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Leadfeeder connector

Set up the Leadfeeder connector in Kaivo: authentication, configuration, the 3 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 Leadfeeder 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 Leadfeeder connector

Sync your Leadfeeder (Dealfront) website visitor data into BigQuery with Kaivo to see which companies visit your site and turn traffic into leads.

CategoryMarketing & Sales
AuthenticationAPI key
SetupSelf-service

Getting started with the Leadfeeder connector

  1. Sign up for Kaivo and create a workspace.
  2. Connect your Leadfeeder account.
  3. Choose which tables to sync.
  4. Wait for the initial sync to finish.
  5. Query your data in BigQuery or your favourite AI or BI tool.

Authenticating Leadfeeder

Authenticate with your API Token.

FieldDescription
API Token

Your Leadfeeder (Dealfront) API token. Create one under Settings > API keys > Create a new API key (it's shown only once, so copy it right away).

Configuring the Leadfeeder connector

When you set up the connector, you provide:

FieldDescription
Start Date

Tables and columns synced from Leadfeeder

Kaivo syncs 3 tables from Leadfeeder into a dedicated dataset in your BigQuery warehouse. Click any table to see its columns and types.

ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
typeSTRING
attributes__nameSTRING
attributes__on_trialBOOL
attributes__subscriptionSTRING
attributes__timezoneSTRING
idSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: accounts__attributes__subscription_addons

ColumnTypeDescription
_kaivo_parent_idSTRINGForeign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
valueJSON
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
typeSTRING
account_idSTRING
attributes__business_idSTRING
attributes__crm_organization_idSTRING
attributes__employee_countFLOAT64
attributes__employees_range__maxFLOAT64
attributes__employees_range__minFLOAT64
attributes__facebook_urlSTRING
attributes__first_visit_dateSTRING
attributes__industrySTRING
attributes__last_visit_dateSTRING
attributes__linkedin_urlSTRING
attributes__logo_urlSTRING
attributes__nameSTRING
attributes__phoneSTRING
attributes__qualityFLOAT64
attributes__revenueSTRING
attributes__statusSTRING
attributes__twitter_handleSTRING
attributes__view_in_leadfeederSTRING
attributes__visitsFLOAT64
attributes__website_urlSTRING
idSTRING
last_visit_dateSTRING
relationships__location__data__typeSTRING
relationships__location__data__idSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: leads__attributes__tags

ColumnTypeDescription
_kaivo_parent_idSTRINGForeign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
valueSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.
ColumnTypeDescription
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
typeSTRING
account_idSTRING
attributes__campaignSTRING
attributes__country_codeSTRING
attributes__dateSTRING
attributes__device_typeSTRING
attributes__hourFLOAT64
attributes__keywordSTRING
attributes__lead_idSTRING
attributes__lf_client_idSTRING
attributes__mediumSTRING
attributes__page_depthFLOAT64
attributes__referring_urlSTRING
attributes__sourceSTRING
attributes__started_atSTRING
attributes__visit_lengthFLOAT64
idSTRING
relationships__location__data__typeSTRING
relationships__location__data__idSTRING
started_atSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: visits__attributes__ga_client_ids

ColumnTypeDescription
_kaivo_parent_idSTRINGForeign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
valueSTRING
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

Subtable: visits__attributes__visit_route

ColumnTypeDescription
_kaivo_parent_idSTRINGForeign key referencing _kaivo_id in the parent table. Auto-generated by Kaivo.
_kaivo_idSTRINGPrimary key that uniquely identifies the row. Auto-generated by Kaivo.
display_page_nameSTRING
hostnameSTRING
page_pathSTRING
page_titleSTRING
page_urlSTRING
previous_page_pathSTRING
time_on_pageFLOAT64
_kaivo_extracted_atTIMESTAMPTimestamp that shows when the row was extracted. Auto-generated by Kaivo.

How the Leadfeeder sync works

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

It depends on how much history is in your Leadfeeder 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 Leadfeeder'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 Leadfeeder, 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 Leadfeeder 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 Leadfeeder connector in Kaivo and all of its synced data is deleted with it.

Common use cases for Leadfeeder data

Visitor identification

Use accounts and visits to see which companies browse your site.

Lead generation

Join leads with visits to prioritise the accounts showing the most interest.

Marketing context

Combine visitor data with your campaign data to see which channels bring high-intent companies.

Use Leadfeeder data in your AI and BI tools

Once Leadfeeder 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 Leadfeeder 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 Leadfeeder connector pricing and plan details.

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