Set up your view in Datascape

When you first open Datascape, make sure your view is configured to display the right apps, time frame, and key data filters for your analysis.

Configure your data

Use the Data configuration () button to view all available options and set up your base view. Changes to the configuration are automatically saved per user and persist between login sessions. From here you can control:

• Time period
• Filters
• Attribution
• Settings

Time period

Date period

Use the Date picker to select the time period for which you want to display data. By default, data is displayed for the last 7 days. The date picker presents a list of preset time periods and includes the option to set a custom one. Use the calendar to define your preferred period.

Compare to

Use the Compare to filter to compare data between two time periods. Comparisons are not shown by default.

The filter allows you to compare your selected time period with the following:

• Previous immediate period.
• Previous periods from a day, a week, a month, a quarter, or a year ago.
• Custom periods.
  • Example: You select a period of 7 days using the Date picker, from Aug 24 to Aug 30. Then, you selected Aug 10 as a custom-period starting date using the Compare to filter. The filter automatically selects the remaining days from Aug 10 to Aug 16.

Date picker - Select a custom time period of 7 days from Aug 24 to Aug 30.

Compare over a period - Select Aug 10 and filter is automatically set to a time period of 7 days from Aug 10 - Aug 16.

Choose between Chart view and Table view.

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Filters

When applying filters in Datascape you have three ways to define what appears in your view:

• Select all: Include every available value.
• Include: Manually choose only the values you want to see. This is useful when you need to focus on a limited subset of data.
• Exclude: Select only the values you want to leave out. All other values will be included automatically.

Filtering using the include option

Filtering using exclude option.

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Global filters vs. widget-level filters

When you open Datascape and you set up a dashboard or report, you’ll see the global filter bar at the top. Global filters define the overall scope of data shown across your report or dashboard and act as the base view for all widgets. However, each widget can have its own widget-level filters. These are commonly used when you want to combine a broad overview of your data (set by the global filters) with more focused or comparative views (defined by widget filters).

There may be times where there is conflict in how you have set up inclusion or exclusion filtering between your global and widget-level filters. In such instances, the final data shown in a widget follows these rules:

1. Different filter types: both are applied
   • If the global filter uses Include and the widget uses Exclude, or vice versa, both filters are applied.
2. Same filter type: widget filter overrides.
   • If both the global and widget filters use the same filter type (both Include or both Exclude), the widget-level filter replaces the global filter.

Attribution

Attribution types

Adjust relies on engagement details sent by our partners to perform attribution according to your attribution settings. During each attribution round, the device and its future performance gets assigned to the corresponding type of a winning engagement.

With the Attribution Types filter, you can select one or multiple engagement types to analyze the users’ performance for. The totals of your KPI’s will remain constant, but your Attribution Types selection will influence how KPIs are categorized between non-organic and organic sources. Non-organic installs and post-install performance in your report will only reflect the users attributed to the engagement types you selected in the filter. All other installs and post-install performance (that does not match the selected types) will be reported under Organic.

To maintain consistency and comparability across the partners, Adjust distinguishes between the following engagement types for this filter:

• Click: Devices attributed to a regular click (typically navigates user to the app store or the app itself for reattribution)
• Engaged Ad: Devices attributed to an ad interaction marked as “engaged” by the ad network.
• Impression: Devices attributed to a view-through engagement.

If all Attribution Types are selected, then Organic represents the devices that weren’t attributed to any ad engagement during the last attribution round.

At launch Adjust supports “engaged” signals for select Self-Attributing Networks, additional partners will be added in the coming weeks.

Attribution source

Use Attribution source to filter attributions and in-app activity under the user's original attribution link or view their activity distributed across their original attribution link, and later reattributions, based on the selected timeframe.

• First - View a user's original attribution source.
• Dynamic - View all the sources a user was attributed or reattributed to.

Attribution status

Use Attribution status to view data for users with a specific attribution status. You can filter by:

• Installed - Users still attributed to their original install link.
• Reattributed - Users reattributed to a new source.
• All - All users.

Settings

Ad spend source

Adjust uses two different ad spend sources to fetch spend data: Network and Attribution. Use the Ad spend source filter to determine which source you want data displayed from. See How ad spend source affects your data to know more.

Ad spend version

Ad revenue sources

Use the Ad revenue sources filter to view data from the ad revenue sources that you want. This filter is available on the Monetization dashboard only. See Ad revenue to learn more.

Selecting multiple ad revenue sources for the same partner can cause Datascape to return duplicate data. For example: if you select both Admost and Admost SDK, you will receive duplicated revenue information from both sources. Select a single source from each partner to avoid duplications.

IAP revenue mode

In-App (IAP) revenue mode lets you visualize data according to the approximate gross profit margin you earn from in-app purchases. This mode applies a calculation to the gross revenue reported from in-app purchases, deducting the estimated associated costs. The deduction also applies to any metrics that use IAP revenue data.

1. You have an in-app purchase event worth 100 USD for an app in the Apple App Store.
2. The transaction took place in the UK where you pay 20% VAT. However, VAT is included in the app price, meaning that the 100 USD purchase already has VAT factored in. The pre-VAT amount is 83.33 USD.
   • Depending on the country of the transaction, taxes and charges may vary.
3. The Apple App Store takes 30% of the pre-VAT amount, leaving you with a total of 58.33 USD.

In this example, the approximate profit margin is 60%. To set up your reports to show numbers that represent the amount you will actually receive after costs, you can enable the IAP revenue mode at 60% to apply the reduction to all metrics.

Cohort maturity

Adjust allows you to visualize your data in terms of Cohort maturity. Select the immature option to view the accumulated data for ongoing cohort periods, or select mature for fully-elapsed periods. See How cohorts work to know more.

Environment

Visualize and analyze your data in production or Sandbox mode, select Sandbox mode to check your data for testing purposes.

UTC offset

Use the UTC offset filter to choose the timezone in which you want to display data.