06:00 UTC
Impact.com
Selected accounts
Configured job
BigQuery
Destination table
Join marketing, finance, CRM, and product data inside the same warehouse.
Metrics availables
Dimensions availables
Impact.com
3 advertising accounts
Connected
Google Ads
2 advertising accounts
Connected
Google Analytics 4
1 web property
Connected
HubSpot
1 CRM portal
Connected
Select your Google Cloud project and BigQuery dataset. Catchr automatically prepares the destination and maps your data into analytics-ready tables.
Catchr continuously imports new and updated data into BigQuery.
Your warehouse stays fresh automatically, ready for SQL, dbt, BI tools, and AI workloads.
Open the dedicated route for each platform. Its field catalog, reporting grain, historical constraints, and warehouse use cases should be specific to that source.
Answers about available Meta Ads data, reporting cadence, history, table settings, attribution changes, and downstream joins.
Add impact.com as a source in Catchr using your Account SID and Auth Token, choose Big Query as the destination, select the available fields, and authorize the target Google Cloud project and dataset.
Export available company information, partner, program, and ad data, including program names, marketplace categories, landing-page URLs, ad settings, account identifiers, and timezone details.
You need your impact.com Account SID and Auth Token to authenticate the source, plus permission to authorize the target Google Cloud project and dataset.
Yes. Store each source in separate tables, then use SQL views or models to join compatible records through shared account, program, or other matching identifiers.
Build structured program and ad inventories, review partner and account information, audit settings such as mobile-ready ads or trademark bidding, and prepare source tables for broader agency reporting.
If your selected schema contains an eligible date field, you can configure that field as the optional date partition for the destination table. Catchr does not configure table clustering or design your downstream analytical models.
Yes. Configure the historical period supported by the source for the initial import, then keep the table updated with recurring exports. The available range is determined by the source API and the settings of your job, not an unlimited-history promise.
Our teams is always here to responds to any question you could have about our data connector.
Connect your accounts, choose the fields then send the configured export to your BigQuery project.
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