the two variations. If testing a marketing email, you can create two test groups of customers with similar or identical demographics.
- Check your results and implement changes: Once your test has run for the predetermined amount of time, you’ll have your results. If your test didn’t produce conclusive results, adjust your hypothesis and run another one. If a clear winner did emerge, implement the variation that performed better. Feed the data from your analysis into your data management platform to help you improve your current and future campaigns.
- Repeat the process: You can use A/B testing over and over to continue to refine your marketing campaigns for even better performance. After your first test, run another with the next element on your prioritized list. This element can be part of the same item you just tested, or part of another one. You should also repeat A/B testing as trends and customer preferences change over time.
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Implementing A/B Testing Results to Maximize Campaign Performance
The way in which you run your tests is crucial for getting accurate results, but what you do once you have your results is essential, too. You should implement the best-performing variant, but there are also other ways you can use your results to improve campaign performance. Here are a few tips for using your A/B test results.
- Implement results across your site: Once you’ve applied what you’ve learned to the web page, email or ad you tested, try using it on other similar elements, too. If a red CTA button works better on one landing page, for example, it might also work better on another. You can even test these other pages to verify your results. One split test can lead to improved performance across your entire site or marketing campaign.
- Track differences between audience segments: You can also drill down further into your test results to get even better insights. One of the best ways to do this is by looking at your results across various audience segments. There’s a huge range of segments you can look at. You can split audiences based on the kinds of devices they’re using to access your site, whether they’re new or returning visitors and whether they came to your page directly or through an internal link. You can also look at demographic data such as age, location, gender and income level, as well as data about interests, beliefs and preferences.
- Use different elements across segments: Use what your tests teach you about your audience segments to create campaigns tailored to different kinds of customers. For instance, you might find a page with large graphics works better for users on smartphones, while a bit more text works best for those on desktops. You can then create two variations of your page for both audiences.
- Use results to inform future tests: Using the results of each test to perform future tests can help you work more efficiently and get better results. If you find your customers like videos, for example, you can try testing more videos in the future.
- Combine the results of tests: You can also analyze different elements of pages you’ve already run tests on to refine them further. If you first tested the subject line of an email, for example, next test the copy in the body of the email. The more you test, the more data you have. Combining the results of your tests can help you further improve your campaigns.
- Archive your test results: Once you finish each test, make sure you archive the results in an organized way. Using a DMP can help with this. Saving this test data allows your knowledge to grow over time, helping you improve your marketing campaigns over the long term.
Benefits of A/B Testing in Marketing
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Marketers can derive tremendous benefits from using A/B testing. Here are some of the main advantages it provides.
- Increased certainty about strategy: With A/B testing, you no longer have to guess what will resonate with your audience. It provides you with firsthand data about your campaigns and your audiences, which you can use to drive your marketing strategy. Backing up your marketing decisions with data will likely help increase buy-in from management and other departments within your company.
- Improved campaign performance and progress toward goals: A/B testing allows you to continuously improve your campaigns’ performance and helps you make progress toward your campaign goals. Tests of different elements can help with different objectives. Some common goals include boosting conversion rates, increasing web traffic, reducing bounce rates and increasing engagement with content. Implementing the results of your A/B tests can also contribute to reaching broader business goals, such as increasing overall sales.
- Improved ROI: A/B testing helps improve the ROI of your campaigns and overall marketing activities, ultimately boosting your company’s bottom line. Refining your campaigns using A/B testing makes them more effective. Thanks to today’s digital technologies, split testing is also inexpensive. Improving the performance of your existing campaigns and reducing ad waste through A/B testing is much more cost-effective than increasing the reach of your campaigns. It helps you make the most of the traffic you already have, rather than paying for more.
How Lotame Can Help
The Lotame DMP can help you conduct A/B testing to improve your campaigns’ performance. You can use the DMP’s audience-splitting features to create groups for your tests, then deliver your campaign to these groups. Next, feed your results back into your DMP to help inform future marketing and testing decisions. Lotame has partnered with Optimizely, allowing Lotame clients to integrate audience data segments from their DMP with Optimizely’s A/B and multivariate testing platform.
Whatever your campaign goals are, Lotame’s DMP and other tools can help you achieve them. To learn more about how Lotame can help you maximize campaign performance and better reach your target audience, contact us today.