This article provides a complete, practical walkthrough of the Code Postgres Update Scheduled n8n agent. It connects HTTP Request, Webhook across approximately 1 node(s). Expect a Intermediate setup in 15-45 minutes. One‑time purchase: €29.

What This Agent Does

This agent orchestrates a reliable automation between HTTP Request, Webhook, handling triggers, data enrichment, and delivery with guardrails for errors and rate limits.

It streamlines multi‑step processes that would otherwise require manual exports, spreadsheet cleanup, and repeated API requests. By centralizing logic in n8n, it reduces context switching, lowers error rates, and ensures consistent results across teams.

Typical outcomes include faster lead handoffs, automated notifications, accurate data synchronization, and better visibility via execution logs and optional Slack/Email alerts.

How It Works

The workflow uses standard n8n building blocks like Webhook or Schedule triggers, HTTP Request for API calls, and control nodes (IF, Merge, Set) to validate inputs, branch on conditions, and format outputs. Retries and timeouts improve resilience, while credentials keep secrets safe.

Third‑Party Integrations

• HTTP Request
• Webhook

Import and Use in n8n

1. Open n8n and create a new workflow or collection.
2. Choose Import from File or Paste JSON.
3. Paste the JSON below, then click Import.
4. Show n8n JSON

   Title:
   Automating Campaign Engagement Insights with n8n: Smartlead and HubSpot Integration
   
   Meta Description:
   Discover how a robust n8n workflow integrates Smartlead, HubSpot, and PostgreSQL to automate campaign data extraction, activity tracking, CRM updates, and analytics reporting—all with zero manual effort.
   
   Keywords:
   n8n workflow automation, Smartlead integration, HubSpot lifecycle stage, PostgreSQL reporting, email campaign analytics, lead engagement tracking, CRM data sync, automation pipelines, Google Sheets reporting, Smartlead API, HubSpot API
   
   Third-Party APIs Used:
   
   1. Smartlead API
      - Endpoints:
        - /api/v1/campaigns
        - /api/v1/campaigns/{campaign_id}/leads-export
      - Purpose:
        - Retrieve campaign metadata and export lead data in CSV format for further processing and enrichment.
   
   2. HubSpot API
      - Endpoints:
        - /crm/v3/objects/companies
      - Authentication:
        - OAuth2
      - Purpose:
        - Fetch lead lifecycle information such as lifecycle stage, number of open deals, and company IDs to enrich and track lead progression through the campaign funnel.
   
   3. Google Sheets API
      - Purpose:
        - Export refined campaign performance data to a centralized document, enabling non-technical teams (marketing, sales, operations) to access up-to-date campaign insights in real time.
   
   4. PostgreSQL Database (Self-Hosted or Cloud)
      - Purpose:
        - Three schemas (ce_campaign, ce_campaign_activity, hubspot) store structured data:
          - Campaign metadata
          - Lead engagement events and history
          - HubSpot CRM insights
   
   Short Article:
   
   Streamlining Campaign Performance with n8n, Smartlead, and HubSpot
   
   In today’s fast-paced digital marketing environment, automation is no longer a luxury—it’s a strategic advantage. Sales and marketing teams frequently juggle dozens of campaigns, yet spend precious hours gathering performance metrics manually. Modern tools like Smartlead for email outreach and HubSpot for CRM insights are powerful on their own, but integrating them can be the game-changer. That’s exactly what this automated n8n workflow delivers.
   
   The goal of this workflow is to centralize, update, and report key performance insights from outreach campaigns, making it easier for businesses to visualize impact, measure ROI, and optimize tactics—all without manual export/import tasks.
   
   What the Workflow Does
   
   At its core, this automation performs three mission-critical functions:
   
   1. Extracts and parses Smartlead campaign data
   2. Enriches it with HubSpot CRM engagement insights
   3. Writes a unified report to PostgreSQL and Google Sheets
   
   Let’s break it down.
   
   1. Fetching Campaigns from Smartlead
   
   The flow begins with a Schedule Trigger — running at intervals that suit the business (daily, weekly, etc.). Smartlead’s API is queried to retrieve a list of all active and past campaigns. Each campaign's metadata (name, created timestamp, user/client ID, etc.) is upserted into a ce_campaign table in PostgreSQL.
   
   Simultaneously, the workflow hits Smartlead’s leads-export API endpoint to pull raw CSV data for each campaign. This CSV contains granular lead-level insights: names, emails, company, status, engagement metrics (opens, clicks, replies), and more.
   
   2. Parsing Complex CSVs Into Structured Data
   
   Rather than manually downloading and importing this file, an inline code node processes the CSV into JSON. It intelligently handles missing values, quoted strings, and column mismatches—transforming raw exports into valid structured records. These are then inserted or updated into the ce_campaign_activity table.
   
   Highlights include:
   - Conversion of "true"/"false" strings into booleans
   - Calculated metrics (e.g., open_count, reply_count)
   - Extraction of the domain from email addresses for reporting
   
   3. Enriching with HubSpot Data
   
   The campaign-activity entries may lack lifecycle intelligence. For this, the workflow queries HubSpot’s CRM API to retrieve companies and their associated properties (like lifecyclestage and number of open deals).
   
   Here’s where smart logic kicks in:
   - It filters out companies with missing IDs.
   - It checks if the lead’s lifecycle has not been updated in the last 24 hours (avoiding redundant API calls).
   - Records are updated in a separate hubspot table that links back to campaign_id, creating a powerful mapping between email engagement and deal pipeline progression.
   
   4. Campaign Analytics Reporting
   
   With marketing and sales highlights now fully populated, a specialized SQL query combines campaign metadata, lead activity trends, and HubSpot engagement fields like MQL/SQL status, opportunities, and closed customers.
   
   The results?
   - Exported to an easy-to-share Google Sheet
   - Each row becomes a live snapshot of campaign performance
   
   Sample metrics include:
   - Total leads contacted
   - Lifecycle progress (Lead → MQL → SQL → Customer)
   - Reply rates and unsubscribes
   - Company engagement benchmarks
   
   Benefits & Use Cases
   
   Teams using this workflow will benefit in the following ways:
   
   - Marketing Ops: Real-time metrics on performance of headline campaigns across agencies or verticals
   - Sales Enablement: Quick access to revenue-driving leads, especially SQLs and opportunities
   - Analytics & BI: Export-ready data for Looker Studio, Tableau, or BI pipelines
   
   The entire process is built using n8n’s visual automation builder, requiring no code beyond a well-crafted JavaScript snippet for CSV transformation.
   
   Final Thoughts
   
   This campaign automation workflow exemplifies what modern data orchestration should look like. Seamless ingestion of data, powered by Smartlead and enriched with HubSpot, results in clean, actionable reporting—delivered automatically to your favorite spreadsheet.
   
   Whether you're tracking thousands of leads or pivoting based on conversion rates, this n8n workflow transforms your marketing operations from reactive to proactive.
   
   Stay ahead of your pipeline—automated, enriched, and always up to date.
   
   Ready to put this to work? Follow the documentation inside the workflow and drop in your API keys to get started.

5. Set credentials for each API node (keys, OAuth) in Credentials.
6. Run a test via Execute Workflow. Inspect Run Data, then adjust parameters.
7. Enable the workflow to run on schedule, webhook, or triggers as configured.

Tips: keep secrets in credentials, add retries and timeouts on HTTP nodes, implement error notifications, and paginate large API fetches.

Validation: use IF/Code nodes to sanitize inputs and guard against empty payloads.

Why Automate This with AI Agents

AI‑assisted automations offload repetitive, error‑prone tasks to a predictable workflow. Instead of manual copy‑paste and ad‑hoc scripts, your team gets a governed pipeline with versioned state, auditability, and observable runs.

n8n’s node graph makes data flow transparent while AI‑powered enrichment (classification, extraction, summarization) boosts throughput and consistency. Teams reclaim time, reduce operational costs, and standardize best practices without sacrificing flexibility.

Compared to one‑off integrations, an AI agent is easier to extend: swap APIs, add filters, or bolt on notifications without rewriting everything. You get reliability, control, and a faster path from idea to production.

Best Practices

• Credentials: restrict scopes and rotate tokens regularly.
• Resilience: configure retries, timeouts, and backoff for API nodes.
• Data Quality: validate inputs; normalize fields early to reduce downstream branching.
• Performance: batch records and paginate for large datasets.
• Observability: add failure alerts (Email/Slack) and persistent logs for auditing.
• Security: avoid sensitive data in logs; use environment variables and n8n credentials.

FAQs

Can I swap integrations later? Yes. Replace or add nodes and re‑map fields without rebuilding the whole flow.

How do I monitor failures? Use Execution logs and add notifications on the Error Trigger path.

Does it scale? Use queues, batching, and sub‑workflows to split responsibilities and control load.

Is my data safe? Keep secrets in Credentials, restrict token scopes, and review access logs.