This article provides a complete, practical walkthrough of the Telegram Googleanalytics Automation 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 Weekly Google Analytics Reports with n8n & AI
   
   Meta Description:
   Learn how to automate Google Analytics reporting with n8n. This no-code workflow collects, compares, and analyzes data weekly before sending actionable insights via email and Telegram—powered by Google Analytics, OpenAI, and more.
   
   Keywords:
   n8n, Google Analytics, marketing automation, weekly report, OpenAI, Telegram bot, email automation, GA4 reporting, AI analytics, no-code tools
   
   Third-party APIs Used:
   
   - Google Analytics API (GA4): For retrieving analytics data from the last 7 days and the same period of the previous year
   - OpenAI API: For converting raw data into sleek, AI-generated summaries and formatting them in human-readable emails and Telegram messages
   - SMTP: For email report delivery
   - Telegram Bot API: For sending short summaries to a specified Telegram chat
   
   —
   
   Article:
   
   Automating Google Analytics Weekly Reports with n8n and AI
   
   Marketing and analytics teams often face the daunting task of compiling performance reports week after week. What if you could automate the entire process—from data collection to analysis to delivery—without writing a single line of code? This is exactly what one powerful n8n workflow achieves, combining Google Analytics, AI-generated insights, and messaging automation.
   
   Let’s break down how it all works so you can set up your own weekly analytics engine.
   
   From Data to Decisions: The Workflow Journey
   
   This n8n automation is designed to generate a weekly Google Analytics performance report by pulling the latest data, comparing it with the same week from the previous year, summarizing in visual format, and distributing the results via email and Telegram.
   
   Here are the key steps in the automation:
   
   1. Scheduled Trigger  
      Every Monday at 7 a.m., a Schedule Trigger node initiates the workflow. This ensures consistency—analytics are processed fresh each week without manual intervention.
   
   2. Fetching This Week’s Data from Google Analytics  
      Using the Google Analytics node, analytics from the past 7 days are pulled. Key GA4 metrics include:
      - Page views (screenPageViews)
      - Sessions
      - Sessions per user
      - Average session duration
      - E-commerce purchases
      - Revenue per purchase
      - Total revenue
   
   3. Assigning and Summarizing Values  
      The Assign node maps raw metric names to cleaner labels like 'Nutzer' (Users) and 'Revenue’. Then the Summarize node calculates totals and averages for an easy overview.
   
   4. Fetching Historical Comparison Data  
      Before analyzing trends, we need a frame of reference. Another GA4 node fetches the same metrics—but from the same 7-day span in the previous year. A code node calculates the correct date range dynamically.
   
   5. Comparing Current vs Previous Year  
      After assigning and summarizing the older data, the values are lined up side by side with the current week’s metrics.
   
   6. AI-Powered Analysis for Email  
      A GPT-4 model is prompted to generate a sleek, modern HTML report. It includes:
      - A 2–3 sentence summary of what changed
      - A well-formatted table with percentage change for each key metric
      - Elegant formatting ideal for email embedding
   
   7. Email Distribution  
      The generated HTML is sent via an SMTP email node to a predefined recipient, making the report accessible and professional.
   
   8. AI-Powered Short Summary for Telegram (Optional)  
      For faster consumption, the same GPT-4 engine simplifies the report into short bullet points. This time, the output is plain text—great for instant sharing on Telegram.
   
   9. Distribution via Telegram  
      Finally, the Telegram node sends the summary to a specific chat ID, allowing real-time updates to a team or stakeholder.
   
   Why This Workflow Matters
   
   ☑️ Zero Manual Work: After initial setup, everything runs hands-free every week.  
   ☑️ Better Analysis: Side-by-side comparisons let you identify trends, wins, and red flags at a glance.  
   ☑️ Team Communication: Enables instant sharing across email and chat, closing the gap between analytics and action.  
   ☑️ AI Enrichment: GPT-4 handles the formatting and insight generation, removing the need for spreadsheet wrangling or copy-pasting.
   
   Tech Stack in Use
   
   This workflow is made possible through direct integration with best-in-class third-party APIs:
   
   - Google Analytics API (GA4): Pulls both real-time and historical web performance data.
   - OpenAI (GPT-4): Transforms data into well-written HTML content and message summaries.
   - SMTP Email: Sends HTML reports via authenticated mail accounts.
   - Telegram Bot API: Enables alerts and insights to be pushed into chats automatically.
   
   Conclusion
   
   Whether you’re reporting to clients, stakeholders, or just watching your own KPIs, this n8n workflow makes weekly reporting instant, insightful, and automated. By combining the power of Google Analytics with AI-enhanced summaries and smart delivery mechanisms, this setup allows marketers and analysts to focus more on strategy and less on spreadsheets.
   
   You can adapt this workflow further—add Slack integration, pull in other tools like CRM data, or extend it to monthly comparisons. With n8n, the only limit is your imagination.
   
   Need help setting it up? Contact the creator at https://www.linkedin.com/in/friedemann-schuetz.
   
   —  
   End of Article

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.