Adjust

Adjust ETL connector for data replication

Features	Details
Release Status	In-dev
Source API Version	v1
Table Selection	Yes
Column Selection	Yes
Edit Integration	Yes (Tables, filters) / No (Columns, Fields)
Replication Type Selection	No
Authentication Parameters	API Key
Replication Type	Key Based Incremental
Replication Key	Date
Suggested Replication Frequency	2-4 hrs

Tables/APIs Supported:

--- | --- There are three types of tables (queries) that you can integrate: 1. Overview 2. Events 3. Cohorts

These largely mirror different sections in the Adjust dashboard, and allow you to see the relevant KPIs directly.

Data will be fetched in combinations of selected Attribution source, Attribution type, Reattributed and Period filter (in case of cohort queries).

Integrate Adjust with Daton

------ | ------ 1. Sign in to Daton 2. Select Adjust from Integrations page 3. Provide Integration Name, Replication Frequency, and History. Integration name would be used in creating tables for the integration and cannot be changed later 4. Provide API Key for authorizing Daton (https://help.adjust.com/en/article/kpi-service#authentication) and app token (https://help.adjust.com/en/article/app-settings#view-your-app-token) to extract data periodically 5. Post successful authentication, you will be prompted to choose from the list of available Adjust queries (tables) 6. Select from the list of kpis (columns) available for your app along with a combination of filters for each table and your UTC offset 7. Submit the integration 8. For integrating additional apps, one has to create a new integration from step-2.

Workflow

------ | ------ 1. Integrations would be in Pending state initially and will be moved to Active state as soon as the first job loads data successfully on to the configured warehouse 2. Users would be able to edit/pause/re-activate/delete integration anytime 3. Users can view job status and process logs from the integration details page by clicking on the integration name from the active list

Adjust Data

------ | ------

Each combination of filters would be used to query the trackers' data for that particular app as a table in the selected warehouse.

The data will be stored incrementally in a batch of 10 days in the warehouse as following base fields in their respective tables- 1. Networks (top level) 2. Campaigns (sublevel 1) 3. Adgroups (sublevel 2) 4. Creatives (sublevel 3)

Tables

1. _OverviewQueries

   Documentation: https://help.adjust.com/en/article/kpi-service#overview-queries

Fields:

Name	Target Datatype
Name	STRING
Currency	STRING
StartDate	DATE
EndDate	DATE
Attribution source	STRING
Attribution type	STRING
Reattributed	STRING
utc_offset	STRING
Networks	RECORD
_daton_user_id	NUMERIC
_daton_batch_runtime	NUMERIC
_daton_batch_id	NUMERIC

Sub-fields:

1. Networks:

   Name	Target Datatype
   Name	STRING
   AppKpis	RECORD
   EventKpis	RECORD
   AdKpis	RECORD
   CostKpis	RECORD
   FraudKpis	RECORD
   Campaigns	RECORD

   1. Campaigns:

      Name	Target Datatype
      Name	STRING
      AppKpis	RECORD
      EventKpis	RECORD
      AdKpis	RECORD
      CostKpis	RECORD
      FraudKpis	RECORD
      AdGroups	RECORD

      1. AdGroups:

         Name	Target Datatype
         Name	STRING
         AppKpis	RECORD
         EventKpis	RECORD
         AdKpis	RECORD
         CostKpis	RECORD
         FraudKpis	RECORD
         Creatives	RECORD

         1. Creatives

            Name	Target Datatype
            Name	STRING
            AppKpis	RECORD
            EventKpis	RECORD
            AdKpis	RECORD
            CostKpis	RECORD
            FraudKpis	RECORD

            1. AppKpis

      Name	Target Datatype
      sessions	FLOAT
      clicks	FLOAT
      installs	FLOAT
      uninstalls	FLOAT
      deattributions	FLOAT
      impressions	FLOAT
      uninstall_cohort	FLOAT
      reinstalls	FLOAT
      click_conversion_rate	FLOAT
      impression_conversion_rate	FLOAT
      ctr	FLOAT
      reattribution_reinstalls	FLOAT
      reattributions	FLOAT
      revenue_events	FLOAT
      revenue	FLOAT
      all_revenue	FLOAT
      cohort_revenue	FLOAT
      daus	FLOAT
      waus	FLOAT
      maus	FLOAT
      limit_ad_tracking_installs	FLOAT
      limit_ad_tracking_install_rate	FLOAT
      limit_ad_tracking_reattributions	FLOAT
      limit_ad_tracking_reattribution_rate	FLOAT
      gdpr_forgets	FLOAT
      cohort_ad_revenue	FLOAT
      cohort_all_revenue	FLOAT

   2. EventKpis

      Name	Target Datatype
      revenue	RECORD
      events	RECORD
      revenue_per_event	RECORD
      revenue_events	RECORD
      first_events	RECORD
      revenue_per_revenue_event	RECORD

      Each RECORD of EventKpis:

      Name	Target Datatype
      EventName	STRING
      Value	FLOAT

   3. AdKpis

      Name	Target Datatype
      all_revenue	FLOAT
      ad_revenue	FLOAT
      ad_impressions	FLOAT
      ad_rpm	FLOAT

   4. CostKpis

      Name	Target Datatype
      install_cost	FLOAT
      click_cost	FLOAT
      impression_cost	FLOAT
      cost	FLOAT
      paid_installs	FLOAT
      paid_clicks	FLOAT
      paid_impressions	FLOAT
      ecpc	FLOAT
      ecpm	FLOAT
      ecpi	FLOAT
      cohort_gross_profit	FLOAT
      return_on_investment	FLOAT
      rcr	FLOAT
      roas	FLOAT

   5. FraudKpis

      Name	Target Datatype
      rejected_installs	FLOAT
      rejected_installs_anon_ip	FLOAT
      rejected_installs_too_many_engagements	FLOAT
      rejected_installs_distribution_outlier	FLOAT
      rejected_reattributions	FLOAT
      rejected_reattributions_anon_ip	FLOAT
      rejected_reattributions_too_many_engagements	FLOAT
      rejected_reattributions_distribution_outlier	FLOAT
      rejected_reattributions_click_injection	FLOAT
      rejected_install_rate	FLOAT
      rejected_install_anon_ip_rate	FLOAT
      rejected_install_too_many_engagements_rate	FLOAT
      rejected_install_distribution_outlier_rate	FLOAT
      rejected_install_click_injection_rate	FLOAT
      rejected_reattribution_rate	FLOAT
      rejected_reattribution_anon_ip_rate	FLOAT
      rejected_reattribution_too_many_engagements_rate	FLOAT
      rejected_reattribution_distribution_outlier_rate	FLOAT
      rejected_reattribution_click_injection_rate	FLOAT

2. _EventQueries

   Documentation: https://help.adjust.com/en/article/kpi-service#event-queries

Fields:

Name	Target Datatype
Name	STRING
Currency	STRING
StartDate	DATE
EndDate	DATE
Attribution source	STRING
Attribution type	STRING
Reattributed	STRING
utc_offset	STRING
Networks	RECORD
_daton_user_id	NUMERIC
_daton_batch_runtime	NUMERIC
_daton_batch_id	NUMERIC

Sub-fields:

1. Networks:

   Name	Target Datatype
   Name	STRING
   Events	RECORD
   Campaigns	RECORD

   1. Campaigns

      Name	Target Datatype
      Name	STRING
      Events	RECORD
      AdGroups	RECORD

      1. AdGroups

         Name	Target Datatype
         Name	STRING
         Events	RECORD
         Creatives	RECORD

         1. Creatives

            Name	Target Datatype
            Name	STRING
            Events	RECORD
            Creatives	RECORD

      2. Events

         Name	Target Datatype
         EventName	STRING
         first_events	FLOAT
         revenue_per_revenue_event	FLOAT
         revenue_events	FLOAT
         revenue	FLOAT
         events	FLOAT
         revenue_per_event	FLOAT

2. _CohortQueries

   Documentation: https://help.adjust.com/en/article/kpi-service#cohort-queries

Fields:

Name	Target Datatype
Name	STRING
Currency	STRING
StartDate	DATE
EndDate	DATE
Attribution source	STRING
Attribution type	STRING
Reattributed	STRING
utc_offset	STRING
period	STRING
Networks	RECORD
_daton_user_id	NUMERIC
_daton_batch_runtime	NUMERIC
_daton_batch_id	NUMERIC

Sub-fields:

1. Networks:

   Name	Target Datatype
   Name	STRING
   Periods	RECORD
   Campaigns	RECORD

   1. Campaigns

      Name	Target Datatype
      Name	STRING
      Periods	RECORD
      AdGroups	RECORD

      1. AdGroups

         Name	Target Datatype
         Name	STRING
         Periods	RECORD
         Creatives	RECORD

         1. Creatives

            Name	Target Datatype
            Name	STRING
            Periods	RECORD
            Creatives	RECORD

   2. Periods

      Name	Target Datatype
      Period	STRING
      time_spent_per_session	FLOAT
      converted_user_size	FLOAT
      conversion_per_user	FLOAT
      conversion_distribution	FLOAT
      converted_users	FLOAT
      revenue_events_per_paying_user	FLOAT
      events	FLOAT
      conversion_per_active_user	FLOAT
      revenue_events_per_active_user	FLOAT
      revenue_events_per_user	FLOAT
      first_uninstalls_total	FLOAT
      first_reinstalls	FLOAT
      first_uninstalls_total	FLOAT
      reinstalls	FLOAT
      reinstalls_total	FLOAT
      gdpr_forgets	FLOAT
      gdpr_forgets_total	FLOAT
      first_uninstalls	FLOAT
      uninstalls_total	FLOAT
      uninstalls	FLOAT
      reattributions_per_deattribution	FLOAT
      deattributions_per_user	FLOAT
      revenue_events	FLOAT
      reattributions_per_user	FLOAT
      deattributions	FLOAT
      reattributions	FLOAT
      events_per_active_user	FLOAT
      events_per_user	FLOAT
      events_per_converted_user	FLOAT
      paying_users	FLOAT
      paying_user_rate	FLOAT
      paying_user_size	FLOAT
      paying_users_retention_rate	FLOAT
      cohort_size	FLOAT
      retained_users	FLOAT
      retention_rate	FLOAT
      sessions	FLOAT
      sessions_per_user	FLOAT
      revenue	FLOAT
      revenue_total	FLOAT
      revenue_per_user	FLOAT
      revenue_per_paying_user	FLOAT
      revenue_total_in_cohort	FLOAT
      revenue_events_total_in_cohort	FLOAT
      lifetime_value	FLOAT
      paying_user_lifetime_value	FLOAT
      time_spent	FLOAT
      time_spent_per_user	FLOAT