What do you do if a variation you thought would rock ends up flopping? Or what if your test results are inconclusive? Don’t throw in the towel just yet! There’s a ton you can do with inconclusive or losing A/B testing data. We’ll cover how to put that information to good use.
Why A/B Testing Is Crucial to Digital Marketing Success
Helps marketers understand the impact of optimization methods
- Provides hard data to back up your optimization techniques
- Allows marketers to make better business decisions because they aren’t guessing at what drives ROI
- They’re making decisions based on how specific changes impact traffic, sales, and ROI
Try Something Really Different
Inconclusive test results could mean your variations are too close
- Consider it an opportunity to try something totally different
- For example, change the page layout, add a different image or take one away, or completely revamp your ad, asset, or CTA
Look Beyond Your Core Metrics
You might have hidden data in your losing test results
- Use that information to improve the buying process
- For example, if you run two variations of an ad. If one variation drives massive traffic, and 30 percent of visitors from that variation convert, this could mean more revenue
A/B testing
Shows different visitors different versions of the same online asset, such as an ad, social media post, website banner, hero image, landing page, or CTA button. The goal is to better understand which version results in more conversions, ROI, sales, or other metrics important to your business.
How Do I Know If I Have a Losing or Inconclusive A/B Test?
You’ll see the results in your own data dashboard or in the testing tool you use
- When your tests don’t have enough data or if the numbers are too close, they are considered inconclusive or statistically insignificant
Are A/B tests better than multivariate tests?
One is not better than the other, but they are used for different purposes
6 Ways to Leverage Data From Losing or Inconclusive A/B Testing
Don’t assume your test failed. There are plenty of steps you can take to leverage that data
- The variation you expected to win performs worse!
- Or you find the variations don’t actually impact the metrics you are tracking at all.
Run Your A/B Tests Again
The goal is to continuously improve your site’s performance, performance, ads, or content
- Once you’ve completed one test and determined a winner or no winner, test again.
- Avoid testing multiple changes simultaneously. Instead, run changes one at a time.
What are the best A/B testing tools?
There are a wide range of testing tools that can be used to test different aspects of your business
Conclusion
Make the most of Losing or Inconclusive A/B Testing
Analyze Different Traffic Segments
Try segmenting the audience to see if different people responded differently
- For example, you might compare data for: new versus returning customers buyers versus prospects, specific pages visited devices used demographic variations, locations or languages
- You might find specific segments of your audience respond better to certain formats, colors, or wording
Remove Junk Data
Sometimes tests are inconclusive not because your variations were terrible or your testing was flawed, but because there’s a bunch of junk data skewing your results.
- Get rid of bot traffic, remove any from your company IP address, and delete competitor traffic if possible.
Look for Biases and Get Rid of Them
Biases are external factors impacting the results of your test.
- Try rerunning the test to separate the positive and negative bias impacts, and take a look at how the test was run to see how you could optimize for each outcome.
