What App Store Connect does not tell you about your apps

In this article, we first look at the four categories Apple uses for its report types. We then examine which of those report types App Store Connect Analytics exposes. Finally, we look at the many report types Apple collects but does not surface in App Store Connect Analytics.

Before we get there, one distinction matters. A report type describes a specific kind of analytics data, such as app crashes, purchases, or widget usage. A report is one concrete dataset within that type for a given time range. If you want to learn more about how Apple structures these reports and how its privacy-first approach shapes them, check out this article.

The Different Categories

Before we look at what App Store Connect Analytics exposes, we should first look at the categories Apple uses for its analytics reports. Apple groups its report types into four categories.

At the highest level, these categories already show that Apple tracks much more than installs and revenue. Some report types focus on how users discover your app on the App Store, others on commerce, others on app behavior after install, and a very large group on framework and device-level usage.

App Store Engagement covers how users interact with your app on the App Store, especially with your product page and in-app events. This data is valuable because you usually cannot collect it yourself with third-party analytics tools. The category contains only two report types, but both cover signals that are highly relevant for acquisition.

Commerce covers the commercial lifecycle from pre-orders to downloads and purchases. Here, downloads include not only first-time downloads, but also redownloads and updates.

App Usage moves closer to behavior after acquisition. It includes report types such as app crashes, installations, deletions, opt-in status, and sessions, but also app clips, CarPlay, and Shortcuts. In total, this category contains nine report types.

The category that changes the picture most is Framework Usage. It starts with common framework features such as Live Activities and widgets, but it goes much deeper. ARKit alone includes report types for session duration, failures, and frame rate throttling. In total, Framework Usage contains 89 report types. At the same time, many of these framework reports are not available for every app. Because Apple applies privacy thresholds, they usually require a large enough user base before any data shows up.

Overall, Apple collects far more usage data than App Store Connect suggests at first glance.

The App Store Connect Reports

Although Apple provides more than 100 report types, App Store Connect Analytics exposes only a small subset of them, and even that subset is limited. To see what is actually available, it helps to separate the overview stats from the metrics view.

Pre-defined Stats

At first glance, the overview in App Store Connect Analytics looks quite broad. In reality, however, it is built from only a small number of report types. Most of its headline stats come from five report types that are reused across multiple tiles, which makes the surface area look larger than it really is.

App Store Discovery and Engagement is one of the key inputs. App Store Connect Analytics uses it without filters for Impressions and with filters for Product Page Views.

App Store Downloads, which belongs to the Commerce category, powers total downloads and, together with App Store Discovery and Engagement, conversion rate. Another Commerce report type, App Store Purchases, powers Proceeds and Proceeds Per Paying User.

The remaining two exposed report types come from the App Usage category: App Crashes and App Sessions. Each powers its corresponding stat, but neither changes the broader pattern: the overview is built from a very narrow base.

In total, the built-in App Store Connect Analytics exposes only five of the 103 available report types.

Advanced Filters

Besides the pre-defined stats, App Store Connect Analytics also gives us a metrics view that is a bit closer to the underlying data. This view is more flexible than the overview, but it still stays within a narrow slice of the full report set. It lets you choose metrics, group them by selected dimensions, and filter them by the same properties.

Many of these metrics are already familiar, including Proceeds, Total Downloads, and Crashes. The metrics view also exposes more granular variants such as First-Time Downloads, Redownloads, and Active Devices. It even includes metrics that many developers may not realize App Store Connect Analytics already provides, such as App Opens, Reminders, and Notification Taps.

Each metric can be grouped by a handful of properties, including Device, Territory, and Source Type. This lets you break down a metric across a selected dimension, for example to see how proceeds vary by device type. The same properties are also available as filters, so you can filter a metric by device and source.

Even here, however, App Store Connect Analytics does not expose the full set of dimensions and filters behind the data. For example, you can group purchase metrics by Payment Method and by whether the user had Pre-Ordered the app. At the same time, the interface remains restrictive. You get only limited filtering per property, and you cannot build more complex queries or calculations across metrics. If you want to do that, ConnectWizard provides custom stats on top of the raw data.

What App Store Connect Hides From You

The five report types exposed through App Store Connect Analytics are only the beginning. Even those report types contain more dimensions than the interface shows. Beyond them, Apple collects many more software and hardware-related report types by default. In the following, we take a closer look at a range of software- and hardware-related report types to show what data might be interesting for your app.

Software Reports

There is a wide range of software-focused report types. At a minimum, they include a count that tells you how often the related event occurred. For example, the count in App Added to Focus shows how often the app was added to a Focus list, either as allowed or denied. In the following, we focus on a few software-related areas that stand out in practice.

If your app relies heavily on App Intents, the Shortcuts report types are especially interesting. Both include the identifier of the shortcut action and whether it completed successfully. One report type covers all executed actions, while the other covers only actions run from the Shortcuts app. The Live Activity Use report type adds another signal by showing the duration of Live Activities.

For apps that make extensive use of widgets, Apple also provides report types for large parts of the widget lifecycle. They start with widget installs on the Home Screen and Lock Screen widget configuration. They also cover how often widgets are added to the Smart Stack and how often they are rotated to the front. There is even a widget usage report type, although Apple does not further distinguish the kind of usage it tracks. What you do not get is data about how long widgets stay installed or when they are removed.

If you build AR features, Apple provides eight ARKit report types. They start with ARSession duration and failures. They then go into feature-specific details such as face tracking usage and world tracking configuration. Some of the more surprising report types show how many seconds pass before frame rate throttling begins and the maximum number of users in a collaborative session.

Accessibility is unfortunately sparse. Beyond a keyboard dictation usage report type and a Speech Framework report, there is little available.

There is much more software-related data than most developers would expect. You can even see how often users choose your browser as the default browser and what the resulting usage rate looks like. If you want to explore this data, ConnectWizard gives you direct access to the raw reports so you can decide which signals matter for your app.

Hardware

Although all of these reports relate to software behavior in some way, Apple also provides report types that show how your app uses hardware. This goes far beyond device model and generation. It includes areas such as camera, connectivity, audio, and accessories.

Audio is one of the richest areas. Apple provides report types for Audio Volume Levels and Duration and Spatial Audio Usage, including head tracking and upmixing. More specific report types such as Audio Input Muting and Audio Input Route and Duration and Call Mode are also available.

Connectivity is another deeply covered area. Bluetooth alone includes report types for advertising, scans, and sessions, to name just a few. Apple also provides report types such as Call Services and Call Performance and Core Location Authorization Results.

Camera and video are also covered. On the camera side, Face-Driven Auto Exposure and Auto Focus Usage and Flashlight Usage reveal patterns that most developers would not expect Apple to expose. For video, there are report types for Video Duration Information, Video Streaming Duration, and picture-in-picture usage through Video PiP Duration.

A few other hardware-related report types are worth mentioning. For CarPlay, there is a report type with visible time, dashboard visible time, and Siri presentation count. For gaming, there is a report that shows session duration and controller type, plus another report that shows how often multiple controllers were used.

As with the software-focused report types, these are only a few examples. Apple exposes many more niche hardware-related report types in its analytics reports documentation. You can start exploring that list here.

Wrap-Up

App Store Connect Analytics exposes only a small part of the more than 100 report types Apple collects for your app. Even within the exposed report types, the interface surfaces only part of the available fields and dimensions. As a result, a large amount of useful data remains hidden unless you work with Apple's raw analytics reports directly. That hidden data can be valuable for both small and large apps, especially because Apple already collects it for free and it becomes more useful as your user base grows.

If you want easier access to all of it, I built ConnectWizard for exactly that. It helps you get started with pre-defined stats and lets you explore the raw data when you want to go deeper. If you have a popular app and want to see what ConnectWizard can reveal about it, get in touch. I want to learn from real-world use cases and keep improving the product.