06:00 UTC
ChatGPT Ads
Selected accounts
Configured job
Azure SQL
Destination table
Join marketing, finance, CRM, and product data inside the same warehouse.
Metrics availables
Dimensions availables
ChatGPT Ads
3 advertising accounts
Connected
Google Ads
2 advertising accounts
Connected
Google Analytics 4
1 web property
Connected
HubSpot
1 CRM portal
Connected
Enter the Azure SQL server host, database, and login details. Catchr verifies the destination before any marketing data is exported.
Choose the fields, initial history, partition field, and recurring schedule for the job. Catchr refreshes the configured import window in your AzureSQL table.
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 AzureSQL setup, available source data, schedules, table updates, and SQL use cases.
Add your ChatGPT Ads API key from Ads Manager, save your Azure SQL connection details, and pair both in a Catchr datastream. You can then select the reporting fields and load them into an Azure SQL table.
You can select metrics such as spend, impressions, clicks, conversions, CTR, CPC, and CPM alongside account, campaign, ad group, ad, budget, and currency dimensions. Rename and preview the selected columns before writing them to Azure SQL.
Yes, you can configure a ChatGPT Ads job to load available historical data and continue on a recurring schedule. The accessible history and scheduling options depend on the source API and your Catchr plan.
Choose a valid date field when configuring the ChatGPT Ads job. Catchr deletes and rewrites the scheduled date window in Azure SQL to limit duplicate rows across overlapping loads.
Azure SQL queries can summarize spend, impressions, clicks, conversions, CTR, CPC, and CPM by campaign, ad group, or ad. Agencies can turn these results into reusable views for client dashboards and cross-channel reporting.
Yes. Connect an existing Azure SQL 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.
Our teams is always here to responds to any question you could have about our data connector.
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