This article provides a complete, practical walkthrough of the Splitout Manual Automate 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:  
   Automating Etsy Data Mining with Bright Data and Google Gemini in n8n
   
   Meta Description:  
   Learn how to build a no-code workflow in n8n to automate Etsy web scraping using Bright Data’s Web Unlocker and AI-assisted data extraction with Google Gemini. Ideal for market researchers and e-commerce analysts.
   
   Keywords:  
   n8n workflow, Etsy scraping automation, Bright Data Web Unlocker, Google Gemini Flash, AI data extraction, e-commerce analysis, no-code automation, Google Gemini API, LLM integration, product information miner
   
   Third-Party APIs Used:
   
   1. Bright Data API (Web Unlocker)  
   2. Google Gemini API (models/gemini-2.0-flash-exp)  
   3. OpenAI API (optional use of GPT-4o-mini)  
   4. webhook.site (for outbound notification testing)
   
   Article:
   
   In the competitive landscape of e-commerce, data is king. Whether you're running an Etsy shop, monitoring trends, or conducting market research, staying ahead requires timely, structured product intelligence. Manually gathering data is time-consuming and inefficient, but with modern automation tools and large language models (LLMs), data mining can be streamlined into a seamless, no-code operation. In this article, we explore how a custom-built workflow in n8n automates the extraction of product data from Etsy using Bright Data's Web Unlocker and Google Gemini’s Flash LLM.
   
   Setting the Stage with n8n
   
   n8n is a powerful open-source workflow automation tool that enables visual programming minus the deep technical know-how. The workflow in question begins with a manual trigger, allowing on-demand Etsy data scraping without waiting for schedules or webhooks. This flexibility is ideal during development, experimentation, or ad-hoc research runs.
   
   Step 1: Defining the Target Data
   
   The initial node “Set Etsy Search Query” prepares the base URL for the Etsy category we're mining—specifically searching for "wall art for mum", an evergreen niche leading up to occasions like Mother’s Day. Additional parameters like sorting by most recent releases and limiting results to the first page are set here. It also registers the Bright Data "zone" for authentication—critical for bypassing anti-scraping controls.
   
   Step 2: Using Bright Data’s Web Unlocker
   
   Etsy, like many marketplaces, is designed to prevent bots. That's where Bright Data’s Web Unlocker shines. The workflow performs a POST request to Bright Data, passing the Etsy URL and rendering format. Bright Data returns the raw HTML content, navigating through JavaScript-heavy pages and Captchas on your behalf.
   
   Step 3: Parsing Scenes with AI
   
   Instead of setting up complex CSS selectors or XPath queries to parse this HTML, the workflow delegates that responsibility to Google Gemini’s model “gemini-2.0-flash-exp”. This LLM parses HTML content and extracts structured data using a predefined JSON schema. It's an elegant fusion of web scraping and AI that minimizes the need for brittle regex filters and traditional parsers.
   
   Extracting Pagination
   
   Etsy pages are rarely singular. Gemini is also leveraged to extract pagination links—ensuring that each "next" page is discovered and recorded to iterate through. The result is a dynamic list of URLs that the workflow will crawl through in batches, thanks to the "Loop Over Items" and "SplitOut" nodes in n8n.
   
   Step 4: Looping Over Pages
   
   For each paginated Etsy page, the workflow repeats the process: using Bright Data to unlock the content, and Google Gemini to interpret it. This is crucial for collecting a comprehensive dataset.
   
   The extracted data includes key product specifics such as:
   
   - Image URL  
   - Product Title  
   - Listing URL  
   - Brand Information  
   - Pricing (with currency)
   
   This product-specific insight is especially useful for market analysts, data scientists, or anyone building a pricing strategy.
   
   Optional OpenAI Integration
   
   A fantastic feature of this workflow is its modularity. While it defaults to using Google Gemini, there's a fully configured switch to use OpenAI’s GPT-4o-mini for extraction if preferred. Simply modify the model credentials and you’re ready to run the same AI-powered extraction using OpenAI infrastructure.
   
   Step 5: Post-Processing and Storage
   
   After data is extracted, two final outputs are triggered:
   
   1. A webhook notification sends a clean summary to a webhook.site endpoint—this simulates an outbound notification, which could easily be redirected to Slack, Telegram, or internal dashboards.
   2. A binary buffer is created from the extracted JSON and saved to disk. With each file named uniquely using the page number, this enables structured archiving across multiple runs.
   
   Use Cases
   
   - E-commerce competitive analysis  
   - SEO and pricing research  
   - Trend discovery  
   - Supplier and product listing monitoring  
   - Hobby projects around gift trends
   
   Conclusion
   
   With Bright Data, Google Gemini, and n8n, you've unlocked a scalable, ethical, and efficient approach to web data extraction from Etsy. This blend of AI and automation transforms chaotic HTML into actionable intelligence—no coding required.
   
   Whether you're a developer looking to simplify data scraping or a non-technical stakeholder in need of market insights, this workflow stands as a prime example of what modern automation can deliver.
   
   Ready to upgrade your data game? Let n8n and AI do the heavy lifting so your team can focus on insights—not infrastructure.

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.