Gorgias + Bruin

Source

Ingest Gorgias 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

Support data meets revenue data
Join Gorgias tickets with billing and product usage. Build customer health scores that predict churn before it happens.
SLA monitoring, automated
Gorgias response times and resolution metrics are quality-checked on every sync. Know when SLAs are at risk before customers escalate.
Support ROI in business terms
Connect Gorgias agent performance to revenue outcomes. Show leadership the business impact of support quality.
No more ticket export Fridays
Gorgias data syncs automatically. Reports are fresh every morning without manual pulls.

For data & engineering teams

How it works

Incremental ticket sync
Only sync new and updated Gorgias tickets. No full reloads, even for high-volume support queues.
YAML-defined, Git-versioned
Your Gorgias pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.
SLA validation in SQL
Custom quality checks validate response times and resolution SLAs. Pipeline alerts when thresholds are breached.
Cross-source customer view
Join Gorgias tickets with CRM and billing data in SQL transforms. Bruin resolves dependencies automatically.

Before you start

Gorgias account with data

API key generated from settings

Appropriate user permissions

Understanding of rate limits

Step 1

Add your Gorgias connection

Gorgias API connection using API key. Add this to your Bruin environment file — credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

api_keyGorgias API key
domainYour Gorgias subdomain

connections:
  gorgias:
    type: gorgias
    uri: "gorgias://[email protected]"

Step 2

Create your pipeline

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

Available tables

ticketsmessagescustomerssatisfaction_surveys

name: raw.gorgias_tickets
type: ingestr

parameters:
  source_connection: gorgias
  source_table: 'tickets'
  destination: bigquery

Step 3

Add quality checks

Add column-level and custom SQL checks to your Gorgias data. If a check fails, the pipeline stops — bad data never reaches downstream models or dashboards.

Validate ticket statuses against accepted values

Catch open tickets with no assignee

Ensure ticket IDs are unique — no duplicates

columns:
  - name: ticket_id
    checks:
      - name: not_null
      - name: unique
  - name: status
    checks:
      - name: accepted_values
        value: ['open', 'pending', 'resolved', 'closed']

custom_checks:
  - name: no tickets missing assignee
    query: |
      SELECT COUNT(*) = 0
      FROM raw.gorgias_tickets
      WHERE status = 'open' AND assignee_id IS NULL

Step 4

Run it

One command. Bruin connects to Gorgias, 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 Gorgias to your dashboards

$ bruin run .

Running pipeline...

  gorgias_tickets
    ✓ 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 Customer Support integrations

Crisp

Delighted

Dixa

Freshdesk

Freshservice

Front

Ready to connect Gorgias?

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

Book a demo Read the docs