Why You Want to A/B Test Your Marketing (and How to Do It)

There are a lot of decisions to make in any marketing effort you put out, many of which could be the difference between success and failure. Even more common, however, are the decisions where the difference is between success and great success. Obviously, the latter option would be preferable…so how can you identify the right path?

Simple… by utilizing something called A/B testing. Let’s discuss what it is and, more importantly, how to do it.

Question: What is A/B Testing?

Answer: A method of comparing two approaches to determine which results in a better outcome, focusing on a single variable.

Which call-to-action inspired the most prospects? Which blog title attracts the most attention on your website? Which image on your social media ad resulted in more click-throughs? Which font generated more responses to your postcard?

Using the A/B testing process, you can evaluate and improve any design or content choice in any aspect of your marketing. Your options can almost be turned into a tournament-style bracket to find the supreme approach for you to take.

As you might imagine, this process presents many benefits to the business that uses it. Not only are you minimizing your risk by adjusting just one detail at a time, but you’re also actively working to make every detail of your marketing work toward your ratio of conversions to visitors.

What Else Does A/B Testing Allow Me to Do?

Answer: Quite a few things, from connecting with your audience and their priorities better to staying in step with current market preferences.

While the primary goal of A/B testing is to maximize your conversion rate, it also offers other benefits that can give your business an advantage. For instance, it can give you valuable insight and understanding into what your audience is looking for and who they are.

With that knowledge, you can direct your future marketing efforts even more precisely… and as a result, craft content that more directly addresses their needs as they evolve. This helps you both stay abreast of your industry and its trends while also helping reduce your bounce rates. After all, if you provide what your audience is looking for, they’re apt to stick around.

So… How Does One Run an A/B Test?

This is where you get to be a scientist, as an A/B test largely follows the scientific method of running an experiment. It begins by identifying the problem or issue you want to resolve, even if it’s just a desire to improve upon what’s already been established. Take any information and data you already have into consideration to identify the root issue and come up with a proposed solution to it.

This solution will inform your hypothesis—the assumption that your A/B test will either confirm or deny.

Then, you need to create a second version of whatever you’re testing, the only difference from the original being that the second version reflects your hypothesis. Then, present them both to your audience, observing how each performs. Ensure you’ve established a timeframe so your experiment has a set endpoint, and let your test run its course.

Gather your data, and consider your results once the test is completed. Which option performed better? Was there any notable difference? Make the changes (if any) that your test indicated would help and—crucially—repeat the process with a fresh hypothesis.

So, the cycle can effectively be summed up as follows:

1. Select the problem/issue to address
2. Examine your existing data
3. Establish a hypothesis
4. Test your hypothesis
5. Consider your data
6. Implement your changes
7. Repeat the process

What (and What Not) to Do for a Successful A/B Test 

DO: Limit each test to a single variable.
If you pack an experiment with more than one variable, it becomes significantly more difficult—if not impossible—to determine which variable was responsible for any changes you see. Maybe adjusting an email’s copy and format killed the conversion rate… the thing is, you need to know which one was responsible. You can confidently associate your results with that specific change by testing one variable at a time.

DON’T: Cut your tests short.
Generally speaking, the more samples you have to work with (in the context of A/B tests, at least), the better or more accurate your results will be. You could create inaccuracies if you don’t give your test enough time to collect sufficient data. 

Of course, the proper amount of time to run these tests depends on what you’re testing. Minor changes (like an edited subject line or change in a postcard’s image) take less time, while larger ones (like website edits) take longer to generate enough data.

DO: Consider how your data may be skewed.
Speaking of inaccuracies, it’s also important to remember all the external factors that could potentially influence your test. Depending on the industry, everything from the time of day to regulatory adjustments to the economy could artificially tip the scale. Again, running tests for enough time can help you collect more data to help minimize these errors.

DON’T: Assume one test will tell you everything.
You should repeat your tests without any changes as often as you possibly can to help narrow down your results and confirm their accuracy as well. Repeating the process will help you catch any errors that may have led to a false positive.

Interested in Running Some A/B Tests? We Can Help with That

Reach out to us for assistance with any questions you have about your marketing needs. We specialize in providing comprehensive marketing solutions and services for managed service providers worldwide.