Apptivo connector
Set up the Apptivo connector in Kaivo: authentication, configuration, the 5 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 Apptivo 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 Apptivo connector
Sync your Apptivo CRM data into BigQuery with Kaivo to report on pipeline, contacts, and cases in one place.
Getting started with the Apptivo connector
- Sign up for Kaivo and create a workspace.
- Connect your Apptivo 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 Apptivo
Authenticate with your Apptivo credentials. You provide:
Tables and columns synced from Apptivo
Kaivo syncs 5 tables from Apptivo into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.
cases (60 columns)
cases (60 columns)
Subtable: cases__address_types
Subtable: cases__app360_objects
Subtable: cases__assignees
Subtable: cases__assignment_levels
Subtable: cases__case_sources
Subtable: cases__collaboration_settings
Subtable: cases__collaboration_settings__activity_action_settings
Subtable: cases__conversions
Subtable: cases__currencies
Subtable: cases__email_templates
Subtable: cases__email_types
Subtable: cases__employees
Subtable: cases__followup_teams
Subtable: cases__labels
Subtable: cases__list_layouts
Subtable: cases__list_layouts__data
Subtable: cases__mobile_views
Subtable: cases__not_responded_teams
Subtable: cases__pdf_templates
Subtable: cases__phone_types
Subtable: cases__priorities
Subtable: cases__privilege_settings
Subtable: cases__privileges
Subtable: cases__privileges__privilege_auto_grants
Subtable: cases__quick_links
Subtable: cases__reference_fields
Subtable: cases__report_groups
Subtable: cases__report_groups__reports
Subtable: cases__report_groups__reports__addresses
Subtable: cases__report_groups__reports__associated_entities
Subtable: cases__report_groups__reports__custom_attributes
Subtable: cases__report_groups__reports__email_addresses
Subtable: cases__report_groups__reports__labels
Subtable: cases__report_groups__reports__phone_numbers
Subtable: cases__report_groups__reports__remove_addresses
Subtable: cases__report_groups__reports__remove_email_addresses
Subtable: cases__report_groups__reports__remove_labels
Subtable: cases__report_groups__reports__remove_phone_numbers
Subtable: cases__report_groups__reports__to_object_ids
Subtable: cases__saved_views
Subtable: cases__slas
Subtable: cases__snap_shots
Subtable: cases__statuses
Subtable: cases__sys_messages
Subtable: cases__teams
Subtable: cases__types
Subtable: cases__user_config__my_views
Subtable: cases__user_config__shared_views
Subtable: cases__view_settings
Subtable: cases__view_settings__bulk_actions
contacts (51 columns)
contacts (51 columns)
Subtable: contacts__accounts
Subtable: contacts__addresses
Subtable: contacts__categories
Subtable: contacts__contact_attributes
Subtable: contacts__custom_attributes
Subtable: contacts__email_addresses
Subtable: contacts__labels
Subtable: contacts__notes
Subtable: contacts__phone_numbers
Subtable: contacts__territories
customers (58 columns)
customers (58 columns)
Subtable: customers__accounts
Subtable: customers__addresses
Subtable: customers__custom_attributes
Subtable: customers__email_addresses
Subtable: customers__labels
Subtable: customers__notes
Subtable: customers__phone_numbers
Subtable: customers__remove_email_addresses
Subtable: customers__remove_phone_numbers
Subtable: customers__territories
Subtable: customers__to_object_ids
leads (43 columns)
leads (43 columns)
Subtable: leads__accounts
Subtable: leads__addresses
Subtable: leads__custom_attributes
Subtable: leads__email_addresses
Subtable: leads__labels
Subtable: leads__notes
Subtable: leads__phone_numbers
Subtable: leads__territories
opportunities (37 columns)
opportunities (37 columns)
Subtable: opportunities__accounts
Subtable: opportunities__addresses
Subtable: opportunities__assignee_managers
Subtable: opportunities__custom_attributes
Subtable: opportunities__email_addresses
Subtable: opportunities__histories
Subtable: opportunities__inquiry_types
Subtable: opportunities__item_list
Subtable: opportunities__items
Subtable: opportunities__labels
Subtable: opportunities__notes
Subtable: opportunities__phone_numbers
Subtable: opportunities__property_list
Subtable: opportunities__remove_labels
Subtable: opportunities__sales_stage_history
Subtable: opportunities__territories
How the Apptivo sync works
After the first load, Kaivo keeps your BigQuery warehouse up to date for you. Where Apptivo 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 Apptivo?
It depends on how much history is in your Apptivo 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 Apptivo'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 Apptivo, 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 Apptivo 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 Apptivo connector in Kaivo and all of its synced data is deleted with it.
Common use cases for Apptivo data
Pipeline reporting
Track opportunities and leads to see pipeline value and conversion over time.
Account view
Join contacts with customers to understand your accounts and where activity sits.
Support analysis
Use cases to measure support volume and resolution alongside your sales data.
Use Apptivo data in your AI and BI tools
Once Apptivo 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 Apptivo 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 Apptivo connector pricing and plan details.
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