It’s a common term in the world of marketing, but, as routine and ubiquitous as it may be, A/B testing is not easily done right. As with all marketing follies, the wrong approach can waste time and money and lead your content down the wrong path. Fortunately, by following a few simple guidelines, you can start using A/B testing to get results you can apply to your strategy to drive conversions.
Marketers make it their business to know their audience, so chances are you know yours pretty well. However, when it comes to A/B testing, relying too heavily on what you think you know (based on the personas you’ve worked so hard to build) may hinder your results. Starting with a clean slate will help you define what you want to learn about your audience and give you the data you need to optimize your digital strategy.
The most effective experiments are based on solid hypotheses. You can’t go into an experiment without first outlining what you hope to learn from it. These hypotheses shouldn’t be defined by hunches or various “expert” theories floating around in white papers and blog posts. They should be tailored to your industry and your goals. Look at your current approach and data you already have. Determine what aspects of your approach you can change and explain how you think those change may impact the data and, ultimately, your audience’s behavior.
Part of having a solid hypothesis is filtering out the smaller details that will likely have no real impact on how you approach your content. Most of this is common sense. You don’t need to test 17 variations of a font or 13 configurations of a graph. Try testing a video against a still image. Headlines that focus on features versus benefits. Change up the design. Rework calls to action. All of these things can give you unique insights into what matters to your audience.
On the flip side, you want to be able to determine what is actually making the difference within your tests. This can be nearly impossible to deduce if you change everything all at once. Pick one variable to test within each run, so that in the end, you’ll have precise data points tied to each variation. This will allow you to determine what changes had the biggest impact on your conversions.
The possibilities of A/B testing are virtually endless. A fact that can quickly become problematic. Even the most expertly designed A/B tests can be rendered useless if the testing never stops. The entire point of these tests is to gather data you can act on. Data you can translate into meaningful change in your strategy. Data you can ultimately turn into conversions. Once you have reached reasonable conclusions for each of your hypotheses, put those conclusions to work.
The digital world has given us access to a goldmine of data, but as marketers, we can’t get too consumed with that data. It can be a great tool to support your strategy, but you don’t want to lose sight of the individuals behind those numbers. The goal is to communicate and deliver a genuine benefit to your customers, not to manipulate them into becoming conversions. So, keep the individual in mind as you analyze your data and use the numbers to inform and shape your approach.
These guidelines merely scratch the surface of A/B testing, but they can help you get on the right track. The more you test and the more insight you gain, the better you’ll become at refining your content to reach your audience and optimize your conversion rates.
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