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

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

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

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