Top A/B Testing Mistakes For Marketers | Data-Dynamix's Tips

Smart marketers are strategic with their budgets and that means testing multiple target groups with various parameters to learn which tactic is most effective with each audience.  We call this A/B testing, as you are testing at least two different groups. Every scenario is different but there are some general guidelines that make A/B testing effective. However, there are some big A/B testing mistakes that marketers can make when testing various scenarios for advertising and we see them all the time.

Here are the top five mistakes we see marketers make when they are doing A/B testing:

  1. Testing too much at one time.  The point of A/B testing is to create a few parameters that you can test to learn valuable intel.  However, if you are testing multiple combinations of multiple parameters, you end up having so many variables that you cannot identify what worked and why.  Think back to science class in middle school when you learned how to create a basic science experiment. You had one variable that you were testing so that you could see if your hypothesis was correct or incorrect.  It’s the same thing with A/B testing. Pick a single variable to test and learn from that data. Then test different parameters on a future A/B advertising campaign.
  2. Basing Campaigns Off of Others’ A/B Campaigns.  You can learn a lot from reading about others’ successes or failures with A/B testing.  However, your business is unique and different from these other brands. You have to run your OWN advertising tests to know what works for YOUR prospective customers.  It’s really the only way to effectively approach comparative digital advertising.
  3. Testing Too Little.  Many marketers give up too soon, or they don’t design campaigns to run long enough to actually gather data.  If you’re going to go to the trouble of designing an A/B campaign plan to run it long enough to gather enough data to conduct thorough, and objective, analysis.
  4. Not Listening To The Data.  Very often we see marketers run A/B tests and get a set of results based on the campaign.  However, the results are the opposite of what they had hoped they’d be. For example, marketers may have learned that their demographic audience is really appealing to Baby Boomers, but they want to be a business for Millennials.  They have an identity crisis and we see many marketers get this information yet continue to pursue Millennials with messages that appeal to Baby Boomers. Stop listening to your own desires and start listening to the data!
  5. Run only one A/B testing campaign.  A/B testing should really be a mindset toward advertising where you are constantly creating campaigns with this perspective.  It should never be seen as a one-time test. Your audience is constantly changing and evolving. By testing various campaigns regularly, you can see changes and trends in your audience and your industry.
  6. Not Using the Right Data. Instead, be smart with the data you use from the beginning. With Deterministix data you can target people with extreme precision using IP address ID numbers to correspond and map to demographic data, mobile device ID data, and other data sets. The power of this combination allows you to get a fine-tuned approach toward your campaign. Ultimately, if you start with better precision, your A/B tests will be that much more effective, helping you eliminate any other guesswork from your campaign. 

As you approach your next digital advertising campaign, we encourage you to bring the A/B testing model into your strategy.  You will gain valuable information about your audience to help you refine your future digital marketing and gain insight into who your audience is.  At Data-Dynamix, our team can help you craft the perfect digital advertising for your business and bring you REAL results!