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Outbrain DSP
Selected accounts
Configured job
Snowflake
Destination table
Join marketing, finance, CRM, and product data inside the same warehouse.
Metrics availables
Dimensions availables
Outbrain DSP
3 advertising accounts
Connected
Google Ads
2 advertising accounts
Connected
Google Analytics 4
1 web property
Connected
HubSpot
1 CRM portal
Connected
Add the account host, user, and database schema. Use a password for compatible users or a PEM private key for service accounts and stricter policies.
Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your PostgreSQL table.
This example summarizes spend, impressions, clicks, and click-through rate by campaign.
Each connector has its own entities, fields, historical limits, and reporting uses. Open a source page for the details that belong to that platform.
Answers about PostgreSQL setup, available source data, schedules, table updates, and SQL use cases.
Add Outbrain DSP in Sources and connect the existing Snowflake database in Storage. A datastream defines the route, while the job loads the chosen fields into "ad groups".
Select concrete Outbrain DSP fields such as Account Status, Ad Group Status, Avg. Cost per Minute, and Day of the month. You can rename the chosen columns, preview the result, and write them to Snowflake tables such as accounts, advertisers, and campaigns.
Define the first Outbrain DSP fetch, run frequency, and lookback window in the "ad groups" job. Each scheduled run replaces data inside the configured period.
Use a supported date field to partition "ad groups". Recurring Outbrain DSP runs can then update the selected window instead of adding another copy of the same period.
With Outbrain DSP data, a Snowflake query can summarize spend, impressions, clicks, and click-through rate by campaign. Model Account Status and Ad Group Status in SQL, then expose the result to dashboards, internal tools, or recurring client reports.
Yes. Connect an existing Snowflake database first. The Catchr job creates and populates the destination table you configure inside that database.
Yes. Create a separate datastream and job for each source, write each export to its own table, then combine the data downstream with SQL, views, or your BI tool.
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