While optimizing the on-screen metadata factors of the app like an icon, screenshots, title, and description are the first steps of app store optimizing services. Understanding what works with the user and what he finds more useful in every update, makes is crucial for every good app developer working hard to increase its efficiency.
So, when it comes to an understanding the app’s performance, A/B testing is a lifesaver. The field of A/B testing is an effective technique used by every digital marketer in the field, helping them make continuous assumptions and improvements based on the trends and user needs.
What is A/B testing?
A/B testing or split testing is a method of hypothesis checking that compares two versions of app store variable and understanding, which performs better in terms of giving app more visibility and drive more potential downloads.
Once you decide to perform A/B testing for a factor, say screenshot it needs to go through a series of events. The essential elements of A/B testing are:
- Analyzing and brainstorming the ideas before testing.
Without thorough research, jumping into A/B testing is a mere waste of time. Instead, you need first to understand what idea you’re testing for?
For example, if you’re testing factor is a screenshot. Instead of the question “what gives me more downloads in screenshots,” come up with an idea like “does orientation of the screenshots effect the download rate” or “do screenshots that are primarily white convert more than blue.”
OfCourse you need experience and good knowledge of what is going on in the market before coming up with a good idea. So good research, along with understanding competitor’s app, help you get a good idea.
- Creating the variations for the test:
Once the hypothesis test is done, you have to come up with the creations of what you are testing for. For example, if you are testing on having a screenshot with solid background colors or more designed creative screenshots. It would be best if you created both of them before doing A/B testing.
- Running A/B experiments:
After creating the variations for the tool, you need to do the experiments. For this, top ASO companies use a lot of tools like google play experiments, split metrics, etc.
No matter what tool you use, it has a set of rules that it needs to follow. Most importantly, it should have the same traffic rate on each side.
- Evaluating the test results:
This is the most interesting part of the process, where the aso team gets the results of their hypothesis. Although there is no win or lose, you will find out which hypothesis is better performing.
- Results implementations:
This step includes two steps:
- Implementing the winning screenshots immediately to your app store straightway
- Doing further a/b testing for better conversion rate optimization.
Better the testing, better performance of the app.
ASO is an ever-changing process.
The truth about top category apps is they never stop optimizing their app and always update the elements that affect conversion rates. This is the strategy used by most of the top app store optimization services while working as determine the factors that bring a change of conversion for better efficiency and performance.