This article provides a complete, practical walkthrough of the Http Aggregate 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 AI-Powered Lead Generation Using Google Maps and Website Scraping in n8n
   
   **Meta Description:**  
   Discover how an advanced n8n workflow automates professional lead generation by integrating AI agents, Google Maps scraping, website content extraction, and data enrichment tools to streamline business data collection.
   
   **Keywords:**  
   AI lead generation, Google Maps scraper, n8n workflow, business data extractor, Apify scraper, Google Sheets automation, web scraping with LangChain, GPT-4o OpenAI, website crawling automation, SerpAPI enrichment, ISO country code scraping
   
   ---
   
   ## Intelligent Workflow Automation for Google Maps Lead Scraping with n8n
   
   In a digital era where data-driven strategies dominate growth agendas, the automation of lead generation is not just a convenience—it's a competitive advantage. This article explores a robust n8n-based workflow that automates B2B lead scraping from Google Maps, crawls associated websites, stores data in Google Sheets, and even uses fallback mechanisms to ensure complete and ethical data acquisition. Built upon a stack of powerful APIs and smart AI orchestration, this system transforms traditional prospecting into a scalable and intelligent process.
   
   ### Overview of the Workflow
   
   The “Google Maps FULL” workflow is the centerpiece of a modular and dynamic data scraping system that automates the retrieval of professional and local business details. From the initial user query to data storage, each component is tightly coupled through intelligent nodes within the open-source tool n8n.
   
   At its core, this workflow:
   - Accepts a user’s request (e.g., “Find coffee shops in Paris, France”),
   - Utilizes an AI agent enhanced with LangChain to interpret and execute the task,
   - Runs Google Maps scraping to acquire core business data,
   - Crawls business websites for enriched content,
   - Stores and de-duplicates information in Google Sheets for downstream usage,
   - Falls back on web search capabilities to fill in any missing gaps.
   
   ### Key Features & Workflow Steps
   
   #### 1. User Interaction Trigger
   The entry point, “Trigger - When User Sends Message,” activates the workflow when a user submits a relevant query. This system supports natural language input, which is processed by GPT-4o through the GPT-4o mini node, ensuring a conversational and intuitive interaction.
   
   #### 2. AI Agent for Lead Collection
   The heavy lifting is coordinated by the LangChain AI agent, which follows a detailed prompt structure that enforces:
   - Ethical data handling rules (no PII, only publicly available info),
   - Accuracy (ISO 3166 Alpha-2 codes in lowercase required),
   - Context-awareness (avoids redundant scrapes by checking stored data),
   - Robust fallback strategies using tools like SerpAPI for internet search.
   
   #### 3. Google Maps Scraping (via Apify)
   Using Apify’s Google Maps Scraper Actor, the workflow extracts vital business details such as:
   - Business name
   - Address
   - Phone number
   - Website URL
   - Email
   - Additional metadata
   
   The scraper is parameterized to accommodate city, state or county, and a search term (e.g., barber, café), and always requires a compliant country code.
   
   #### 4. Website Crawling and Enrichment
   If a business listing includes a website, the URL is forwarded (as-is) to another Apify actor—Website Content Crawler. This tool combs through the site, pulls readable content, and structures it for downstream applications like vector indexing or further AI processing.
   
   #### 5. Data Storage in Google Sheets
   Two Google Sheets integrations store structured results—one for basic business listings, and another for enriched website data. This not only organizes the data but enables real-time collaboration, filtering, and visualization by stakeholders.
   
   #### 6. Contextual Memory & Processing
   A LangChain memory buffer tracks recent dialogue and requests. This prevents duplication, ensures continuity across user sessions, and personalizes the user experience by maintaining context.
   
   #### 7. Fallback with Web Search
   Should any scraping steps return incomplete data, the AI automatically employs SerpAPI to perform enriched searches—ensuring no lead is left behind due to limitations in data sources.
   
   ### Benefits of the Workflow
   
   - 🔄 Fully Automated: From user intent to final spreadsheet entries—everything runs without human intervention.
   - 🎯 Lead Quality: Grabs detailed, accurate, and high-quality public data.
   - ⚙️ Scalable: Capable of handling hundreds of leads across multiple locations thanks to Apify and Google Sheets.
   - 🧠 AI-Driven Logic: Uses GPT-4o's intelligence combined with strict formatting, validation, and ethical guidelines.
   - 🛠 Modular & Extensible: Each component can be reused or customized for various scraping needs.
   
   ### Third-Party APIs and Integrations Used
   
   1. **OpenAI GPT-4o (via LangChain)** – Understands and interprets conversational input, providing smart decisions and formatting instructions.
   2. **Apify Google Maps Scraper** – Extracts business listings from Google Maps using search parameters and geolocation.
   3. **Apify Website Content Crawler** – Crawls and processes website content for structured storage and further AI applications.
   4. **Google Sheets API** – Stores all collected and enriched data for viewing, team collaboration, or export.
   5. **SerpAPI** – Acts as a fallback tool for enriching or completing incomplete datasets via traditional web search.
   
   ### Ethical and Structural Safeguards
   
   To ensure responsible data usage, the AI agent is instructed to:
   - Collect only publicly available professional data,
   - Respect Google's and websites' scraping policies,
   - Avoid storing sensitive or personal information,
   - Validate scraped data for duplicates and formatting consistency before storage.
   
   ### Conclusion
   
   This sophisticated n8n workflow turns lead scraping from a manual, error-prone chore into a fast and ethical AI-powered automation. Ideal for digital marketers, data analysts, and B2B prospecting teams, the workflow demonstrates how you can use low-code automation + AI to deliver game-changing operational efficiencies.
   
   With this setup, the future of lead generation is not just automated—it’s intelligent.
   
   ---
   
   🔗 External Setup & Guide:
   For those looking to replicate or deploy this workflow, a detailed implementation guide is available here: [Google Maps Scraper Notion Guide](https://automatisation.notion.site/GOOGLE-MAPS-SCRAPER-1cc3d6550fd98005a99cea02986e7b05)

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.