Pendo + Bruin

Source

Ingest Pendo 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

Feedback tied to revenue
Join Pendo responses with CRM and billing data. See which customer segments are unhappy, and how much revenue is at risk.
NPS/CSAT trends, automated
Pendo response data flows into your warehouse. Trend dashboards update automatically, no manual exports.
Response quality validation
Quality checks catch duplicate submissions, incomplete responses, and stale data before it reaches your reports.
Cross-source customer insight
Combine Pendo feedback with support tickets, product usage, and sales data for a complete customer picture.

For data & engineering teams

How it works

Response deduplication
Bruin's merge strategy prevents duplicate Pendo responses. Re-runs and retries are always safe.
YAML-defined, Git-versioned
Your Pendo pipeline is a YAML file. Review in PRs, deploy with CI/CD, roll back with git revert.
Completeness validation
Quality checks catch incomplete responses, missing timestamps, and null IDs on every sync.
Transform responses in SQL
Calculate NPS, CSAT, and sentiment metrics with SQL transforms, in the same pipeline as ingestion.

Before you start

Pendo account with API access

Integration key from Pendo settings

Step 1

Add your Pendo connection

Connect using integration key authentication. Add this to your Bruin environment file, credentials are stored securely and referenced by name in your pipeline YAML.

Parameters

integration_keyPendo integration key for authentication

connections:
  pendo:
    type: pendo
    uri: "pendo://?integration_key=<key>"

Step 2

Create your pipeline

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

Available tables

visitorsaccountseventsguidespolls

name: raw.pendo_visitors
type: ingestr

parameters:
  source_connection: pendo
  source_table: 'visitors'
  destination: bigquery

Step 3

Add quality checks

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

Catch duplicate survey responses

Validate submission timestamps are recent

Ensure response IDs are unique across syncs

columns:
  - name: response_id
    checks:
      - name: not_null
      - name: unique
  - name: submitted_at
    checks:
      - name: not_null

custom_checks:
  - name: responses are recent
    query: |
      SELECT MAX(submitted_at) >
        TIMESTAMP_SUB(CURRENT_TIMESTAMP(), INTERVAL 7 DAY)
      FROM raw.pendo_visitors

Step 4

Run it

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

$ bruin run .

Running pipeline...

  pendo_visitors
    ✓ 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

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Ready to connect Pendo?

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