The Cohort pipeline can be used to request and retrieve data that has been aggregated by user cohort, e.g. a date on which the user has installed/made a purchase/registered etc. This allows you to retrieve cohort-based KPIs such as retention by day after install.

Read more about this here

Configuring the Credentials

Select the account credentials which has access to relevant Adjust data from the dropdown menu & Click Next

Credentials not listed in dropdown ?

Click on + Add New for adding new credentials

Data Pipelines Details

Data Pipeline

Select Cohort from the dropdown

adjust cohort list

Select one or more KPIs from the drop-down. KPIs specifies the comma-separated list of requested KPIs that may vary for each of the resources.

While you can add multiple KPIs here, the table size may become too large and so it is advisable to add one or few KPIs per pipeline and use Union queries in the data warehouse to join the data for consumption.

Setting Parameters

Parameter Description Values

App ID


Enter the App ID.


Default Value: None

Cohort Period


The period describes the segmentation depth of the data. Select the Cohort period for which you wish to get the data in each run.

{Day, Week, Month}

Custom Cohort Period definition


You can run a cohort query for a specific day, for a range of days (or both), or a specific week or range of weeks using this. Read more about this [here, window=_blank]. Enter the custom cohort period definition for which you wish to get the data in each run.


Default Value: None



Grouping specifies a grouping for the dataset. The resulting data will be nested in the exact order as specified. Select the option according to which you want the data to be grouped by in each run. Recommended to use one grouping per report.

{Trackers, Networks, Campaigns, Adgroups, Creatives, Hours, Days, Week, Month, Countries, Region, Device Types, OS Names, Partners, Apps}



Select the UTC offset for timezones.

{Offset in Hours and Minutes}

Default Value: Delete

Human Readable KPIs


Select if the KPIs are human readable or not. TRUE translates the resulting KPIs, period, etc. headlines into appropriately formatted English facilitating sharing results from the CSV API calls as reports, without having to rename columns or headlines.

{True, False}

Default Value: False

No of Days


Enter the number of days for which you wish to get the data in each run.

Integer value (Recommended value 30)

Insert Mode


This refers to the manner in which data will get updated in the data warehouse, with 'Upsert' selected, the data will be upserted (only new records or records with changes) and with 'Append' selected, all data fetched will be inserted. Selecting 'Replace' will ensure the table is dropped and recreated with fresh data on each run. Recommended to use "Upsert" option unless there is a specific requirement.

Upsert, Append, Replace

Default Value: UPSERT


Click on + Add New for setting up a new filter

Available filters are as under:-

Filter Description Values



Filter KPIs by installed or reattributed users only or by all users (default)


Attribution Type


Filter KPIs based on the attribution type.


Attribution Source


Filter KPIs based on the attribution source. Determines whether in-app activity is assigned to the user’s install source (FIRST) or divided among the install source and subsequent sources of reattribution (DYNAMIC).




Filter KPIs based on the countries [Choose from ISO 3166 alpha-2 country names]

List of countries of the world.

Operating System


Filter KPIs based on the operating system names.

List of os names eg. ios, android

Device Types


Filter KPIs based on the device types.

List of device types eg. phone, tablet



Filter KPIs based on the standard or account-specific business regions.


adjust cohort config one
adjust cohort config two

Datapipeline Scheduling

Scheduling specifies the frequency with which data will get updated in the data warehouse. You can choose between Manual Run, Normal Scheduling or Advance Scheduling.

Manual Run

If scheduling is not required, you can use the toggle to run the pipeline manually.

Normal Scheduling

Use the dropdown to select an interval-based hourly, monthly, weekly, or daily frequency.

Advance Scheduling

Set schedules fine-grained at the level of Months, Days, Hours, and Minutes.

Detailed explanation on scheduling of pipelines can be found here

Dataset & Name

Dataset Name

Key in the Dataset Name(also serves as the table name in your data warehouse).Keep in mind, that the name should be unique across the account and the data source. Special characters (except underscore _) and blank spaces are not allowed. It is best to follow a consistent naming scheme for future search to locate the tables.

Dataset Description

Enter a short description (optional) describing the dataset being fetched by this particular pipeline.


Choose the events for which you’d like to be notified: whether "ERROR ONLY" or "ERROR AND SUCCESS".

Once you have finished click on Finish to save it. Read more about naming and saving your pipelines including the option to save them as templates here

Still have Questions?

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