Overview - Ownership Reports

App Ownership data is one of many data points used to create App Insights. ​However, ownership data alone is not a full picture of an end user. ​When ownership data is overlaid with engagement, the full picture of the audience materializes.​

Utilizing Ownership Data

• Compare the device ownership footprint of apps, both inside and outside of your business vertical.
• Determine which apps have large engaged audiences, and which just have large installation bases.
• Trend active & inactive devices over time to gauge an app's engagement effectiveness.
• Trend specific apps to uncover the effectiveness of re-engagement and conquesting initiatives.
• Trend for seasonal and promotion based dips and spikes in ownership across numerous apps.

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Ownership Definitions

Owned
A device Owns an app when it has...

• Either installed the app or engaged with the app within the past 30 days of the date (or date range) being considered.
• And still owns the app as of the date (or date range) being considered.

Engagement is considered at least one (1) app focus event of two (2) consecutive seconds, or longer, in duration.

• For Example: In a daily grain Ownership report where the Ownership count is 1,000,000 devices on Sept 17th, all devices in that count must have either installed or engaged with the app prior to Sept 17th, and still have the app installed as of Sept 17th (ie. have not uninstalled as of Sept 17th). In a weekly or monthly report the same logic holds true.

Owned & Active
A device Owns and is Active with an app when it has...

• Either installed the app or engaged with the app within the past 30 days of the date (or date range) being considered.
• Still owns the app as of the date (or date range) being considered (ie. has not uninstalled the app).
• And Has engaged with the app on the date (or within the date range) being considered.

Engagement is considered at least one (1) app focus event of two (2) consecutive seconds, or longer, in duration.

• For Example: In a daily grain Ownership report where the Owned & Active count is 300,000 devices on Sept 17th, all devices in that count must have installed the app prior to Sept 17th, and still have the app installed as of Sept 17th (ie. have not uninstalled as of Sept 17th), and also engaged with the app on Sept 17th. In a weekly or monthly report the same logic holds true.

Owned & Inactive
A device Owns but is Inactive with an app when it has...

• Installed the app or engaged with the app within the past 30 days of the date (or date range) being considered.
• Still owns the app as of the date (or date range) being considered (ie. has not uninstalled the app).
• But, has not engaged with the app on the date (or within the date range) being considered.

Engagement is considered at least one (1) app focus event of two (2) consecutive seconds, or longer, in duration.

• For Example: In a daily grain Ownership report where the Owned and Inactive count is 700,000 devices on Sept 17th, all devices in that count must have installed the app prior to Sept 17th and still have the app installed as of Sept 17th (ie. have not uninstalled as of Sept 17th), but also not engaged with the app on Sept 17th. In a weekly or monthly report the same logic holds true.

Ownership Breakdown Report

The breakdown bar chart displays the average counts of devices that own a given app over a given date range. The data is presented as those devices that both own and have engaged with the app during the selected date range, and those devices that own the app, but have not engaged with it during the date range.

This chart presents a quick summary of ownership, allowing for at-a-glance analysis and sizing of apps without having to perform offsite aggregations/averages of data from the accompanying time series breakdown of ownership.

For each app in the bar chart:

• The 100% Ownership number represents the average of all devices owning that app (Active and Inactive) within the date range being considered.
• The X% Active represent the portion of the 100% Ownership that the engaged devices account for.
• The X% Inactive represents the portion of the 100% Ownership that the unengaged devices account for.

In all cases, the % Active and the % Inactive for a given app will total to 100% Ownership for that app. Consider this example:

App A has an average daily Ownership count of 1,000,000 devices for the date range of Jan 1, 2022 through Jan 10, 2022. In that same period of time, App A has an average daily Active Ownership device count of 50,000 devices, and an average daily Inactive Ownership device count of 950,000 devices. We can read this data as such...

• On any given day between Jan 1 and Jan 10, App A had an average Ownership footprint of 1 million devices. Some days in this range may show more than 1 million owning devices, and some days less, but generally about 1 million devices owned App A in this date range.

• On any given day between Jan 1 and Jan 10, App A had an average Active Ownership footprint of 50,000 devices, which is roughly 5% of its overall average daily footprint of owning devices.

• On any given day between Jan 1 and Jan 10, App A had an average Inactive Ownership footprint of 950,000 devices, which is roughly 95% of its overall average daily footprint of owning devices.

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Breakdown Chart Scaling

All app data displayed in the Breakdown chart are scaled to the largest app in the report run. For example, in a report run that includes 3 apps with average ownership footprints of 47mm, 43mm, and 1.25mm, the bar charts are scaled to 47mm, and all app data is visually represented comparative to that value.

Ownership Over Time Report

The time series ownership graph displays the precise (distinct/unique) counts of devices that own a given app over a given date range. The data is presented as those devices that both own and have engaged with the app during the selected date range, and those devices that own the app, but have not engaged with it during the date range.

This graph presents a trendable, micro-view, of ownership over time, allowing for data-mining analysis of app growth trends.

The key difference between the Breakdown bar charts, and the Time Series line graph, is that the Time Series line graph presents distinct (unique) counts of devices for each data point, while the Breakdown bar chart is an average of these distinct (unique counts). This means that the Breakdown bar chart is not a distinct (unique) count, but rather an average representation of the distinct (unique) counts from the line graph below it.

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Unique / Distinct Counts

For any given date grain, the Time Series Line graph will always present distinct (unique) counts. This means that at a daily grain, each day is a count of individual devices, with no duplication. At a weekly grain, each week is a count of individual devices with no duplication across days in the week, and at a monthly grain, each month is a count of individual devices with no duplication across days or weeks in the month.

Because each day, week or month is a non-duplicative distinct (unique) count of devices for that data point, these data points cannot be averaged or summed together to build to each other.

Take for example the following scenario:

An Ownership report is run for Monday Feb 1, 2021 to Sunday Feb 28, 2021 for App A. At a daily grain over this range each day is a count of individual devices. Suppose that the first 7 days in this range have the following daily unique device counts:

• Feb 1 = 1,000 Devices Owning
• Feb 2 = 1,000 Devices Owning
• Feb 3 = 1,600 Devices Owning
• Feb 4 = 700 Devices Owning
• Feb 5 = 1,200 Devices Owning
• Feb 6 = 1,500 Devices Owning
• Feb 7 = 1,000 Devices Owning

If the report is re-run at a weekly grain, suppose that the first week (same 7 days as above) returns a count of 1,300 Devices Owning.

We cannot average or sum the daily counts to get to the weekly count. The daily sum is 8,000 devices, far too many. The daily average is ~1,143, too few devices. The reason that this happens is because a single device owning App A can be in any number of the individual day counts, so summing or averaging the day counts will count that device more than once, and the resulting sum or average will not be itself a unique count of individual devices from across all 7 days.

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Time Graph Scaling

Each app utilized in an Ownership report run are plotted in their own time series line graphs, in which the X-Axis (horizontal) for date is tied to all graphs, but the Y-Axis (vertical) for Ownership counts is independently scaled to each app so that it is appropriate to that app's size. This is unlike the Breakdown bar chart scaling, in which all apps are scaled relative to the largest app.

The benefit of independent scaling in the time series line graphs is that apps with both large and small footprints can be viewed comparatively without overly-flattening data trends like spikes and dips. When a large and small app are placed on the same Y-Axis, the disparate relative size of each app reduces the ability to adequately appraise data shifts over time.

Ownership Info Table

All data points from the time series trend graph are available for review and export via the Ownership Info table beneath it.​

The data in the table is exportable to CSV via the provided download button in the upper right hand corner of the table.