This article provides a complete, practical walkthrough of the Code Schedule Automation 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

   Title:
   Automated SEO Reports Using n8n, Umami Analytics, OpenRouter AI, and Baserow
   
   Meta Description:
   Learn how to build an automated SEO analytics and content optimization workflow using n8n, Umami, OpenRouter AI, and Baserow. This setup fetches web traffic data, analyzes it using AI, and stores insights for better content strategies.
   
   Keywords:
   n8n workflow, Umami analytics, OpenRouter AI, SEO automation, content optimization, Baserow integration, web analytics, AI SEO analysis, data workflow automation, Umami API
   
   Third-Party APIs Used:
   
   1. Umami API – for collecting website traffic and user analytics.
   2. OpenRouter AI API – for processing SEO insights using AI (LLaMA 3.1 model).
   3. Baserow API – for storing generated reports and analysis data.
   
   Article:
   
   Automating SEO Insights with n8n, Umami, OpenRouter AI, and Baserow
   
   In today’s content-driven internet economy, understanding your website traffic—and responding intelligently to it—is crucial for sustained growth. One powerful way to achieve this is through data automation. In this article, we’ll explore a complete n8n-based workflow that integrates Umami, OpenRouter AI, and Baserow to automate the collection, analysis, and archival of weekly website performance reports.
   
   This no-code/low-code solution not only saves hours of manual work but also provides fresh content strategy insights based on your Umami analytics—powered by advanced AI.
   
   Overview of the Workflow
   
   The n8n automation consists of several key elements:
   
   - Trigger: A schedule-based or manual trigger initializes the workflow.
   - Data Collection: Umami APIs fetch view and page-specific user metrics.
   - Data Parsing: JavaScript transformations simplify data into readable formats.
   - AI Analysis: OpenRouter’s LLaMA 3.1 model provides SEO insights.
   - Report Storage: The results are saved in a Baserow database for easy record-keeping.
   
   Let’s walk through how each part works.
   
   Step 1: Trigger Execution
   
   This workflow can be initiated in two ways:
   
   - Manually: Via a manual trigger node labeled "When clicking ‘Test workflow’."
   - Automatically: A weekly schedule trigger set to run every Thursday (day 4), ensuring insights are generated on a weekly cadence.
   
   Step 2: Fetching Analytics from Umami
   
   The workflow makes a REST API call to Umami—a privacy-focused alternative to Google Analytics—fetching core engagement metrics for the past seven days. These include:
   
   - Pageviews
   - Unique Visitors
   - Total Visits
   - Bounce Rate
   - Total Time on Site
   
   Each request is authenticated via a bearer token in the HTTP header, and takes into account timezone offsets using dynamic date parameters.
   
   Two sets of data are pulled:
   
   - Summary Stats: General metrics like total visitors and bounce rate.
   - Page Metrics: Individual URL visit statistics for this week and the previous week.
   
   Step 3: Parsing and Structuring the Analytics Data
   
   Once raw JSON data is fetched from Umami, it needs interpretation. The workflow uses JavaScript functions in n8n’s Code Nodes to transform and encode this data for later stages.
   
   These scripts extract the relevant values, structure them into simple objects, and encode them to be safe for AI interpretation.
   
   Step 4: Driving SEO Insights Using AI (OpenRouter)
   
   The parsed data is sent to OpenRouter's API, which supports advanced large language models. The AI used here is Meta’s LLaMA 3.1, configured in the "instruct" mode, which is well-suited for analysis and summarization tasks.
   
   Two prompts are created:
   
   1. A high-level summary of the week’s overall web traffic and page visits.
   2. A comparative analysis between this week and last week's page view performance, including five SEO improvement suggestions.
   
   The AI output includes structured markdown tables and detailed content strategy advice.
   
   Step 5: Archiving Reports in Baserow
   
   Once the AI insight is ready, the workflow saves all the findings into a Baserow database—an open-source Airtable alternative. Each weekly record includes:
   
   - Date of report
   - Summary analysis
   - Comparison of top pages
   - Blog or website identifier
   
   This enables historical tracking of website performance and centralizes strategic insights in a searchable database.
   
   Why This Matters
   
   This automated workflow offers several major advantages:
   
   - Consistency: Weekly automated reports remove any possibility of missed analysis cycles.
   - AI-Augmented Insights: Using contextual LLMs ensures reports go beyond raw data to real strategic suggestions.
   - Central Recordkeeping: Baserow provides a structured home for all your insights.
   - Customizable: You can easily adapt URL endpoints, time frames, or AI models to suit different projects.
   
   Final Thoughts
   
   If marketing teams want to stay agile and data-aware, they will need to automate analytical intelligence. This n8n setup demonstrates just how accessible such a solution has become, even without programming skills. By combining open-source tools (n8n, Umami, and Baserow) with cutting-edge AI (OpenRouter), you can build a powerful SEO command center to drive smarter content decisions—on autopilot.
   
   Try replicating this workflow, adjust it for your use case, and take your content performance reviews to the next level.
   
   Resources
   
   - Umami API Docs: https://umami.is/docs/api/
   - OpenRouter: https://openrouter.ai/
   - Baserow: https://baserow.io/
   - n8n Workflow Automation: https://n8n.io/
   
   Want to see it in action? Check out this detailed case study here.

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.