Apple App Analytics 101 (updated) Understand App Analytics and use it the right way

App Analytics Dashboard

Understand App Analytics and use it the right way

We updated this post to reflect the latest changes and additions to sources and more, so it’s still up-to-date!

We’ve all been there: You just finished your app, uploaded it to App Store Connect, maybe even got it through review. Now comes the moment of truth: will people actually download your app? It’s not a secret that the App Store is a crowded place. There’re more than 2.2 million apps on the App Store and there’re added more than 1000 new apps per day.

So the big challenge is not only to craft a high-quality app, but also to gain visibility, get people to download and use it. That’s why you should spend a significant amount of time to do PR, create a launch strategy and tie it all together with a marketing plan.

A big part of your launch strategy/marketing plan should be App Store Optimisation (ASO), as it will have a direct impact on your app’s ranking and visibility in search (mainly through keywords and app title). But ASO also tackles the conversion rate mainly with screenshots, app preview/trailer and description, but also the “management” of ratings and reviews.

That’s especially the part where Apple’s App Analytics can help you tremendously, because it sheds some light on previously “unknown” territory. In this introduction we’ll have a look on what App Analytics actually is, why you should use it and how you can get the most value out of it.

What is App Analytics? Covering the basics

App Analytics is Apple’s very own analytics platform. It lives right inside of App Store Connect. Announced at the WWDC in summer 2014, it launched finally in spring 2015 and just recently added new metrics on the discovery of your apps.

One might say just “another” analytics platform like free solutions from Flurry/Yahoo MobileGoogle or Facebook, but App Analytics finally provides reliable data nobody else can (Spoiler: App Store impressions, referring websites, attribution)

App Analytics as part of App Store Connect

Before you get too excited here’re a couple of small caveats:

  • All data shown is from devices running iOS 8 and tvOS 9 and later only; on average you’re missing out 5% of iOS users
  • Apple has three different metric types: “App Store”, “Usage” and “Sales”. Customers can opt-out of app usage data, but not out of sales and store data
  • Reporting can be delayed up to 72 hours

App Analytics consists of four parts:

  1. Overview, which is your App Analytics “Dashboard” and gives you a quick overview
  2. Metrics, the core of App Analytics, where you can deep-dive into the data
  3. Sources, shows you the top referring apps, websites (only via Safari) and custom campaign links
  4. Retention, cohort analysis (opt-in only)
App Analytics Overview Dashboard


Let’s have a closer look at the core of App Analytics, metrics. There have been quite a few misunderstandings and discussions around the definitions of the different metrics. I’m trying to define and explain them as simple as possible based on Apple’s various docs.

App Store (aka Apple’s blackbox data)

  • Impressions
    The number of times your app was viewed in the Featured, Categories, Top Charts, and Search sections of the App Store. This also includes view of the Product Page. Basically all impressions of your app within (!) the App Store app.
  • Product Page Views (previously “App Store Views” in the Sales section)
    The number of times your app’s product page has been viewed on devices using iOS 8 and tvOS 9 or later. This includes data from the App Store app (obviously), but also from the StoreKit API (i.e. within apps).

Sales (aka all data)

  • App Units
    The number of first-time app purchases made on the App Store using iOS 8 and tvOS 9 or later. Updates, re-downloads, download onto other devices are not counted. Family Sharing downloads are included for free apps, but not for paid apps.
  • In-App Purchases
    The number of first-time purchases of an In-App Purchase on a device using iOS 8 and tvOS 9 or later. Restored In-App Purchases are not counted.
  • Sales
    The total amount billed to customers for purchasing apps, app bundles, and In-App Purchases. Taxes are only included in the sales if those taxes were included in the App Store price. (Sales totals are not the same as proceeds; sales include Apple’s 30% cut)
  • Paying Users
    The number of unique users that paid for an app or an In-App Purchase.

Usage (aka user opt-in data)

  • Installations
    The total number of times your app has been installed on an iOS device with iOS 8 and tvOS 9 or later. Re-downloads on the same device, downloads to multiple devices sharing the same Apple ID, and Family Sharing installations are included. (Updates not included)
  • Sessions
    The number of times the app has been used for at least two seconds. If the app is in the background and is later used again, that counts as another session.
  • Active Devices
    The number of devices with at least one session during the selected period. Only devices with iOS 8 and tvOS 9 or later are included
  • Active Last 30 Days
    The number of active devices with at least one session during the previous 30 days.
  • Crashes
    The total number of crashes.

The biggest issue is the “Opt-in Rate” for usage metrics. You can find the opt-in rate based on the users’ of your app from the last 30 days directly in App Analytics by clicking on the little question mark next to “About App Analytics Data” in the metrics section.

Just recently Apple started sharing aggregated and averaged data on the Opt-In rate, which can be seen on the screenshot below. As you can see it’s consistently hovering around 25%. After more than one two years of comparing the data across various apps, we’ve seen this rate being consistently around 25-30%.



Sources are a great way to track the marketing attribution of your apps via (other) apps, websites, campaigns and the App Store itself. Sources can help you answering questions like “Do people actually search on Google for my app?” or “How many people buy the app via my landing page?”  or “How many people are coming via Store search vs. browsing it?”

  • All
    This shows you a rough overview of the different sources from which a customer tapped a link to your app’s product page to view or download it for the first time.
  • App Referrers
    People coming via links from within other apps. This also includes apps using the StoreKit API and excludes the native Safari.
App Referrers — Source: David Barnard
  • Web Referrers (previously Top Websites)
    Works out of the box and shows the referring website for the app download. Web referrals must be from Safari on devices with iOS 8 or tvOS 9, or later. Taps from websites using web browsers like Chrome are attributed to that app (see above).
Web referrers
Overview of web referrers
  • Campaigns (previously Top Campaigns)
    Help you to track app and website referrals to measure the impact of an advertising campaign. If you are familiar with the iTunes Affiliate program (you should have been!) and how links are constructed, it’s pretty similar. You basically have to add two tokens to any App Store link to see results in App Analytics.
Campaign Link
Campaign specific link with provider token (pt) and campaign token (ct)

The following two sources are not specifically broken down by keywords or something else and are only shown on the “All”/overview dashboard. But you can break down all “Metrics” and filter/plot them by these “categories”, which gives some interesting details when it comes to conversion rates or where the actual sales came from.

  • App Store Browse
    Customers viewed your app or tapped to download it for the first time while browsing the App Store (for example, in the Featured, Categories, or Top Charts sections).
  • App Store Search
    Customers viewed your app or tapped to download it for the first time from Search on the App Store. Includes Search Ads.


In the beginning called “Stickiness”, the Retention part of App Analytics shows you the general usage behaviour of your users and most importantly the daily retention (oftentimes called “Cohort Analysis”).

Some people might say that Retention is the weakest part of App Analytics as it’s based only on “opt-in” data. This data might not represent the actual usage behaviour of all of your users and it’s not possible to get any app-specific data like events.

If you want to better understand your users and how the interact with your app, you should definitely get some event-based tracking integrated into your app.

Rolling Retention
Overview of the Retention section

Why should you use App Analytics?

First of all, you do not need to include any (3rd party) SDK or turn on anything to get access to App Analytics or record any data. It literally requires no technical implementation and “just” works out of the box. Apple takes care of all the data collection and you don’t have to fear that your app get’s rejected for using any privacy-concerning 3rd party analytics suite.

Secondly, App Analytics has data you won’t find anywhere else like App Store Impressions and Product Page Views. Combine this with reliable attribution links where you have to trust a 3rd party that might have a conflict of interest, because you are also using them to spend your ad dollars? (-> Click/Install fraud)

And most importantly, it’s finally possible to get a complete view of your app’s funnel from discovery to consideration, purchase and to some degree also usage. Especially App Store Views help greatly to better understand your ASO efforts, changes to your screenshots, the impact of adding an App Preview and also localisations.

How should you use App Analytics?

1. Get your App Store conversion rate

Even though App Analytics provides us with a plethora of data, getting meaningful insights out of them isn’t obvious. A good starting point is your app’s conversion rate, i.e. what percentage of people, who visit the app store page, actually download your app.

To get the conversion rate, you have to compare your “App Units” to the “App Store Views”. Paid apps will usually get something between 1% and 5%, whereas free apps can get rates up to 80%.

Test different options and styles for your screenshots and see if they have an impact on the conversion rate. Break the conversion rate down by country or region and understand if localised metadata, mainly app name and description, have an impact on people actually downloading your app. Create and upload an app preview and see if it helps convince people getting your app.

Plotting conversion rate
Plotting the conversion rate

But be aware, the conversion rate is not 100% accurate, as installs from search are counted as App Units, but these numbers are not reflected in the App Store Views (these people never visited your app’s store page).

2. Review and monitor your App Store Views

By monitoring your App Store Views closely, you can learn a great deal about ASO and what worked and what didn’t work. Now you can see directly, if changing your app name or adding keywords has any significant impact on your app’s visibility.

You can also better understand seasonal trends and update cycles. The screenshot below shows the impact of updating an app, which almost doubled the App Store Views.

App Store Views
App Store Views before & after new version

3. Generate campaign links

As already mentioned, if you’re using affiliate links, you can simply add two more “tokens” to your links to better understand how people are converting. Good examples are “internal” sources like your app’s landing page or cross-promotions between you own apps and “external” sources like ad campaigns, promotions or emails.

The provider token pt=123456 will always stay the same, just make sure to use unique and self-explanatory campaign tokens like ct=Landing-Page or ct=Twitter-Ads to identify your different campaigns.

Campaign Link

In general it is important that you only compare sales data with sales data and usage data with usage data (e.g. don’t compare In App Purchases to Sessions) to avoid comparing different data sets.


Apple’s App Analytics is a great starting point into the world of measuring the visibility and success of your app. With no technical implementation needed and minimal configuration it helps app developers and marketers to better understand what ASO efforts worked and which didn’t.

The biggest problem of App Analytics is the opt-in rate for usage data, which makes it hard to get a broader picture. Especially if you invest in paid downloads, you should make sure to get reliable usage data (event-based data) to identify valuable ad networks or 3rd party sources, which provide you with engaged, loyal and lucrative users.

Nevertheless you should not fly “blindly” through the App Store, so make sure you use some kind of app analytics, ideally more than one to better understand which numbers are reliable.

Next step

Head directly over to and have a look at your latest app’s stats in App Analytics. Get a better understanding of your conversion rate by plotting App Units vs. App Store Views.

Once you’re familiar with the basics, you should definitely include an event-based tracking SDK into your app to better understand you users.

Other useful resources: