This article provides a complete, practical walkthrough of the Manual Googleanalytics Import Triggered 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 Google Analytics to Airtable: A Simple n8n Workflow to Track Website Traffic by Country  
   
   Meta Description:  
   Learn how to automate the collection of Google Analytics session data by country and store it in Airtable using n8n. Perfect for marketers and analysts looking to streamline web analytics reporting.  
   
   Keywords:  
   n8n workflow, Google Analytics automation, Airtable integration, no-code automation, website traffic analytics, n8n Google Analytics, store analytics in Airtable, Google Analytics sessions, no-code data pipeline  
   
   Third-Party APIs Used:
   
   - Google Analytics API via n8n Google Analytics Node  
   - Airtable API via n8n Airtable Node  
   
   Article:
   
   If you're a marketer, analyst, or business owner, chances are you're constantly monitoring your website traffic. But digging into Google Analytics every time and organizing data manually can be time-consuming. Wouldn't it be great if you could create an automated pipeline that pulls data directly from Google Analytics and stores it neatly in a system like Airtable?
   
   This is exactly what you can accomplish with a simple n8n workflow. n8n (short for "nodemation") is a powerful, open-source workflow automation tool that allows you to connect different apps and services with ease—no coding required. In this tutorial, we'll walk you through a basic yet powerful workflow that collects session analytics for your website based on country and saves that data into Airtable for future use.
   
   Overview of the Workflow
   
   At a high level, the workflow does the following:
   
   1. Starts upon a manual trigger (for example, when you hit “Execute”).
   2. Pulls session data from Google Analytics grouped by country.
   3. Processes and formats the data using the Set node.
   4. Appends the data to a designated Airtable table.
   
   Let's break each step down in more detail.
   
   1. Manual Trigger  
   The first node in this workflow is a Manual Trigger node titled "On clicking 'execute'". This serves as the initiating point for the workflow. This setup is perfect for running the automation on demand—for example, you can trigger it weekly or monthly, depending on your reporting needs.
   
   2. Google Analytics Node  
   The next node in the sequence is the Google Analytics node. This node connects to your Google Analytics view using pre-configured OAuth2 credentials. It is configured to pull in a critical user engagement metric: sessions (ga:sessions). Additionally, the data is segmented by country (ga:country), giving you a regional breakdown of where your traffic is coming from.
   
   What’s particularly useful is that the node includes a date range filter, pulling data from January 1, 2020 to August 30, 2020. You can easily adapt these dates or update the node to retrieve data based on the current date using dynamic date formats.
   
   3. Data Transformation with Set Node  
   Once the raw data is pulled from Google Analytics, the Set node cleans and formats this data. It extracts two useful fields:
   
   - Metric: Total number of sessions.
   - Country: The visitor’s country.
   
   This preparation ensures that the data is formatted precisely for easy insertion into Airtable.
   
   4. Store in Airtable  
   Finally, the clean data is sent to Airtable using its API via the Airtable node. The operation is set to 'append', which means every interaction adds a new row to your selected Airtable table. This is a great way to maintain a historical log of analytics data over time.
   
   Use Cases
   
   This automation workflow is perfect for:
   
   - Marketing teams tracking international web traffic.
   - Startups that want to build a centralized analytics dashboard in Airtable.
   - Consultants reporting to clients on web performance without digging into Google Analytics every time.
   - Product managers who want a low-maintenance analytics snippet for their Airtable-based reporting hub.
   
   Why Use n8n?
   
   Unlike other automation tools, n8n gives users complete control over their data and offers a range of integrations without the tech-heavy lift of traditional development. Best of all, it's open source, so you’re not locked into a proprietary platform.
   
   This Google Analytics to Airtable workflow is a great example of how n8n can be used as a lightweight data pipeline for analytics. With just four nodes and no custom code, you turn a manual task into a repeatable, scalable process.
   
   Further Enhancements
   
   To take this workflow even further, consider:
   
   - Automating the manual trigger with a Cron node to run it weekly or monthly.
   - Adding additional metrics or dimensions such as bounce rate, pages per session, or device type.
   - Creating visualizations in Airtable using its interface designer or syncing to another dashboarding tool like Tableau or Google Data Studio.
   
   Conclusion
   
   With just a few simple steps in n8n, you can automate the entire process of pulling session data from Google Analytics and storing it in Airtable. It’s a great example of how no-code tools can empower teams to work smarter and streamline data operations. Whether you're tracking marketing performance or monitoring international engagement trends, this workflow provides an efficient and scalable solution.
   
   By automating common analytics tasks, you free up your time to focus on strategic decision-making and growth initiatives—instead of wrangling spreadsheets.

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.