This article provides a complete, practical walkthrough of the Code Filter Monitor 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 Competitor Price Monitoring with n8n: A No-Code Workflow
   
   Meta Description:  
   Discover how to automate competitor pricing analysis using a powerful n8n workflow that integrates Google Sheets, Airtop AI, and Slack. Eliminate manual tracking and get real-time updates on pricing changes.
   
   Keywords:  
   n8n, price monitoring automation, competitor pricing, no-code tools, pricing tracker, Airtop AI, Google Sheets automation, Slack notifications, workflow automation, SaaS pricing monitor, web scraping alternative
   
   Third-Party APIs Used:
   
   - Google Sheets API (via n8n’s Google Sheets node)
   - Airtop API (for AI-powered text and pricing extraction)
   - Slack API (for real-time notifications)
   
   —
   
   Article:
   
   Automating Competitor Price Monitoring with n8n: A No-Code Workflow
   
   In a rapidly evolving digital market, keeping an eye on competitors' pricing is essential to making strategic business decisions. However, manually tracking changes across multiple websites is time-consuming and error-prone. What if you could build a fully automated, real-time competitor price monitoring workflow—without writing a single line of backend code?
   
   Enter n8n, a powerful open-source workflow automation tool. This article breaks down a sophisticated n8n workflow designed for automating competitor price tracking using Google Sheets, Airtop AI, and Slack. Here's how it works and why it could transform the way your business manages pricing intelligence.
   
   Why You Need Automated Price Monitoring
   
   For startups, e-commerce retailers, and SaaS companies, pricing agility is key. Monitoring competitors lets you:
   
   - React quickly to pricing changes.
   - Optimize your own plans for market positioning.
   - Save time vs. manual scraping or analysis.
   
   However, automation tools for pricing are often expensive or over-complicated. With n8n, you can DIY your own robust system using best-in-class integrations.
   
   Overview of the Workflow
   
   This n8n workflow, named “Monitor Competitor Pricing,” automates the process of checking multiple competitor pricing pages, comparing previous prices to current ones, and notifying you of any changes—all in one seamless flow.
   
   Here’s a step-by-step breakdown of the workflow:
   
   1. Manual Trigger:  
   The process begins with a manual trigger node, allowing you to initiate the workflow with the click of a button during testing or at scheduled intervals.
   
   2. Read Competitor URLs from Google Sheets:  
   Using n8n’s Google Sheets node, the workflow pulls a list of pricing page URLs from a connected Google Sheet ("Copy of Monitor Pricing"). Each row contains the current pricing and the link to a pricing page.
   
   3. AI-Powered Price Extraction via Airtop:  
   Each URL is then sent to the Airtop API, which uses advanced language models to read the pricing pages and extract:
   
      - A summarized description of the pricing plans (name, price, top 3 features).
      - A summary of any differences from the previous value.
      - A status tag: [DIFF], [SIMILAR], or [NEW].
   
   The prompt given to Airtop ensures precise and non-speculative extraction by instructing the AI to only summarize clearly visible pricing information.
   
   4. Merge and Parse Results:  
   Once results return from Airtop, a merge node organizes the data, and a code node parses the response to include additional fields like the row number and original URL for mapping.
   
   5. Filter Out Unchanged Entries:  
   A filter node evaluates the “status” field. If the status is [SIMILAR], it’s ignored—only updates marked as [DIFF] or [NEW] proceed.
   
   6. Update Google Sheets with New Data:  
   For updated pricing info, the workflow sends the new data back to the original Google Sheet, replacing the old pricing summary for that row.
   
   7. Notify Team in Slack:  
   Lastly, the Slack node sends a message to a specified channel (like #pricing-changes) with a link to the page and a brief summary of the pricing difference.
   
   Putting It Together
   
   This tightly connected system achieves a live feedback loop with zero manual intervention:
   
   - Google Sheets is the source of truth.
   - Airtop provides automated, accurate analysis of pricing pages.
   - Slack ensures team visibility and fast reaction to price variance.
   
   As changes on competitors’ pricing pages are detected, your team is instantly alerted, and your database remains up-to-date.
   
   Why Use Airtop Instead of Scraping HTML?
   
   Scraping the DOM for prices and feature text is fragile and often breaks with minor layout changes. Airtop’s AI interprets the meaning of text, extracting human-readable plan names, features, and pricing—just like a real analyst would. This drastically increases reliability and reduces maintenance overhead.
   
   Use Cases and Benefits
   
   This automated setup is ideal for:
   
   - SaaS companies tracking similar tools.
   - E-commerce brands analyzing Shopify competitors.
   - Agencies monitoring subscription services for clients.
   
   Key benefits include:
   
   - Elimination of repetitive manual checks.
   - Human-like comprehension of pricing tiers via AI.
   - Real-time insights, team collaboration, and historical tracking.
   
   Conclusion
   
   With just a few tools—n8n, Google Sheets, Airtop, and Slack—you can build a robust, intelligent pricing tracker that scales with your business. The no-code nature of n8n makes it accessible to marketers, product managers, and analysts alike.
   
   Stop chasing price tags manually and start automating your competitive edge.
   
   —
   
   Want help setting it up? Visit n8n.io to start building your own competitive intelligence workflows.

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.