Analytics Event Volume


The Analytics Event Volume page provides visualizations of the event totals by days, weeks or months. The graph may be moused over to display the data associated with each event.


Analytics Interface

  1. Log in to Kochava.
  2. Select the desired app.
  3. Select App Tools>Analytics.
  4.  

     

    NOTE: By default, the Analytics Dashboard Interface is loaded.

  5. Select the Analytics drop-down menu>Event Volume.
  6.  


Analytics Page Tools

For more information on the tools available for this Analytic Page such as the date field, exporting device IDs, sharing the page and applying Cohorts and filters, refer to our Analytics Page Tools support documentation.


Event Volume Chart Overview

The Event Volume Chart is divided into 3 main sections which are event names, the graphical display of event volume and the event totals for the selected time frame. Mousing over any event within the graphical display of event volume will display the data associated with the corresponding day/week/month.

NOTE: When leveraging Cross App functionality, the event data that is consistent between each app of the App Name filter will be displayed within the Event Volume. For more information about adding apps using the filter feature, refer to our Analytics Page Tools support documentation.

 

analyticseventvolumechartoverviewhd

A. Event Names
B. Graphic Display of Event Volume
C. Mouseover Data
D. Event Totals


Event Organization

Events within the Event Volume display can be organized in many different ways in order to assist in the optimization of data visualization.

  1. From the Split By drop-down menu, Select one of the following:
    1. App
      1. App ID
      2. App Name
      3. App Version

      NOTE: In order to use the App split by feature, the desired 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. Campaign
      1. Campaign
      2. Creative
      3. Segment
      4. Tracker
    3. Device
      1. Device Carrier Name
      2. Device Network Conn Type
      3. Device Orientation
      4. Device Os
      5. Device Os Version
      6. Device Type
      7. Device Version
    4. Events
      1. Ad Size
      2. Ad Type
      3. Country Code
      4. Currency
      5. Currencycode
      6. Data
      7. Device Type
      8. Game
      9. Pack
      10. Placement
      11. Product
      12. Receipt Status
      13. Revenue
      14. TV Brand Name
      15. TV Channel
      16. TV Channel Name
      17. TV DMA
      18. TV Episode Title
      19. TV Genre
      20. TV Name
      21. TV Product Name
      22. TV Program Name
      23. NOTE: Kochava now provides the tracking of events associated with the serving of advertisements through television. Once the TV advertisement data has been collected, the event data can be visualized within the Analytics dashboard. For instructions on visualizing TV tagging data within Analytics, refer to our TV Tagging support documentation.

      24. User ID
    5. Location
      1. City
      2. Country
      3. Zip
    6. Attribution
      1. Type
      2. Matched To
      3. Matched By
      4. Network Name
      5. Network ID
      6. Network Key
      7. Site
    7. Traffic Verification
      1. Traffic Verification Fail Reason
      2. Traffic Verified
  2. Locate the desired Event and click the Event Expand Button.

 

analyticseventvolumesplitbyhd

A. Events organized by Campaign
B. Campaigns Event has occurred in
C. Mouseover Data


Organize by Interval

Intervals within the Event Volume display can be organized to display specific windows of time.

  1. From the Interval drop-down menu, Select one of the following:
    1. Days
    2. Weeks
    3. Months

 

analyticseventvolumeintervalhd

A. Interval organized by Weeks
B. Intervals within Date Range
C. Mouseover Data


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.
  •  

    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.

 

Split By Network:

Expanding _PredictedChurn provides the details of the churn that occurred within the associated networks. Mousing-over the desired network and day will display the associated churn count.

 

A. Mouse-over the associated network and day to view the churn count.

 
 

Last Modified: Sep 4, 2018 at 8:04 am