Adjust v1
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
_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:
Networks:
Name
Target Datatype
Name
STRING
AppKpis
RECORD
EventKpis
RECORD
AdKpis
RECORD
CostKpis
RECORD
FraudKpis
RECORD
Campaigns
RECORD
Campaigns:
Name
Target Datatype
Name
STRING
AppKpis
RECORD
EventKpis
RECORD
AdKpis
RECORD
CostKpis
RECORD
FraudKpis
RECORD
AdGroups
RECORD
AdGroups:
Name
Target Datatype
Name
STRING
AppKpis
RECORD
EventKpis
RECORD
AdKpis
RECORD
CostKpis
RECORD
FraudKpis
RECORD
Creatives
RECORD
Creatives
Name
Target Datatype
Name
STRING
AppKpis
RECORD
EventKpis
RECORD
AdKpis
RECORD
CostKpis
RECORD
FraudKpis
RECORD
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
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
AdKpis
Name
Target Datatype
all_revenue
FLOAT
ad_revenue
FLOAT
ad_impressions
FLOAT
ad_rpm
FLOAT
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
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
_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:
Networks:
Name
Target Datatype
Name
STRING
Events
RECORD
Campaigns
RECORD
Campaigns
Name
Target Datatype
Name
STRING
Events
RECORD
AdGroups
RECORD
AdGroups
Name
Target Datatype
Name
STRING
Events
RECORD
Creatives
RECORD
Creatives
Name
Target Datatype
Name
STRING
Events
RECORD
Creatives
RECORD
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
_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:
Networks:
Name
Target Datatype
Name
STRING
Periods
RECORD
Campaigns
RECORD
Campaigns
Name
Target Datatype
Name
STRING
Periods
RECORD
AdGroups
RECORD
AdGroups
Name
Target Datatype
Name
STRING
Periods
RECORD
Creatives
RECORD
Creatives
Name
Target Datatype
Name
STRING
Periods
RECORD
Creatives
RECORD
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
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