Boosting Results with A/B Testing

Looking to increase the opens of your upcoming email campaigns, boost views on your new company video, or improve the quality of inbound leads to your website? A/B testing just might be the solution you need.

A/B testing is a process of experimentation between two variant elements (element A and element B) which, when served at random to an evenly split audience, can be statistically analyzed to identify which element performs best for their stated goal. In marketing, A/B testing is a tool that isn’t often leveraged due to a limited availability of a company’s marketing resources, but can help to drastically improve the results of a variety of marketing initiatives.

Successful A/B testing requires planning and process – both of which are necessary to ensure you are testing the right elements for your marketing goals and are able to draw actionable conclusions from a test’s results. To help kickstart your A/B testing, we’ve provided the following framework. So, without further ado, here are the ABCs of successful A/B testing:

Determine Key Performance Metrics
A successful plan starts with a vision of success – the more specific, the better. Use your marketing goals as a launching point to determine if you’re satisfied with the current level of performance across your marketing channels. For example, if you spend a lot of money on digital advertising but aren’t getting enough inbound leads to justify the cost, that may be a good place to dive in deeper to try to understand the underlying causes. From here, look into your key performance indicators for your campaign or channel and compare them against industry benchmarks to better gauge their overall performance. To continue with the digital marketing example, is it that the ads are not being served to enough people (low impressions) to serve your marketing goals or is it that the click-through rates are below industry averages? Whatever the cause, garnering a wholistic understanding of the health of your marketing channels will provide you with the cornerstone for your A/B test: the key performance metric you can mark for improvement. It’s important to focus in on one metric at a time, as subsequent tests can always be run to improve other performance metrics. For those looking to take a more proactive approach, you can apply A/B testing to any newly initialized marketing efforts to help clear the uncertainty between any two elements (i.e. subject lines, send times, page length, etc.).

Isolate Your Testing Variable
Once you’ve identified the key performance metric for your A/B test, it’s time to think through ways to improve it. Once again, specificity is the key here, as the more targeted you can get with your suggested changes, the more accurate your testing results will be.
For example, if the goal was to increase the downloads of a new whitepaper on the website, there are many variables that we could tweak to potentially affect the number of downloads, such as the website’s page structure, the thumbnail provided, whether or not an excerpt is included, of even the name of the whitepaper.

The importance of these variables can often change from audience to audience, so it’s important to see the problem from your audience’s perspective. Doing so will help you pinpoint which variable might have the most impact on your marketing goal, thus identifying your testing variable. Depending on the testing variable you have chosen, determine the timeline needed for the test to produce insightful results (we recommend a minimum of 3 weeks, marketing channel dependent).

Utilize a Control Group
If you’ve ever done a science fair experiment as a kid, you should understand the importance of a control group in experimentation. A control group is the testing element which is to be used as-is, without any changes or variation.

To return to our whitepaper example, the control group (element A) would be the page that currently holds a downloadable whitepaper on the website. On the other hand, our variant group (element B) would be a copy of that page but with whatever change we identified from our previous step (updated page structure, thumbnail, etc.). The importance of a control group cannot be understated, as without one there is no way to make a final comparison between the two elements in your A/B test.

Launch and Monitor
Finally, the moment as arrived when all of your planning has come to fruition. The launch of your A/B test will be reliant on your ability to randomly and evenly split your audience between your variant and control groups. Many marketing automation, email marketing, and advertising programs are increasingly providing the ability to A/B test directly in-platform, reducing the manual effort required to run these tests on a regular basis.

Once launched, continuously monitor its results to ensure the tests are running smoothly. Keep a close eye on your key testing metric and keep track of it on a regular basis. Whether that’s daily, weekly, or monthly is subject to the nature of your tests.

Analyze and Improve
Congratulations, you’ve successfully planned, prepared, operated, and completed your A/B test! But not so fast, you’re not finished yet – the final step of A/B testing is to analyze the results and select your winner. Look back at your tracking document and use it to draw statistical comparisons between your variant and control groups as they relate to the key performance metric you have identified. Once you’ve taken a look and settled which group was more successful, keep track of that conclusion and use it continually improve your marketing efforts moving forward.

A/B testing can provide unexpected insights that drastically improve your campaign results, especially for ongoing marketing activities. Happy testing!