Using iTunes App Analytics To Understand How Effective Is Your ASO

Congratulations! You are about to publish your app. The development, the testing, and your app is now ready to be launched. Before you enter the highly competitive mobile app market, you need to know that over 2,500 apps are submitted to the three biggest app stores on a daily basis, and 70% of these apps generate less than 5,000 downloads each.
When it comes to PC World, we couldn’t update a game or an app right after its release, nor could we collect information on how it was being used. Whereas in the Mobile World, we’re able to rethink our app again and again, and steadily improve its performance whilst maximizing user experience based on observations we make about our app’s usage. This is where data analysis comes into play. It helps you to reach win-win relationships with your users and is a great source to learn, analyze, and understand the real value users get from your app or game.

WHY Do I Need To Analyze Data?

Understanding your users’ need and knowing what they like and don’t like about your app are the key factors to your success. Let’s say your acquisition campaigns are only effective when you take the time to find out who your users are, their interests, at what time they’re most responsive. Then, you need to set the right targeting for your campaign if you want to improve your “ASO” App Store Optimization strategy. You need to analyze your app’s data to help you understand what app description, keywords, and screenshots would appeal to your users.
You can’t get far without these data – from helping choose your beta testers, to showing you how to optimize your app’s screen which has high churn rates. Data can help you develop the best user experience, and guide you in optimizing your marketing strategy.
In fact, your app’s value relies on the data it offers. Data optimization processes are your key to success. And with the rollout of the Apple’s app analytics module in iTunes Connect, you can see the kind of data you need to make efficient steps toward even more efficient ASO. With this in mind, I thought it useful to quickly run through a few stuff that might not be apparent to users coming to it for the first time.
What Is iTunes App Analytics?
The iTunes app analytics is a module that comes with a collection of data relevant to developers and marketers of apps. It provides an up-to-date, first-party data that you can use and modify without requiring any changes to your app. The analytics module can be found in the iTunes Connect landing page and is only available to admin, finance, or sales users.

What Data Does It Give You?

That data offered by this module is divided into four: overview, metrics, sources and retention.
As its name suggests, it’s the unfiltered data that gives you almost all the information in the other modules at a glance.

  • App Store Views
  • App Units
  • In-App Purchases
  • Sales
  • Installations
  • Sessions
  • Active Devices
  • Active last 30 Days
  • Along with a comparison drop down menu so you can compare any of the abovementioned metrics side-by-side.

Provides sources and figures of the users coming to your app. Pretty self-explanatory eh?
A 30-day retention chart, showing retention by day.

WHAT Data Should I Look I For?

With all the information provided to you by the iTunes App Analytics, you’ll get lost if you try to analyze it all at once. So, begin with the basics until you know these parameters, you can define possible behavior patterns. It’s also important to be aware of the life-cycle stage of your users (new|dormant |engaged the user, the risk of churn, etc.) – So use and analyze your data accordingly.
The most useful element of the iTunes App Analytics module in terms of ASO is within the metrics tab. As I have mentioned earlier, it gives you App Store Views, App Units, In-App Purchases, Sales, Installations, Sessions, Active Devices, Active last 30 Days and a comparison drop down menu. With all these information, we can now see the link between App Store Views and App Units. Comparing these two values will give you a very basic conversion rate (bear in mind that data comes with caveats). Obviously, one of the biggest issues here is how you would be able to identify a low conversion rate, given the fact that you don’t have access to a global average, but it may be worth looking for more answers online and other mobile analytics and making a few best guesses relevant to your field.
Conversion rates vary across categories, but with some tweaking over time should yield results that are now measurable, albeit not in A/B format. Let’s say you’re running at a very low conversion rate, improving your app’s metadata, title, and having a closer look at your keywords to ensure they are highly relevant, is the sensible next step.

WHEN To Use Data?

Data analysis is a critical component to consider when defining your ASO strategy, not a last minute consideration.
“Deciding which data points to gather, collect, analyze and profile with, is a critical process which app developers should be aware of. The best way to approach this is to discuss this with your advertising and analytics partners in advance, to be sure that all possible data points are well covered by in-app event tags integrated into your app.” – Freddy Friedman, glispa CPO
Whether you are an app publisher or an ASO practitioner, data is your helping hand. You can make use of all the data points available in your app and launch more successful ASO campaigns with precise targeting and more relevant users, eCPMs, download increases, and more IDFAs (Identifier for Advertising). In the long run, proper data analysis will contribute to your app’s success, as well as a higher company valuation.

So, What’s next?

We can say that most if not all app developers have already realized the real power of data as a key driver in ASO: from conceptualizing your app, to trials with beta users, to driving downloads & installs with the right target audience, and to driving engagement and retargeting of dormant users.
Before you start analyzing your data, remember to focus on the rapidly changing mobile ecosystem and make sure that you are on the cutting edge of technology. Don’t just follow the norms – go beyond traditional patterns and develop your own strategy for getting and analyzing the data that you need. Do not hide what you are after, think outside the box, define your goals, and for sure you’ll definitely succeed!

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