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Packages

Packages are extensions to Data Apps with a purpose to enable specific use cases by providing an out-of-box solutions. To do this, a package may contain widgets, reporting tables, data fields, and/or segments. The range of packages varies from providing unique user attributes to be used in custom data visualizations, to full fledged solutions with widget, tables and all the required fields.

You can find the list of Packages available by navigating in a Data App to Data Model > Packages.

User Lifetime Value

LTV, or Lifetime Value, predicts the overall (lifetime) spend of users with 28 or fewer days of behavior to analyze. The calculation uses logarithmic regression to predict this value, which is most useful for marketers so they can effectively set their CPI bids. It can also be used to see the difference in user quality between different countries, platforms, ad networks, or other user data.

LTV requires both om_load and om_revenue as the model utilizes revenue and retention data to predict the spending patterns. In addition, an application needs to have enough users and spending occurring for the model to be able to use the inputs effectively. The smaller the user base, the less predictive power the model will have. As an example, consider breaking LTV out by country. If an application has one million average DAU from China, the LTV model will output a good prediction; however, if the same application has one hundred average DAU from Germany, the predictive power will not be as good, as there is less data from which to generalize the spending patterns.

Custom Basic Metrics

Custom Basic Metrics provides similar metrics to Standard Metrics, but with the added flexibility that all Reporting Tables and Dashboards can be modified by the end user as desired. This package can function as a “jumping off” point for designing custom analyses, as well as provide a similar high level overview as Standard Metrics. Marketers in particular will find this package useful as they can see the general metrics needed for user acquisition, and also specify their own.

Custom Basic Metrics depends on the same three events as Standard Metrics; om_load, om_revenue, and om_user.

Engager Advanced Analytics

Engager Advanced Analytics provides deeper insights into the results of Campaigns and A/B tests by breaking out various metrics by the Experiment and Experience that the users are a part of. Omniata provides A/B test data automatically within the Engager, but this package is a useful accompaniment to the fixed metrics contained there. End users have flexibility to design their own metrics or add onto the existing ones in this package.

Engager Advanced Analytics depends on the same three events as Standard Metrics; om_load, om_revenue, and om_user. In addition, it requires that there have been Campaigns created so that the Experiment and Experience Data Fields are populated.

Funnel Event Type

Funnel Event Type contains a methodology for creating funnel analyses for custom events. In general, funnels require that tables are broken out by UID, which causes the tables to grow very quickly, as every unique combination of activity date, event type, and UID has it’s own row in the table. This package avoids that issue and allows the creation of much smaller tables for the purpose of funnel analyses, which show what events a user generates as they progress through an application.

Funnel Event Type can be used with any combination of events.

System User Fields

Omniata provides you with an option to completely customize your Data App. For this you need to install a Blank Custom Data App. Depending on your use case you can add System User Fields at will. In the following, we will cover the content of each of these Packages.

Acquisition

Use case:

  • User attibution to a specific acquisition source (i.e. ad network)

Included fields:

  • Referral Code
  • User Acquisition Source Code

Core

Use case:

  • Core Fields that are need to basic functionalities

Included fields:

  • API Key
  • Event Count
  • Event Type
  • Uid
  • Users

Country

Use case:

  • Geographical information

Included fields:

  • Acquisition Country Code
  • Acquisition Country Name
  • Country Code
  • Country Name
  • User IP Address

Demographics

Use case:

  • Demographic information

Included fields:

  • Count of om_user
  • Dob
  • Gender
  • User Age
  • User Age Tier
  • User Age Tier Id
  • User Birthdate
  • User Gender

Event Meta Data

Use case:

  • Event details (typically used for debugging)

Included fields:

  • Event API key
  • Event Date
  • Event Highway
  • Event IP Address
  • Event Lane
  • Event Sequence Count
  • Event Time
  • Event Timestamp

Experiments

Use case:

  • Campaign information

Included fields:

  • Experience Id
  • Experience Name
  • Experiment Id
  • Experiment Name

Identity

Use case:

  • User identity

Included fields:

  • Project Id
  • Project Name
  • User Id

Revenue

Use case:

  • Revenue and Spender information

Included fields:

  • Count of om_revenue
  • Currency Code
  • Purchases
  • Revenue
  • Spenders
  • Total
  • User Cumulative Purchases
  • User Cumulative Revenue
  • User Daily Purchases
  • User Daily Revenue
  • User Is Spender
  • User Last Event Time
  • User Purchases Last 7 Days
  • User Spender Tier
  • User Spender Tier Id

SDK Android

Use case:

  • Android specific information

Included fields:

  • Android Device
  • Android Hardware
  • Android Id
  • Android Serial

SDK General

Use case:

  • General SDK information

Included fields:

  • Delta
  • Device
  • Discarded
  • Os Version
  • Platform
  • SDK Version

SDK iOS

Use case:

  • iOS specific information

Included fields:

  • Bundle Id
  • Bundle Version
  • Bundle Version Short
  • iOS Hardware
  • iOS Model
  • iOS Sysname
  • iOS Sysver

SDK Unity

Use case:

  • Unity specific information

Included fields:

  • Unity SDK Version

Session

Use case:

  • Session and Engagement information

Included fields:

  • Count of om_load
  • User Activity Date
  • User Creation Date
  • User Cumulative Events
  • User Cumulative Session Count
  • User Cumulative Session Time
  • User Daily Events
  • User Daily Session Count
  • User Daily Session Time
  • User Days Active Last 7 Days
  • User Is New
  • User Last Event Time
  • User Last Session Started
  • User Retained Days
  • User Session Count Tier
  • User Session Count Tier Id
  • User Time of Current Session

This article was last updated on November 14, 2015 00:24. If you didn't find your answer here, search for another article or contact our support to get in touch.

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