This article provides a complete, practical walkthrough of the Webhook Filter Export Webhook 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

   Certainly! Here's a well-structured article based on the provided n8n workflow:
   
   ---
   
   # Article Title:
   Automating Retell AI Voice Call Analysis with n8n: Export to Airtable, Google Sheets, and Notion
   
   ## Meta Description:
   Learn how to automate the logging and analysis of Retell AI voice calls using n8n workflows. This guide shows how to extract call data and store it in Airtable, Google Sheets, and Notion with ease.
   
   ## Keywords:
   Retell AI, voice agents, Retell call analysis, n8n automation, n8n workflow, Airtable automation, Google Sheets API, Notion API, call transcript logging, voice AI analytics
   
   ---
   
   ## Streamlining Retell AI Call Data with n8n
   
   Voice agents powered by Retell AI deliver robust automated communication experiences by leveraging advanced AI speech recognition and synthesis. But what happens to the valuable data—transcripts, sentiment, summaries—after each call ends? Without structured storage, this rich information remains underutilized.
   
   This is where n8n—the powerful, low-code automation platform—steps in. With n8n, builders and developers can automate the capture and logging of Retell AI calls in real-time, storing essential call attributes and AI-driven analysis across their preferred tools like Airtable, Google Sheets, and Notion.
   
   Let’s take a closer look at a ready-made n8n workflow that accomplishes exactly that.
   
   ---
   
   ## What the Workflow Does
   
   This workflow is designed to automate the receipt and logging of Retell AI's post-call `call_analyzed` webhook events. It extracts structured information from analyzed calls—including transcripts, sentiment, and summary insights—and saves it to multiple destinations for long-term storage and analysis.
   
   Here’s a breakdown of what’s under the hood:
   
   ### 1. Webhook Listener for Retell Events
   
   The first step is a Webhook node that listens for POST requests sent by Retell AI once a call is analyzed. You simply set the webhook URL (e.g., `https://your-instance.app.n8n.cloud/webhook/poc-retell-analysis`) under your Retell agent’s webhook settings.
   
   This node filters for the event type `call_analyzed`—Retell sends different events (`call_started`, `call_ended`, and `call_analyzed`), but only `call_analyzed` contains the full post-call insights.
   
   ### 2. Smart Filtering
   
   A Filter node ensures only the `call_analyzed` events continue through the workflow. This is important to avoid storing partial or irrelevant information from other webhook triggers.
   
   ### 3. Extracting and Formatting Data
   
   The “Set fields to export” node plays a crucial role in parsing and transforming the incoming JSON. It extracts details such as:
   
   - Call ID
   - Start and End timestamps (converted to ISO format)
   - Transcript text
   - Call summary
   - User sentiment (e.g., Positive, Neutral, Negative)
   - Total duration (in seconds)
   - Total cost (converted from cents to dollars)
   - Phone number (depending on call direction—`from_number` or `to_number`)
   
   Each of these fields is not only extracted but also cleaned and transformed to fit the expected schema of the output tools.
   
   ---
   
   ## Where the Data Goes: Three Export Options
   
   Depending on your tech stack, you can choose one or more destinations to store your transcripts and call data:
   
   ### A. Airtable
   
   Data is saved to a predefined Airtable base titled “Retell Sample” and a table called “Transcripts”. Key columns such as Call ID, Transcript, Call Summary, and Duration allow users to easily browse and search past voice conversations.
   
   Ideal for: Visual, team-based collaboration & lightweight databases.
   
   ### B. Google Sheets
   
   The same data is also appended to a tab in Google Sheets named “Transcripts.” This is perfect for quick filtering, sharing, or triggering further analysis pipelines (e.g., via Google Apps Scripts).
   
   Ideal for: Analytics, pivot tables, spreadsheets, and Google Workspace integration.
   
   ### C. Notion
   
   Lastly, the workflow also posts this data into a Notion database. The transcript becomes a rich-text field, with additional fields (dates, sentiment, phone number, etc.) matching the database schema.
   
   Ideal for: Internal knowledge bases, customer service logs, and AI assistant training datasets.
   
   ---
   
   ## Benefits of Automating Retell Call Logging
   
   - 📈 Centralize all Retell agent interactions in searchable databases
   - 🧠 Quickly analyze or visualize call quality, sentiment, and cost
   - ⚙️ Seamlessly connects with other automation tools in your workspace
   - ✅ Saves time vs. manual data entry or exporting JSON blobs
   
   This automation becomes highly scalable for teams managing multiple agents or using Retell for high-call-volume use cases, such as customer support or booking systems.
   
   ---
   
   ## Getting Started
   
   Before using the template, ensure you have:
   
   1. A Retell AI account and a connected phone number.
   2. At least one of the output tools prepared:
      - An Airtable base and table
      - A Google Sheets file with a “Transcripts” tab
      - A Notion database with required fields
   
   Once those are set up, follow these steps:
   
   1. Import the n8n workflow and activate it.
   2. Add the n8n webhook URL to your Retell agent under “Webhook settings”.
   3. Run a call through your Retell AI agent.
   4. Watch the data appear in Airtable, Google Sheets, or Notion.
   
   ---
   
   ## Extend and Customize
   
   You can further enrich the workflow by:
   
   - Adding language/tone classification
   - Ingesting custom fields from `call.call_analysis.custom_analysis_data`
   - Syncing to CRMs like HubSpot or Salesforce
   - Creating follow-up email actions triggered by negative sentiment
   
   ---
   
   ## Third-Party APIs Used
   
   This workflow successfully integrates with several APIs:
   
   1. **Retell AI Webhooks** – For real-time call analysis updates.
   2. **Airtable API** – To write structured data into a specified base and table.
   3. **Google Sheets API** – For appending rows into the “Transcripts” sheet.
   4. **Notion API** – To create structured pages containing call summaries and metadata.
   
   ---
   
   By using n8n to automate how Retell AI conversations are stored and analyzed, teams can focus on insights—not infrastructure.
   
   🔗 Want to skip building from scratch? Use the community templates:
   - [Airtable Template](https://airtable.com/appN4jeIrD8waWCfr/shrsPtQLeqt8Sp3UZ)
   - [Google Sheets Template](https://docs.google.com/spreadsheets/d/1TYgk8PK5w2l8Q5NtepdyLvgtuHXBHcODy-2hXOPP6AU/edit?usp=sharing)
   - [Notion Template](https://www.notion.so/1cea19b9d4848089bda6f3d7e05a818d)
   
   —
   
   Need help analyzing Retell conversations or expanding this workflow? Contact us at hello@agentstudio.io.
   
   ---
   
   Let me know if you'd like this as a polished PDF or want to publish it on your documentation platform.

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.