BigMailer connector
Set up the BigMailer connector in Kaivo: authentication, configuration, the 10 BigQuery tables it syncs, and answers to common questions.
Written By Lauri Raivio
Last updated 16 days ago
Kaivo is a fully managed data platform that syncs your BigMailer data into a Google BigQuery warehouse and keeps it up to date automatically. There is no pipeline to build and no infrastructure to run, so you can spend your time analysing your marketing and sales data instead of moving it.
What is the BigMailer connector
Sync your BigMailer email data into BigQuery with Kaivo to track campaigns, lists, and audience growth in one place.
Getting started with the BigMailer connector
- Sign up for Kaivo and create a workspace.
- Connect your BigMailer account.
- Choose which tables to sync.
- Wait for the initial sync to finish.
- Query your data in BigQuery or your favourite AI or BI tool.
Authenticating BigMailer
Authenticate with your API Key.
Tables and columns synced from BigMailer
Kaivo syncs 10 tables from BigMailer into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
brands (10 columns)
brands (10 columns)
bulk_campaigns (23 columns)
bulk_campaigns (23 columns)
contacts (10 columns)
contacts (10 columns)
Subtable: contacts__field_values
Subtable: contacts__list_ids
Subtable: contacts__unsubscribe_ids
fields (7 columns)
fields (7 columns)
lists (6 columns)
lists (6 columns)
message-types (6 columns)
message-types (6 columns)
segments (5 columns)
segments (5 columns)
suppression_lists (6 columns)
suppression_lists (6 columns)
transactional_campaigns (21 columns)
transactional_campaigns (21 columns)
users (8 columns)
users (8 columns)
How the BigMailer sync works
After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where BigMailer supports it, each sync pulls only new and changed records so it stays fast; otherwise it refreshes the whole table. Every record keeps its original ID, so you won't get duplicate rows.
Frequently asked questions
How long does the initial sync take for BigMailer?
It depends on how much history is in your BigMailer account. Most initial syncs finish within minutes, while large accounts can take a few hours. After that, syncs only fetch new and changed records, so they're much faster.
Can I sync only some tables or columns?
Yes. You pick which tables to sync when you set up the connection and can change the selection later. Tables you don't select are never copied to your warehouse.
What happens when BigMailer's schema changes?
New fields are never added automatically. You choose which fields to sync, so data you haven't selected (sensitive personal data, for example) never lands in your warehouse. When a new field appears, it becomes available for you to add. What happens to removed or renamed fields depends on a table's sync mode: full-refresh tables always match what's currently in BigMailer, so dropped fields disappear, while incremental tables keep their existing columns and history, so an old field stays and newly added fields fill in over time.
How do I handle GDPR or data deletion requests?
Your data lives in your own Kaivo-managed BigQuery warehouse, so the most direct option is to delete or anonymise specific records right in BigQuery. If you delete data in BigMailer instead, full-refresh tables drop it on the next sync, while incremental tables keep it, so you would remove the row in BigQuery or ask us to run a full refresh. To remove everything, delete the BigMailer connector in Kaivo and all of its synced data is deleted with it.
Common use cases for BigMailer data
Campaign performance
Use bulk_campaigns and transactional_campaigns to compare email results over time.
List and segment growth
Track lists and segments to see how your audience grows and engages.
Deliverability
Use suppression_lists to monitor bounces and unsubscribes across brands.
Multi-brand view
Use brands to compare email performance across the brands you manage.
Use BigMailer data in your AI and BI tools
Once BigMailer data lands in your Kaivo-managed BigQuery warehouse, you can explore it with AI tools or any BI tool that connects to BigQuery. Here's how the most common destinations work with BigMailer data.
Claude
Use Kaivo's MCP server to give Claude secure, workspace-scoped access to your data. Setup guide →
Power BI
Microsoft's BI tool with a native BigQuery connector. Supports direct query and scheduled refresh. Setup guide →
Data Studio
Free Google BI tool with native BigQuery support. One-click connection to your Kaivo warehouse; great for SMB teams on Google Workspace. Setup guide →
Tableau
The premium analytics standard, with native BigQuery integration. Setup guide →
Google Sheets
Use Connected Sheets to query BigQuery directly from a spreadsheet, with no SQL. Setup guide →
Excel
Connect via Power Query's BigQuery connector. Setup guide →
Metabase
Open-source BI tool with strong BigQuery support. Setup guide →
See our pricing page for BigMailer connector pricing and plan details.
Related connectors
- Google Ads: Sync Google Ads to BigQuery.
- Gmail: Sync Gmail to BigQuery.
- Custobar: Sync Custobar to BigQuery.
- Google Search Console: Sync Google Search Console to BigQuery.
- HubSpot: Sync HubSpot to BigQuery.
- Adform: Sync Adform to BigQuery.
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