Connect Reply.io to BigQuery
Send Reply.io campaigns, email accounts, people and 1 more data type to BigQuery on a schedule. Refresh as often as every 15 minutes.
BigQuery
dataset reply_io
campaignsemail_accountspeopletemplates
How to connect Reply.io and BigQuery
4 steps. You can preview the Reply.io data in Coupler.io before anything reaches BigQuery.
Step 1 of 4
Connect Reply.io
Enter your Reply.io API token. You only do this once per account.
Step 2 of 4
Choose what to export
Pick the Reply.io 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 Reply.io 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 campaigns with fresh Reply.io data.
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Build your Reply.io integrations with these destinations
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4 data types, including Campaigns, Email accounts, People and Templates.
With your Reply.io API token, entered once when you add the connection.
Yes. If the table doesn't exist in the dataset you choose, Coupler.io creates it on the first run and fills it with Reply.io 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 Calendly or Klaviyo, and join or append them before the data reaches BigQuery.
