Connect Mailjet Mail to BigQuery
Send Mailjet Mail contacts, campaigns, contacts lists and 3 more data types to BigQuery on a schedule. Refresh as often as every 15 minutes.
BigQuery
dataset mailjet_mail
contactscampaignscontacts_listsstats_api_lifetime_messagesmessages- 1 more data type
How to connect Mailjet Mail and BigQuery
4 steps. You can preview the Mailjet Mail data in Coupler.io before anything reaches BigQuery.
Step 1 of 4
Connect Mailjet Mail
Enter your Mailjet Mail API key and API secret key. You only do this once per account.
Step 2 of 4
Choose what to export
Pick the Mailjet Mail 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 Mailjet Mail 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 contacts with fresh Mailjet Mail data.
Coupler.io made it easy to create dashboards and reports from different data sources. The sync is reliable and the user experience is amazing.
Take your data analytics to the next level
Sign Up with Google
Sign Up with MICROSOFT
SIGN UP WITH EMAIL
By signing up to Coupler.io, you agree to our Privacy Policy and Terms of Use.
Build your Mailjet Mail integrations with these destinations
Get the most of Mailjet Mail to BigQuery integration
Gather data
Understand data
Automate data
Act on data
6 data types, including Contacts, Campaigns, Contacts lists, Stats api lifetime messages and Messages.
With your Mailjet Mail API key and API secret key, 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 Mailjet Mail 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.
