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 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.

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Analytics Interface

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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.

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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.

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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 Free App Analytics.

1. Within the Dimensions section, Click the “+” icon and Select one of the following:
1. App ID
2. App Name
3. App Version
4. Campaign
5. Creative
6. Segment
7. Tracker
8. Device Carrier Name
9. Device Language
10. Device Network Conn Type
11. Device Orientation
12. Device Os
13. Device Os Version
14. Device Type
15. Device Version
16. Ad Size
17. Ad Type
18. Churn Liklihood
19. Churn Score
20. Currency
21. Friends Invited
22. Items in Cart
23. Mtr Rejected
24. Data
25. Device Type
26. Placement
27. Product Brand
28. Product Name
29. Product Sku
30. Product Style
31. Push Campaign
32. Push Segment
33. Receipt Status
34. Revenue
35. Session Duration
36. Subscription Action
37. Sum
38. Total Sessions
39. User Id
40. User Total Revenue To Date
41. Event Name
42. City
43. Country
44. DMA
45. Region
46. Zip
47. Type
48. Install Campaign
49. Install Creative
50. Install Matched By
51. Install Network Name
52. Install Site
53. Install Tracker
54. Matched To
55. Matched By
56. Network Name
57. Network Id
58. Network Key
59. Partner Ad Group Id
60. Partner Ad Group Name
61. Partner Campaign Id
62. Partner Campaign Name
63. Partner Keyword
64. 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.

65. QR Code
66. Site
67. Agency Name
68. Agency Id
69. Traffic Verification Fail Reason
70. Traffic Verified
71. By Hour
72. By Day
73. By Week
74. 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.

2. 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.

1. Events
2. Clicks
3. New Users
4. Cost
5. ROI
6. RPU
7. Revenue
8. Cohort Installs
9. LTV
10. RPI
11. New Users Attr
12. Users
13. CVR
14. Impressions
15. Sessions
16. Average Session Count
17. Average Session Time
18. Events per User
19. Total
20. Search
21. Events per User
22. Total Users
23. Ad View
24. Purchase
25. Push Opened
26. Rating
27. Logout
28. Invite Friend
29. Login
30. Uninstall
31. Subscribe
32. Register
33. 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

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Predicted Churn

FAA Limited Option: This feature is not available within Free App Analytics. Contact us for more information on upgrading to a paid Kochava account.

 

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:

1. Click Add a Filter.
2. Select Churn Likelihood.
3. 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.

    

   BEST PRACTICES: Kochava recommends that the focus should be on the higher levels of churn. Focus mainly on the High, Medium High and possibly the Medium Low levels of churn.

4. Remove Dimensions, except for Network Name.
5. Add Dimensions>Churn Likelihood

 

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

 

6. 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.

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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.