06:00 UTC
Comment Sold
Selected accounts
Configured job
BigQuery
Destination table
Join marketing, finance, CRM, and product data inside the same warehouse.
Metrics availables
Dimensions availables
Comment Sold
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 CommentSold as a source in Catchr, enter your CommentSold API token and Shop ID, choose BigQuery as the destination, select your fields, and authorize the target Google Cloud project and dataset.
Export customer and order data, including payment amounts, subtotals, taxes, shipping costs, coupon discounts, final totals, unique customer counts, dates, and shipping locations.
Yes. Available dimensions include customer email and street address, plus recipient name, email, phone number, city, state, ZIP code, country code, and other shipping address fields.
Yes. Keep each source in separate tables, then use SQL views or models to combine CommentSold orders and customers with other data through shared fields such as date, customer, or region.
Build order and customer reporting that compares paid amounts, discounts, taxes, shipping costs, final totals, unique customers, and geographic patterns without relying on manual exports.
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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