AdRoll (v20-07-2020)
Last updated: 9/15/2026This integration is certified by Stitch. For support, contact Support.
AdRoll integration summary
Stitch’s AdRoll integration replicates data using the AdRoll CRUD API. Refer to the Schema section for a list of objects available for replication.
AdRoll feature snapshot
A high-level look at Stitch's AdRoll (v20-07-2017) integration, including release status, useful links, and the features supported in Stitch.
| STITCH | |||
| Release status |
Deprecated on July 24, 2020 |
Supported by
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Stitch plan
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Standard |
API availability
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Not available
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| Singer GitHub repository |
Not applicable |
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| REPLICATION SETTINGS | |||
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Anchor Scheduling
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Unsupported
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Advanced Scheduling
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Unsupported
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Table-level reset
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Unsupported
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Configurable Replication Methods
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Unsupported
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| DATA SELECTION | |||
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Table selection
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Unsupported
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Column selection
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Unsupported
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Select all
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Unsupported
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| TRANSPARENCY | |||
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Extraction Logs
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Unsupported
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Loading Reports
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Supported
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Connecting AdRoll
Step 1: Create an AdRoll User for Stitch
While you can use your own credentials to connect AdRoll to Stitch, we recommend creating a separate user for us. This will make it easier for you to manage users and audit events in your AdRoll account.
We require a General User role - which is the default - to be able to replicate your AdRoll data. Note that Stitch does not need billing access. If you need help creating an AdRoll user, you can find instructions here in AdRoll’s support docs.
Step 2: Add AdRoll as a Stitch data source
- Sign into your Stitch account.
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On the Stitch Dashboard page, click the Add Integration button.
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Click the AdRoll icon.
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Enter a name for the integration. This is the name that will display on the Stitch Dashboard for the integration; it’ll also be used to create the schema in your destination.
For example, the name “Stitch AdRoll” would create a schema called
stitch_adrollin the destination. Note: Schema names cannot be changed after you save the integration. - Enter the email address and username for the Stitch AdRoll user.
Step 3: Define the historical replication start date
The Sync Historical Data setting defines the starting date for your AdRoll integration. This means that:
- For tables using Key-based Incremental Replication, data equal to or newer than this date will be replicated to your destination.
- For tables using Full Table Replication, all data - including records that are older, equal to, or newer than this date - will be replicated to your destination.
Change this setting if you want to replicate data beyond AdRoll’s default setting of 1 year. For a detailed look at historical replication jobs, check out the Syncing Historical SaaS Data guide.
Step 4: Create a replication schedule
In the Replication Frequency section, you’ll create the integration’s replication schedule. An integration’s replication schedule determines how often Stitch runs a replication job, and the time that job begins.
AdRoll integrations support the following replication scheduling methods:
To keep your row usage low, consider setting the integration to replicate less frequently. See the Understanding and Reducing Your Row Usage guide for tips on reducing your usage.
Initial and historical replication jobs
After you finish setting up AdRoll, its Sync Status may show as Pending on either the Stitch Dashboard or in the Integration Details page.
For a new integration, a Pending status indicates that Stitch is in the process of scheduling the initial replication job for the integration. This may take some time to complete.
Initial replication jobs with Anchor Scheduling
If using Anchor Scheduling, an initial replication job may not kick off immediately. This depends on the selected Replication Frequency and Anchor Time. Refer to the Anchor Scheduling documentation for more information.
Free historical data loads
The first seven days of replication, beginning when data is first replicated, are free. Rows replicated from the new integration during this time won’t count towards your quota. Stitch offers this as a way of testing new integrations, measuring usage, and ensuring historical data volumes don’t quickly consume your quota.
AdRoll table reference
Schemas and versioning
Schemas and naming conventions can change from version to version, so we recommend verifying your integration’s version before continuing.
The schema and info displayed below is for version 20-07-2017 of this integration.