The Analytics Explorer page provides a detailed breakdown of any dimension and metric within the selected app. The Explorer page is fully customizable and provides the ability to include, exclude and reorganize data to maximize efficiency.

NOTE: From any of the other Analytics pages, you can navigate to the Explorer tool and retain the current filter settings. This provides in depth views into any aspect of an app’s data.

Analytics Interface

Log in to Kochava.
Select the desired Account and App.
Select Analytics > Explorer.

Analytics Page Tools

For more information about the tools that can be used on the Analytics page such as date range, filters, sharing the page and exporting device ID, refer to our Analytics Page Tools support documentation.

Filters:

Filters

Filters can be used to further refine, organize and visualize the displayed data in a method that is most beneficial. Multiple filters can be added and saved for later use.

Click Add Filter.

Added filters may be inclusive or exclusive. Select from the following filters categories:

App — Based on the available apps within account.
Campaign — Based on campaign naming conventions.
Device — Based on user agent.
Events — Based on Standard or Custom events.
Location — Based on IP address.
Attribution — Based on attributed installs and campaign attribution settings.
Agency — Based on the available apps within the agency account.
Traffic Verification — Based on Traffic success or failure.

Once the filter category has been selected, one or more values may be added per filter. Filters can be saved and reapplied within any of the Analytics pages.

Select the Filter drop-down menu, Select desired Filter.
Add desired values.
Click “X” to remove Filter.

A. Filters
B. Click “+” to add metric
C. Click “X” to remove metric
D. Click “X” to remove Filter and associated Metric(s)

Save App Filters —

Click the “X” to remove a value.
Click “+” to add a value.
Click Save View.

Selecting a Saved Filter —

Select the Saved States drop-down box.
Select the desired Filter Set.

A. Select the desired Filter Set

Deleting Filter Sets:

When saved Filter Sets are no longer needed, they can be deleted.

WARNING: Analytics filters are also used to generate dynamic Audience Export reports, if a filter that is used to create an Audience Export report is deleted an error will be generated when the report is pulled. Before deleting a filter, verify that the filter is not used to pull a report.

Select the Saved States drop-down box.
Select the desired Filter Set.
Click “X” to remove.
Click Proceed.

A. Click “X” to remove

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Explorer Chart Overview

The Explorer chart is divided into 2 main sections, the Dimensions and Metrics selection areas, and the interactive chart.

Dimensions and Metrics can be added, removed and reordered as needed.

Mousing over Dimensions displays the expand button. By clicking on the Dimension expand button, specific level data can be displayed.

NOTE: When leveraging Cross App functionality, Explorer data for all apps within the App Name filter will be displayed. Explorer data may be displayed for each app by utilizing the dimensions feature. For more information on viewing Explorer data by app, refer to the Explorer Organization section.

NOTE: Only the first 250 rows will be displayed for the highest level dimension defined within the view. Adding a highest level dimension with over 250 unique combinations can produce varying results depending on dimension order.

A. Dimensions and Metrics can be updated and organized as needed
B. Chart displaying selected Dimensions and Metrics
C. Dimension expand button.
D. Summary values are a sum of each row in the Metrics column. The only exception(s) to this are the RPU and RPI Metrics in which Kochava takes an average of the column.

Explorer Organization

Explorer data can be organized in many different ways in order to assist in the optimization of data visualization.

NOTE: The dimensions available is dependent on the data that is being sent to Kochava.

Within the Dimensions section, Click the “+” icon and Select one of the following:

Agency Name
App ID
App Name
App Version
Campaign
Creative
Segment
Tracker
Device Carrier Name
Device Language
Device Network Conn Type
Device Orientation
Device Os
Device Os Version
Device Type
Device Version
Ad Size
Ad Type
Churn Liklihood
Churn Score
Currency
Friends Invited
Items in Cart
Mtr Rejected
Data
Device Type
Placement
Product Brand
Product Name
Product Sku
Product Style
Push Campaign
Push Segment
Receipt Status
Revenue
Session Duration
Subscription Action
Sum
Total Sessions
User Id
User Total Revenue To Date
Event Name
City
Country
DMA
Region
Zip
Type
Install Campaign
Install Creative
Install Matched By
Install Network Name
Install Site
Install Tracker
Matched To
Matched By
Network Name
Network Id
Network Key
Partner Ad Group Id
Partner Ad Group Name
Partner Campaign Id
Partner Campaign Name
Partner Keyword
Partner Platform

NOTE: For more information about how the Partner fields map to SAN metadata, please refer to our SAN Networks Campaign Data Mapping support documentation.

QR Code
Site
Traffic Verification Fail Reason
Traffic Verified
By Hour
By Day
By Week
By Month

NOTE: By default, Campaign, Segment, Tracker, Event Name and By Day Dimensions are displayed.

NOTE: In order to use the App dimension feature (App ID, App Name, App Version), the desired corresponding apps must be added utilizing the filter feature. For more information about adding apps using the filter feature, refer to our Analytics Page Tools support documentation.

Within the Metrics section, Click the “+” icon and Select one of the following:

NOTE: The metrics available is dependent on the data that is being sent to Kochava.

Events
Clicks
New Users
ROI
RPU
Revenue
Cohort Installs
LTV
RPI
New Users Attr
Users
CVR
Impressions
Sessions
Average Session Count
Average Session Time
Events per User
Total
Search
Events per User
Total Users
Ad View
Purchase
Push Opened
Rating
Logout
Invite Friend
Login
Uninstall
Subscribe
Register
Custom events being sent to the app

NOTE: By default, Users, Events, Revenue, RPU, and Average Session Time Metrics are displayed.

NOTE: (Distinct) Metrics limit the associated event to display only the initial occurrence of a device ID for the given date range.

Specific Dimensions and Metrics can be removed by Clicking on the “X”.

Dimensions and/or Metrics can also be reordered by dragging and dropping the Dimensions and/or Metrics into any desired order. Once Dimensions and/or Metrics have been reordered, the interactive chart will be updated to reflect the change.

A. Original Configuration
B. Drag and Drop to reorder
C. New Configuration

Predicted Churn

Churn is the rate at which customers install an app and shortly afterwards abandoned the usage of the app. Churn rate is often used as an indicator of the health of an app’s user base. Kochava has created an algorithm that will score the likelihood to churn within only seven days providing marketers the opportunity to mitigate churn or reengage with their retained users. Our machine learning models observe over 30 data points which can include standard post-install events, custom post-install events tracked by the advertiser, and derived/engineered features.

NOTE: By default, churn modeling is not enabled for an app. If churn modeling needs to be enabled, contact your Client Success Management team.

Churn Score:

The Churn Score is a numeric representation of the probability that the device will churn. The Churn Score is a number that is between 0 and 1, where the closer the score is to 1 the more likely the device is to churn.

Churn Likelihood:

Churn Likelihoods are categories of devices based on the likelihood to churn. The groups represent four ranges of churn scores and are based on a dynamic mid-point that has been optimized for each app/model.

Low — A group of devices that has a very low risk of churning. On average, these devices will have a churn score between 0 and 0.25.
Medium Low — A group of devices that have a moderately low risk of churning. On average, these devices typically have a churn score between 0.25 and 0.50.
Medium High — A group of devices that have a moderately high risk of churning. On average, these devices typically have a churn score between 0.50 and 0.75.
High — A group of devices that have the highest likelihood of churn. On average, these devices typically have a churn score of 0.75 or higher.

Analytics Explorer provides the most in-depth look into churn, completing the following steps provides the deepest look into churn:

Click Add a Filter.
Select Churn Likelihood.
Add the desired Likelihood Levels:
- Low — A group of devices that has a very low risk of churning. On average, these devices will have a churn score between 0 and 0.25.
- Medium Low — A group of devices that have a moderately low risk of churning. On average, these devices typically have a churn score between 0.25 and 0.50.
- Medium High — A group of devices that have a moderately high risk of churning. On average, these devices typically have a churn score between 0.50 and 0.75.
- High — A group of devices that have the highest likelihood of churn. On average, these devices typically have a churn score of 0.75 or higher.
Remove Dimensions, except for Network Name.
Add Dimensions > Churn Likelihood.

BEST PRACTICES: It is recommended that Network Name be the primary Dimension with Churn Likelihood being the secondary Dimension.

Expand the desired Network to view the associated churn data.

A. Add a Churn Likelihood filter.
B. Add the Churn Likelihood Dimension and remove other Dimensions except for Network Name.
C. Churn Likelihood Data.

NOTE: The device IDs associated with the higher levels of churn may be exported or saved as an audience for reengagment or push campaigns. For more information about exporting device IDs, refer to our Analytics Page Tools support documentation.

Exporting the Explorer Data

The data displayed within the Explorer chart can be exported in CSV format.

NOTE: Only the highest dimension selected will be displayed as part of the export.

Analytics Explorer