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Join marketing, finance, CRM, and product data inside the same warehouse.
Metrics availables
Dimensions availables
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.
This example summarizes spend, impressions, clicks, and click-through rate by campaign.
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.
Connect Apple Search Ads as a Catchr source. Add your existing Azure SQL database, create a datastream, and configure a job that writes the selected fields to the "campaigns" table.
Select concrete Apple Search Ads fields such as Average Cost Per Acquisition Amount, Average Cost Per Acquisition Currency, Average CPM Amount, and Day of the month. You can rename the chosen columns, preview the result, and write them to Azure SQL tables such as accounts, advertisers, and campaigns.
Catchr first processes the historical range configured for Apple Search Ads. Later runs update the "campaigns" table using the saved frequency and rolling import window.
Catchr uses the selected partition field to refresh the relevant Apple Search Ads period inside "campaigns". Leaving it blank changes the job to append-only behavior.
With Apple Search Ads data, an Azure SQL query can summarize spend, impressions, clicks, and click-through rate by campaign. A Azure SQL view comparing Average Cost Per Acquisition Amount and Average Cost Per Acquisition Currency can feed agency dashboards or downstream BI models.
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.