Smaily connector

Set up the Smaily connector in Kaivo: authentication, configuration, the 6 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 Smaily 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 survey and email data instead of moving it.

What is the Smaily connector

Sync your Smaily email data into BigQuery with Kaivo to measure campaigns and audience growth in one place.

Category	Surveys & Email
Authentication	Username and password
Setup	Self-service

Getting started with the Smaily connector

Sign up for Kaivo and create a workspace.
Connect your Smaily 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 Smaily

Connect with your Smaily login. You provide:

Field	Description
API User Password	Password for your Smaily API user. See the Smaily docs for how to create an API user.

Configuring the Smaily connector

When you set up the connector, you provide:

Field	Description
API Subdomain	Your Smaily account subdomain (the part before `.sendsmaily.net`). See the Smaily docs for where to find this.
API User Username	Username for your Smaily API user. See the Smaily docs for how to create an API user.

Tables and columns synced from Smaily

Kaivo syncs 6 tables from Smaily into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

ab_tests (7 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`completed_at`	`STRING`
`created_at`	`STRING`
`id`	`INT64`
`name`	`STRING`
`status`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: ab_tests__sections

Column	Type	Description
`_kaivo_parent_id`	`STRING`	Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`id`	`INT64`
`subject`	`STRING`
`template__id`	`INT64`
`template__name`	`STRING`
`template__preview_url`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: ab_tests__tags

Column	Type	Description
`_kaivo_parent_id`	`STRING`	Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`value`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

automations (4 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`id`	`STRING`
`name`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: automations__sections

Column	Type	Description
`_kaivo_parent_id`	`STRING`	Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`id`	`INT64`
`subject`	`STRING`
`template__id`	`INT64`
`template__name`	`STRING`
`template__preview_url`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

campaigns (10 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`completed_at`	`STRING`
`created_at`	`STRING`
`id`	`STRING`
`name`	`STRING`
`status`	`STRING`
`template__id`	`STRING`
`template__name`	`STRING`
`template__preview_url`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: campaigns__tags

Column	Type	Description
`_kaivo_parent_id`	`STRING`	Foreign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`value`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

segments (5 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`id`	`STRING`
`name`	`STRING`
`subscribers_count`	`INT64`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

templates (8 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`type`	`STRING`
`created_at`	`STRING`
`id`	`INT64`
`modified_at`	`STRING`
`name`	`STRING`
`preview_url`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

users (9 columns)

Column	Type	Description
`_kaivo_id`	`STRING`	Primary key that uniquely identifies the row. Auto-generated by Kaivo.
`email`	`STRING`
`first_name`	`STRING`
`id`	`INT64`
`is_owner`	`BOOL`
`last_name`	`STRING`
`role__id`	`INT64`
`role__name`	`STRING`
`_kaivo_extracted_at`	`TIMESTAMP`	Timestamp that shows when the row was extracted. Auto-generated by Kaivo.

How the Smaily sync works

After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Smaily 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 Smaily?

It depends on how much history is in your Smaily 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 Smaily'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 Smaily, 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.

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 Smaily 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 Smaily connector in Kaivo and all of its synced data is deleted with it.

Common use cases for Smaily data

Campaign performance

Use campaigns to track sends and engagement over time.

Audience growth

Use users and segments to see how your audience grows and engages.

Automation reporting

Use automations to see how automated flows perform.

Use Smaily data in your AI and BI tools

Once Smaily 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 Smaily 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 Smaily connector pricing and plan details.

Gmail: Sync Gmail to BigQuery.
Iterable: Sync Iterable to BigQuery.
Klaviyo: Sync Klaviyo to BigQuery.
Mailchimp: Sync Mailchimp to BigQuery.
Twilio SendGrid: Sync Twilio SendGrid to BigQuery.
Surveypal: Sync Surveypal to BigQuery.

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