All integrations
Zoho CRM
+
Bruin

Zoho CRM + Bruin

Source

Ingest Zoho CRM data into your warehouse with incremental loading, quality checks, and full lineage. Defined in YAML, version-controlled in Git.

For business teams

What you get

  • Sales analytics beyond the CRM

    Join Zoho CRM pipeline data with marketing spend and product usage. Know which campaigns actually drive revenue.

  • Clean contact data

    Quality checks deduplicate contacts, catch missing emails, and validate pipeline stages on every sync.

  • Revenue forecasting you trust

    Feed clean Zoho CRM data into forecasting models. Bad CRM data makes bad forecasts — Bruin catches issues first.

  • Marketing attribution that works

    Connect Zoho CRM closed-won deals back to ad spend and campaigns. Finance gets numbers they can actually trust.

For data & engineering teams

How it works

  • Deduplication built in

    Bruin handles incremental loading with merge strategy. Contacts and deals are deduplicated automatically on every sync.

  • YAML-defined, Git-versioned

    Your Zoho CRM pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.

  • Custom SQL quality checks

    Validate pipeline stage values, check for orphaned deals, and enforce referential integrity with custom SQL.

  • End-to-end lineage

    Trace Zoho CRM data from ingestion through every transform to final dashboards. Know what breaks when schemas change.

Before you start

Zoho CRM account with API access
Self-client or server-based OAuth app
Refresh token with required scopes

Step 1

Add your Zoho CRM connection

Connect using Zoho CRM OAuth credentials. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

  • client_idZoho API client ID
  • client_secretZoho API client secret
  • refresh_tokenOAuth refresh token
connections:
  zoho_crm:
    type: zoho-crm
    uri: "zoho-crm://client_id:client_secret@organization_id?refresh_token=token"

Step 2

Create your pipeline

Define a YAML asset that tells Bruin what to pull from Zoho CRM and where to land it. This file lives in your Git repo — reviewable, version-controlled, and deployable with CI/CD.

Available tables

leadscontactsdealsaccountstasksactivities
name: raw.zoho_crm_leads
type: ingestr

parameters:
  source_connection: zoho_crm
  source_table: 'leads'
  destination: bigquery

# Syncs contacts, deals, and activities
# with incremental loading and deduplication.

Step 3

Add quality checks

Validate Zoho CRM data on every sync. Catch orphaned deals, duplicate contacts, and invalid pipeline stages before they corrupt your analytics.

Validate pipeline stage values against accepted list
Catch orphaned deals with no contact attached
Ensure contact emails are never null
columns:
  - name: id
    checks:
      - name: not_null
      - name: unique
  - name: email
    checks:
      - name: not_null
  - name: stage
    checks:
      - name: accepted_values
        value: ['lead', 'qualified', 'proposal', 'closed_won', 'closed_lost']

custom_checks:
  - name: no orphaned deals
    query: |
      SELECT COUNT(*) = 0
      FROM raw.zoho_crm_contacts deals
      LEFT JOIN raw.zoho_crm_leads contacts
        ON deals.contact_id = contacts.id
      WHERE contacts.id IS NULL

Step 4

Run it

One command. Bruin connects to Zoho CRM, pulls data incrementally, runs your quality checks, and lands clean data in your warehouse. If a check fails, the pipeline stops — bad data never reaches downstream.

Backfill historical data with --start-date
Schedule with cron or trigger from CI/CD
Full lineage from Zoho CRM to your dashboards
$ bruin run .
Running pipeline...

  zoho_crm_leads
    ✓ Fetched 2,847 new records
    ✓ Quality: campaign_id not_null     PASSED
    ✓ Quality: spend not_null           PASSED
    ✓ Quality: no negative ad spend     PASSED
    ✓ Loaded into bigquery

  Completed in 12s

Other CRM & Sales integrations

Ready to connect Zoho CRM?

Start for free, or book a demo to see how Bruin handles ingestion, quality, lineage, and scheduling for your entire data stack.