Connect CallRail to BigQuery
Send CallRail companies, users, calls and 1 more data type to BigQuery on a schedule. Filter by date. Refresh as often as every 15 minutes.
BigQuery
dataset callrail
companiesuserscallsconversations
How to connect CallRail and BigQuery
4 steps. You can preview the CallRail data in Coupler.io before anything reaches BigQuery.
Step 1 of 4
Connect CallRail
Enter your CallRail API key and account ID. You only do this once per account.
Step 2 of 4
Choose what to export
Pick the CallRail data you want in BigQuery.
Step 3 of 4
Connect BigQuery
Upload the JSON key file from your Google Cloud service account, then enter the dataset and table for the CallRail data.
Step 4 of 4
Choose a write mode and schedule
Every run either replaces or appends the data in BigQuery. Run it as often as every 15 minutes.
Each run overwrites companies with fresh CallRail data.
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4 data types, including Companies, Users, Calls and Conversations.
With your CallRail API key and account ID, entered once when you add the connection.
Yes. Set the start date to cover the period you need.
Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with CallRail data.
Refresh the source field list in Coupler.io and select the new column. If you define the BigQuery table schema manually, add the column there too.
On a schedule you choose, from monthly down to every 15 minutes, depending on your Coupler.io plan.
Yes. Add more sources to the same data flow, for example Pipedrive or Calendly, and join or append them before the data reaches BigQuery.
