A/B testing is a crucial component of any business strategy, to ensure your monetization approach is maximizing revenue and growing your business. With AdTiming’s A/B testing tool, you’ll be able to experiment with different ad implementations to conclusively understand how your users engage with ads and choose a winning strategy.
Common Mistakes While A/B Testing
In case of making incorrect conclusions, please pay attention to these common mistakes while A/B Testing.
Testing too many variables together
Testing too many variables together makes it difficult to pinpoint which variable influenced the success or failure of the test most. This means that you can’t set a new network live for Group B while also changing the Traffic Filtering of another network Instance for Group A. You can absolutely test more than one variable, just make sure each gets its own unique test. Please make sure Changes should only be made on Group B (leave your Control Group unaltered).
Testing without enough traffic
A/B testing should be done with the appropriate traffic to get meaningful results. Using lower or higher traffic than required for testing increases the chances of your campaign failing or generating inconclusive results. Performance can fluctuate a lot when only exposed to a small amount of traffic.
Not planning your optimization goal
In A/B testing, your goal (hypothesis) is formulated before conducting a test. All the next steps depend on it: what should be changed, why should it be changed, what the expected outcome is, and so on. If you start with the wrong hypothesis, the probability of the test succeeding decreases. Thus, before starting a test, take some time to think about it and identity your goal.
Testing for incorrect duration
Based on your traffic and goals, run A/B testing for a certain length of time for it to achieve statistical significance. Running a test for too long or too short a time period can result in the test failing or producing useful results. Because one Group appears to be winning within the first few days of starting the test does not mean that you should call it off before time and declare a winner.
Each test should be given a 2-3 day runway for the instances on group B to equalize with group A. We recommend that a test should run for an absolute minimum of one week, with 2 weeks or more being ideal. The duration for which you need to run your test depends on various factors like existing traffic, existing Retention rate, expected improvement and so on.
Failing to follow an iterative process
There’s a joke in the marketing world that A/B testing actually stands for “Always Be Testing.” It’s a good reminder that you can’t get stellar results at one test for Monetization strategies. Keep testing because there’s always room for more optimization!