Using Segments in Explorer, you can calculate ad hoc metrics from your app’s data using powerful aggregation, filtering and grouping capabilities.
For example, when you run queries with segments, you can determine the popularity of a product, based on a geographical breakdown or other demographic. In so doing, you can analyze product trends for your app or business.
Typically, you can analyze your app’s data by aggregating and grouping metrics by specific dimensions. This type of segmentation analysis is most useful when you need to dig deeper into a particular metric and understand how it breaks down by different dimensions.
The metrics you can analyze in Explorer Segments include:
- Average Time per Session
- Average Time per User
- Total Time
- Event - Occurrences
- Event - Unique Users
You can apply various dimensions to these metrics that illustrate how they break down. By adding filters, you can also limit the scope of the data being analyzed in your query.
Build & Run Segments Queries¶
To build and run Segment queries, first navigate to Explorer as described in Getting Started.
Once you are in the Explorer UI, you can run saved queries by selecting one from the Saved Queries dropdown or create a new query by clicking the + New Query button at the right side of the page.
To build and run a new Segment query:
- Click the + New Query button.
- Select the metric to be segmented under Metrics.
- Optional: Specify the first dimension to define the X-axis
- Optional: Specify an additional dimension to further segment the metric
- Optional: Add Filters to limit the scope of the Segment query
- Click Run Query.
Example Use Cases¶
When you segment your audience, you gain valuable insights about the users who have installed your app (and those who haven’t). Segmenting can help your marketing and development teams to further bolster installations in the more responsive segments, or increase the number of installations in the less responsive segments.
If you build a simple segments query for your dataset, specifying the number of DAU’s by Region, with User metrics, Dimensions defined as Session Date/Time in days, and User Region as All, and run that query, Explorer will report the data similar to the chart shown below.
The DAU count tells you how many users in your install base have used your app at least once on a given day. If a user initiates 10 sessions, the active user session count only increments once for that user on that day.
If your goal is to increase the number of unique users who use your app on a regular basis, you can determine the unique user session count, and work towards increasing the number of users who initiate sessions.
You can show trending data to expose unique user sessions over time. For apps that generate ad revenue, unique user sessions determine the number of unique impressions (the number of unique users who have viewed an advertisement) that you can bill to your advertisers.
Segment DAU by Region¶
Segmenting DAU by region provides insights into the location and culture of your users. Knowing your users’ geographical region can help you make decisions about promoting and localizing your app to increase adoption, and targeting in-app advertising.
Segment DAU by Age and Gender¶
Segmenting by age and gender provides important demographic information about the users who have installed your app. Knowing your users’ age and gender can help you make decisions about promoting your app to increase adoption, and targeting in-app advertising.
In Dimensions, you can specify the Session Date/Time for segmentation. Explorer lets you segment by days, day of the month, day of the week, hour of the day, months, month of the year and week. This level granularity enables to build queries that return a wide range of data for segmentation reporting.
Note that a session begins when an app is launched and ends when the app is terminated.
You can specify the session length as the length of time between the start app event and the end app event, which can vary by platform.
In Filters, you can add filters to your query, specifying Install Date/Time or Session Date/Time, in addition to attributes, like Attributed/Organic, Acquisition Channel and Acquisition Campaign, in additions to various demographics.
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