06:00 UTC
Google Trends
Selected accounts
Configured job
BigQuery
Destination table
Join marketing, finance, CRM, and product data inside the same warehouse.
Metrics availables
Dimensions availables
Google Trends
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 Google Trends as a source in Catchr, choose BigQuery as the destination, select the fields to export, and authorize the target Google Cloud project and dataset.
Export sites, pages, queries, keywords, clicks, impressions, position, countries, devices, sitemaps, and other available organic search fields.
Schedule recurring refreshes in Catchr so your BigQuery tables stay updated automatically. Available frequencies depend on your plan, source limits, and reporting needs.
Yes. Keep sources in separate tables, then use SQL views or models to join them on shared dimensions such as date, campaign, account, customer, product, or region.
Build SEO dashboards, query and landing-page analysis, ranking trends, technical monitoring, and joined search performance datasets.
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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