This article provides a complete, practical walkthrough of the Splitout Manual 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:  
   Automate Lead Generation: Extract Business Data from Google Maps to Google Sheets Using n8n and Dumpling AI
   
   Meta Description:  
   Discover how to automate lead scraping from Google Maps using Dumpling AI and n8n. Learn how to extract key business information and store it in a Google Sheet for easy access and future outreach.
   
   Keywords:  
   Google Maps scraping, business leads automation, Dumpling AI, n8n workflow tutorial, Google Sheets integration, lead generation automation, restaurant data extraction, Google Maps API alternatives, scraping with n8n, automate business data collection, Google Maps to spreadsheet, business intelligence automation
   
   Third-Party APIs Used:
   
   1. Dumpling AI API – for performing Google Maps-style searches and returning structured data on business listings.
   2. Google Sheets API (via n8n's Google Sheets node) – for appending extracted business info into a defined spreadsheet.
   
   Article:
   
   ---
   
   Are you tired of manually searching Google Maps and writing down business leads into a spreadsheet? Whether you work in sales, market research, or local SEO, having a streamlined way to collect structured local business data can be a game-changer. In this tutorial, we’ll uncover how to automate the entire process — from querying businesses on Google Maps using Dumpling AI to saving the results into Google Sheets — using the powerful n8n automation platform.
   
   In just a few clicks, you can gather dozens of potential leads, complete with name, address, phone number, website, price level, Google rating, and even booking links.
   
   Let’s break it all down.
   
   🎯 What You’ll Build  
   A simple yet efficient automation workflow in n8n that accomplishes the following:
   
   - Sends a search query to Dumpling AI to simulate a Google Maps search (e.g., “best restaurants in New York”).
   - Receives a rich payload of business information.
   - Breaks down each search result.
   - Stores that data dynamically into a Google Sheet.
   
   📦 Tools Used:
   
   - n8n (Open-source workflow automation)
   - Dumpling AI (Semantic search engine for websites and maps)
   - Google Sheets (Cloud spreadsheet for storing data)
   
   🛠️ Workflow Summary
   
   1. Manual Trigger  
   The workflow is initiated with a Manual Trigger node. This is perfect for testing or one-off scrapes. In production, this could easily be replaced with a Cron or Webhook trigger.
   
   2. Dumpling AI API Request  
   Next, the workflow sends a POST request to Dumpling AI's /search-maps endpoint. This mimics a Google Maps search with a query string like `best+restaurants+in+New+York`. The response includes a `places` array containing dozens of business entries.
   
   3. Split the Response  
   The n8n “SplitOut” node takes that array and splits each business into its own item. This is necessary for processing each business record individually and appending it to the spreadsheet line by line.
   
   4. Save to Google Sheets  
   Finally, each business result is pushed into a predefined Google Sheet. The fields include:
   
   - Name
   - Rating
   - Address
   - Type (e.g., Italian restaurant, French restaurant)
   - Website
   - Price level
   - Booking link
   - Phone number
   
   Each scrape can populate as many leads as Dumpling AI’s API credits allow per search.
   
   🧠 Customization Options
   
   - The query can easily be changed to target other verticals or regions; just replace the `query` parameter in the HTTP Request node with another term (e.g., “top cafes in San Francisco”).
   - Use a schedule trigger instead of manual – run it daily or weekly.
   - Add a Set node to add tags, filters, or enrichment steps between extraction and sheet entry.
   - Integrate a CRM, email automation tool, or Airtable instead of Google Sheets.
   
   💡 Pro Tips
   
   - Make sure to monitor your Dumpling AI API credits — each search uses a credit.
   - Use URL encoding for query strings: spaces become "+" or "%20" to avoid malformed requests.
   - You can enrich the results further by connecting additional APIs like Clearbit, Hunter.io, or Yelp.
   
   ⚙️ Why Use Dumpling AI Instead of Google Maps API?
   
   While you might wonder why this doesn’t use the official Google Maps API, Dumpling AI offers easier parsing and keyword-based business discovery at a fraction of the complexity. It essentially acts as a semantic wrapper for Google Maps, returning cleaner, structured JSON that’s ideal for low-code platforms like n8n.
   
   📈 Real Use Cases
   
   - Local digital marketing agencies scraping business details for outreach.
   - Food bloggers collecting restaurant data for reviews.
   - Sales professionals building lead databases.
   - Market researchers collecting price ranges and ratings data.
   
   🏁 Conclusion
   
   With just a few nodes in n8n, you can transform the laborious task of manually collecting business info from Google Maps into a slick, reusable automation. Dumpling AI handles the search legwork, while n8n takes care of the data flow, and Google Sheets stores the results. Whether you need this once or every morning before coffee, this workflow will save you hours of tedious effort.
   
   Start building smarter lead pipelines, one automated fetch at a time.
   
   ---
   
   Need help customizing this workflow further? The open-source n8n community is a great place to explore more use cases or share your automation story!
   
   Happy automating! 👨‍💻📊✨

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.