To maximize the effectiveness of your digital marketing efforts, it’s important to be constantly testing and optimizing your campaigns. Creating different variations before deciding what will benefit your campaign the most is a good way to start, and this is where A/B testing comes into play.
A/B testing is a way for marketers to test different variables and see which is the most effective at accomplishing a goal, such as generating leads and conversions. A/B testing can provide actionable, measurable and (sometimes) immediate results. When it comes to details such as email titles, sometimes the smallest change can make a big difference. We’ll walk through the basics of A/B testing, what to test, what to measure and how to get started.
A/B testing is a pretty simple concept. It involves using two versions of an element and testing each version on a different sample of your audience. This could be something as simple as two different subject lines in an email or two different landing page layouts. One version goes to half of your test audience, the other version goes to the other half. In the end, the version that performs better gets used moving forward. For example, just changing the wording or location of a call to action button could dramatically increase your conversion rate.
Before testing, you need to choose your evaluation criterion to ensure you are not swayed by the results later. Focus on one key performance indicator (KPI), write a hypothesis, and determine a specific audience to target. Choose a schedule, so that you aren’t tempted to look at data too early or make conclusions before there is significant information. You can gather data using a multitude of tools, but the most common ways are using website analytics through Google Analytics, heatmap technology, and email tracking systems. These tools will provide you with information about where users are spending time, where leads are being converted, and which features are working.
Once you have a plan, stay patient; don’t get excited and jump to conclusions before the test runs its course or if a different metric than what you’re measuring shows significant change. If your goal is to increase the time spent on your page, but instead, one option ends with a marginally higher click rate, be cautious when deeming this option the winner. Making a goal and sticking to it will produce the best results.
A/B testing is most effective when you keep it simple and only change and test one variable. Only one element should be different between your two samples. For example, if you are sending an email and want to test the subject line, make sure the body and design of the email is exactly the same in both emails. Don’t change the subject line AND the length of the email because it is harder to see what made the real difference in your goal KPI (open rates or conversions, for example). And you should only run one A/B test on a single campaign at a time, so as to reduce confusion and doubt about what worked from the final results.
Make sure to also test both versions at the same time; traffic and engagement can be very different depending on the day of the week or time of the year. This eliminates external factors such as holidays or workweek cycles. You also need to be mindful of how long your tests run. The time required for a reliable A/B test can vary depending on what you are trying to accomplish, while also factoring in your current traffic and conversion rates. Many experts believe most A/B tests should run for two weeks, with a minimum testing time of seven days. This will increase the likelihood that the data you have gathered is statistically significant.
When is the right time to begin A/B testing your campaign? While A/B testing can be extremely insightful, it’s most effective if you already have a steady flow of traffic. If you have low traffic volume or open rates, there is a high possibility that you will not have statistically significant results, or the small tweaks you make will be less measurable. The more users that are testing, the more accurate your results will be.
A/B testing can be used to test a variety of elements in your marketing program. Here are some different ways it can be utilized:
Specific data points you analyze will depend on the medium you are A/B testing. For example, you might want to track the time on page when testing a new landing page. If version A has a higher average time on page, it would suggest users are more engaged with that version; when paired with a higher conversion rate, this would indicate that version A is better than version B. Data will remove the uncertainty of not knowing where leads are falling off and will point out elements that have the biggest impact on conversion rate.
Also, be aware that not all tests will have a statistically significant result. This did not mean that you failed; it just means it doesn’t make a big difference. Find another aspect that can be tested and test again. One last thing to remember: don’t trust your gut—trust the results! Your personal preference might not be the best approach to take, which is where the science of A/B testing is so helpful.
What one test determines to be most effective may not be the case down the road, so A/B testing should become an ongoing process for your campaign. Each time you test, you take any knowledge you gain and try to apply that in the future. As you write more content, create more landing pages or make changes to your website, A/B testing can help you see what is working so you can improve your marketing efforts.
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