OnePageCRM connector
Set up the OnePageCRM connector in Kaivo: authentication, configuration, the 19 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 OnePageCRM 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 CRM data instead of moving it.
What is the OnePageCRM connector
Sync your OnePageCRM data into BigQuery with Kaivo to report on pipeline, contacts, and activity in one place.
Getting started with the OnePageCRM connector
- Sign up for Kaivo and create a workspace.
- Connect your OnePageCRM 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 OnePageCRM
Authenticate with your API Key.
Configuring the OnePageCRM connector
When you set up the connector, you provide:
Tables and columns synced from OnePageCRM
Kaivo syncs 19 tables from OnePageCRM into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
action_stream (26 columns)
action_stream (26 columns)
Subtable: action_stream__address_list
Subtable: action_stream__closed_sales
Subtable: action_stream__custom_fields
Subtable: action_stream__emails
Subtable: action_stream__phones
Subtable: action_stream__sales_closed_for
Subtable: action_stream__tags
Subtable: action_stream__urls
actions (12 columns)
actions (12 columns)
bootstrap (55 columns)
bootstrap (55 columns)
Subtable: bootstrap__call_results_order
Subtable: bootstrap__company_fields
Subtable: bootstrap__custom_fields
Subtable: bootstrap__deal_fields
Subtable: bootstrap__filters
Subtable: bootstrap__filters__filter__conditions
Subtable: bootstrap__filters__filter__conditions__list
Subtable: bootstrap__next_action_dates
Subtable: bootstrap__predefined_action_groups
Subtable: bootstrap__predefined_actions
Subtable: bootstrap__reason_losts
Subtable: bootstrap__settings__deal_stages
Subtable: bootstrap__settings__pipelines
Subtable: bootstrap__settings__pipelines__pipeline__stages
Subtable: bootstrap__settings__popular_countries
Subtable: bootstrap__team
Subtable: bootstrap__user__user__account_rights
Subtable: bootstrap__virtual_groups
calls (14 columns)
calls (14 columns)
Subtable: calls__attachments
companies (16 columns)
companies (16 columns)
Subtable: companies__company_fields
Subtable: companies__contacts
Subtable: companies__contacts__contact__address_list
Subtable: companies__contacts__contact__closed_sales
Subtable: companies__contacts__contact__custom_fields
Subtable: companies__contacts__contact__emails
Subtable: companies__contacts__contact__phones
Subtable: companies__contacts__contact__sales_closed_for
Subtable: companies__contacts__contact__tags
Subtable: companies__contacts__contact__urls
Subtable: companies__contacts__next_action_conflicts
Subtable: companies__contacts__next_actions
Subtable: companies__contacts__queued_actions
Subtable: companies__pending_deals
Subtable: companies__pending_deals__deal__attachments
Subtable: companies__pending_deals__deal__deal_fields
Subtable: companies__pending_deals__deal__deal_items
contacts (26 columns)
contacts (26 columns)
Subtable: contacts__address_list
Subtable: contacts__closed_sales
Subtable: contacts__custom_fields
Subtable: contacts__emails
Subtable: contacts__phones
Subtable: contacts__sales_closed_for
Subtable: contacts__tags
Subtable: contacts__urls
custom_fields (8 columns)
custom_fields (8 columns)
deals (34 columns)
deals (34 columns)
Subtable: deals__attachments
Subtable: deals__deal_fields
Subtable: deals__deal_items
filters (4 columns)
filters (4 columns)
Subtable: filters__conditions
Subtable: filters__conditions__list
lead_sources (7 columns)
lead_sources (7 columns)
Subtable: lead_sources__team_counts
meetings (11 columns)
meetings (11 columns)
Subtable: meetings__attachments
notes (11 columns)
notes (11 columns)
Subtable: notes__attachments
pipelines (7 columns)
pipelines (7 columns)
Subtable: pipelines__stages
predefined_actions (7 columns)
predefined_actions (7 columns)
predefined_items (8 columns)
predefined_items (8 columns)
relationship_types (6 columns)
relationship_types (6 columns)
Subtable: relationship_types__relationship_variants
statuses (10 columns)
statuses (10 columns)
Subtable: statuses__team_counts
team_stream (26 columns)
team_stream (26 columns)
Subtable: team_stream__address_list
Subtable: team_stream__closed_sales
Subtable: team_stream__custom_fields
Subtable: team_stream__emails
Subtable: team_stream__phones
Subtable: team_stream__sales_closed_for
Subtable: team_stream__tags
Subtable: team_stream__urls
users (12 columns)
users (12 columns)
Subtable: users__account_rights
How the OnePageCRM sync works
After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where OnePageCRM 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 OnePageCRM?
It depends on how much history is in your OnePageCRM 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 OnePageCRM'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 OnePageCRM, 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 OnePageCRM 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 OnePageCRM connector in Kaivo and all of its synced data is deleted with it.
Common use cases for OnePageCRM data
Pipeline reporting
Use deals and pipelines to track pipeline value and movement over time.
Account view
Join contacts with companies to understand your accounts.
Activity tracking
Use actions and action_stream to measure follow-up across the team.
Use OnePageCRM data in your AI and BI tools
Once OnePageCRM 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 OnePageCRM 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 OnePageCRM connector pricing and plan details.
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