Workflow Templates

This n8n workflow template uses community nodes and is only compatible with the self-hosted version of n8n. 📈 StockPulse: AI-Picked Daily News for Your Portfolio Stay ahead of the market with this automated, AI-powered stock market news briefing delivered straight to your inbox — no code required. Watch Step-by-step Video Tutorial Here: https://www.youtube.com/watch?v=iZvPej9eLYE&t=201s ⚙️ What it does: This workflow runs every morning and: Triggers a scheduled prompt to a Langchain AI Agent (OpenAI) Uses the Tavily Web Search API to fetch fresh financial news relevant to your watchlist or portfolio Summarizes the top stories, highlighting: 🔍 Key headlines 💡 Investment opportunities ⚠️ Risks and macro trends 📊 Suggested trades Sends a clean, readable email via Gmail to your preferred address 🔧 Built with: 🧠 Langchain AI Agent (OpenAI GPT-4o) 🔍 Tavily Search Tool 📬 Gmail Node for Email Delivery ⏰ Daily Cron Trigger (customizable) 💼 Who it’s for: Investors and traders who want to save time on news gathering Financial creators looking for curated, actionable insights Non-technical users interested in automating stock news monitoring Anyone who wants to combine AI + automation + market data 🟢 Customize easily: Edit your stock list or news focus inside the Agent prompt 📨 Email ready: Just plug in your Gmail credentials and you’re good to go ⏱️ 10-minute setup — no coding required!

This n8n template helps you automatically discover, analyze, and track trending topics and videos on YouTube using an AI-powered agent. Use cases are many: This workflow is perfect for YouTube creators needing fresh video ideas, digital marketers scouting new campaign topics, social media managers who want to catch trends early, and researchers who want to analyze what’s viral. How It Works The workflow starts whenever a chat message is received (e.g., a trend question, a topic prompt, or a request for insights). Incoming chat is routed to the AI Agent – Trend Explorer node: First, the agent triggers the Workflow – YouTube Search tool to gather the latest trending topics and keywords from YouTube. Next, the agent supplies this real-time YouTube data to the OpenAI Chat Model for deep analysis, trend interpretation, and unique insights. To provide context-aware answers and track ongoing interests, the agent also references a Simple Memory module, recalling past queries, and user instructions. Finally, the result is a fast, data-driven, and smart trend report delivered instantly to your chat. How To Set Up Download the workflow package (including 2 .json files) and import it into your n8n interface. Set up necessary access in the following components of the AI Agent - Trend Explorer node: OpenAI Chat Model: allows API connection for trend insights. Workflow – YouTube Search: searches for trending videos based on the query. Simple Memory (optional): enhances experience for ongoing sessions. Start by sending a chat message on n8n. Check the response from the AI agent in the same chat box. Ask follow-ups, explore deeper, or trigger new searches - all in one chat thread. Requirements n8n instance (self-hosted or cloud). Set up API access to OpenAI Chat Model for chat-based AI. How To Customize Connect to your favorite chat platforms**: Easily integrate with additional chat triggers such as Telegram, Slack, or your preferred messaging app. Choose your preferred AI model**: If you want a different viewpoint, simply swap OpenAI Chat Model for Google Gemini, Claude, or any compatible LLM model in your workflow. Upgrade memory for smarter conversations: For long-term recall or more advanced, context-aware chats, replace **Simple Memory with a vector database like Pinecone or Redis. Need Help? If you’d like this workflow customized to fit your tools and platforms availability, or if you’re looking to build a tailored AI Agent for your own business - please feel free to reach out to Agent Circle. We’re always here to support and help you to bring automation ideas to life. Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle

Description This n8n workflow template allows users to check if a Tron wallet address is blacklisted on the USDT contract via a Telegram bot. When a user sends the command {walletAddress} through the Telegram bot, the workflow queries the Tronscan API to determine if the provided wallet address is blacklisted. The result is then sent back to the user via the Telegram bot. Detailed Description Workflow Overview This workflow is designed to interact with users through a Telegram bot and check if a given Tron wallet address is blacklisted on the USDT contract. The workflow consists of four main nodes: Telegram Trigger Node: Listens for messages from the Telegram bot. HTTP Request Node: Sends a GET request to the Tronscan API to check the blacklist status of the provided wallet address. Function Node: Processes the API response and formats the message to be sent back to the user. Telegram Send Message Node: Sends the formatted message back to the user via the Telegram bot. Nodes Configuration 1.Telegram Trigger Node Event: Message Update Types: Message Command: /sorgu Description: This node listens for the {walletAddress} command followed by a wallet address from the user. 2.HTTP Request Node Method: GET URL: https://apilist.tronscanapi.com/api/stableCoin/blackList?blackAddress={{ $json.message.text }} Response Format: JSON Description: This node sends a GET request to the Tronscan API using the wallet address provided by the user. 3.Code Node Check Api Response: let message; if (response.total && response.total > 0) { message = 🚨🛑 This Wallet is Blacklisted! 🛑🚨: ${response.data[0].blackAddress}; } else { message = ✅💚 This Wallet is NOT Blacklisted! 💚✅.; } return [ { json: { text: message, }, }, ]; Description:** This node processes the API response to determine if the wallet address is blacklisted and formats the message to be sent back to the user. 4.Telegram Send Message Node Resource: Message Operation: Send Chat ID: ={{$json["chat_id"]}} Text: ={{$json["text"]}} Description: This node sends the formatted message back to the user via the Telegram bot. How to Use Set Up Telegram Bot: Create a Telegram bot and obtain the API token. Configure the bot to listen for the {walletAddress} command. Import Workflow: Import this workflow into your n8n instance. Configure Credentials: Add your Telegram API credentials to the Telegram Trigger and Telegram Send Message nodes. Run Workflow: Start the workflow. Users can now send the {walletAddress} command to the Telegram bot to check if a Tron wallet address is blacklisted. Example Usage User Telegram Command: {TR7NHqjeKQxGTCi8q8ZY4pL8otSzgjLj6t} API Request: https://apilist.tronscanapi.com/api/stableCoin/blackList?blackAddress=TR7NHqjeKQxGTCi8q8ZY4pL8otSzgjLj6t API Response: "total": 1, "data": [ { "blackAddress": "TR7NHqjeKQxGTCi8q8ZY4pL8otSzgjLj6t", "tokenName": "USDT", "num": "367583344429", "time": 1593184959, "transHash": "af4bc4d793f82ca5ba500cf13cf93ca3e7a56fccc2aabf8b09e55fc756500ea8", "contractAddress": "TR7NHqjeKQxGTCi8q8ZY4pL8otSzgjLj6t" } ] } Bot Response: 🚨🛑 This Wallet is Blacklisted! 🛑🚨: TR7NHqjeKQxGTCi8q8ZY4pL8otSzgjLj6t > This workflow provides a simple and efficient way to check the blacklist status of Tron wallet addresses via a Telegram bot, making it easy for users to stay informed about the status of their wallets.

🏖️ AI-Based Tour Itineraries via Email Using OpenAI & Pinecone Vector Search Overview This workflow automates the process of handling new tour package requests received via email, analyzes the request, and provides personalized tour package recommendations using AI and a vector database. It’s designed to streamline customer interactions and deliver quick, relevant responses. Precondition Create a Embedded Tour Package Database (refer to the link below): Pinecone Database setup Register and create API Keys for OpenAI, Pinecone Database. Copy Mail Credentials to access Email Inbox from n8n node This workflow automates the process of extracting tour information from PDF files stored in a Google Drive folder, processes and vectorizes the extracted data, and stores it in a Pinecone vector database for efficient querying. This is especially useful for building AI-powered search or recommendation systems for travel packages. 🛠️ Tools & Nodes Used Email Trigger (IMAP): Monitors the inbox for new tour package requests. Text Classifier: Categorizes incoming emails (e.g., New Request, Follow-up, Other). Code Node: Extracts and structures relevant data from the email (subject, sender, content, etc.). Tour Recommendation AI Agent: An AI agent that interprets the request and formulates a prompt for package recommendations. OpenAI & OpenRouter Chat Models: Used for natural language understanding and generating responses. Simple Memory: Maintains context for ongoing conversations. Pinecone Vector Store: Stores and retrieves tour packages using semantic search. Embeddings (OpenAI): Converts text data into vector embeddings for similarity search. Answer Questions with a Vector Store: Retrieves the most relevant packages from Pinecone. Send Email: Sends the AI-generated recommendations back to the customer. 🔄 Process & Flow Email Reception: The workflow starts with the Email Trigger (IMAP) node, which listens for new emails in the inbox. Classification: The Text Classifier node determines if the email is a new tour package request. Data Extraction: The Code node parses the email, extracting key details like sender, subject, and content. AI Agent Processing: The Tour Recommendation AI Agent receives the structured request and crafts a prompt for package recommendations. Vector Search: The agent queries the Pinecone Vector Store, which holds previously created tour packages, using OpenAI embeddings for semantic matching. Recommendation Generation: The AI agent selects the top 3 most relevant packages and generates a friendly, personalized response. Response Delivery: The Send Email node sends the recommendations back to the customer. 🚀 Recommendations & Improvements for Next Version Error Handling: Add error handling nodes to manage failed email parsing or AI response issues. Logging & Analytics: Integrate logging to track requests, recommendations, and customer responses for continuous improvement. Personalization: Enhance the AI agent to consider customer history or preferences for even more tailored recommendations. Multi-language Support: Add language detection and translation for international customers. Feedback Loop: Include a mechanism for customers to rate recommendations, feeding this data back into the system for improved future suggestions. Attachment Handling: Enable the workflow to process attachments (e.g., customer itineraries or preferences). Scalability: Consider batching or queueing requests if email volume increases. 💡 Conclusion This workflow demonstrates how n8n, combined with AI and vector databases, can automate and personalize customer service in the travel industry. With a few enhancements, it can become even more robust and customer-centric!

Pizza Ordering Chatbot with OpenAI - Menu, Orders & Status Tracking Introduction This workflow template is designed to automate order processing for a pizza store using OpenAI and n8n. The chatbot acts as a virtual assistant to handle customer inquiries related to menu details, order placement, and order status tracking. Features The chatbot provides an interactive experience for customers by performing the following functions: Menu Inquiry: When a customer asks about the menu, the chatbot responds with a list of available pizzas, prices, and additional options. Order Placement: If a customer places an order, the chatbot confirms order details, provides a summary, informs the customer that the order is being processed, and expresses gratitude. Order Status Tracking: If a customer asks about their order status, the chatbot retrieves details such as order date, pizza type, and quantity, providing real-time updates. Prerequisites Before setting up the workflow, ensure you have the following: OpenAI account** (Sign up here) OpenAI API key** to interact with GPT-3.5 n8n instance** running locally or on a server (Installation Guide) Configuration Steps Step 1: Set Up OpenAI API Credentials Log in to OpenAI's website. Navigate to API Keys under your account settings. Click Create API Key and copy the key for later use. Step 2: Configure OpenAI Node in n8n Open n8n and create a new workflow. Click Add Node and search for OpenAI. Select OpenAI from the list. In the OpenAI node settings, click "Create New" under the Credentials section. Enter a name for the credentials (e.g., "PizzaBot OpenAI Key"). Paste your API Key into the field. Click Save. Step 3: Set Up the Chatbot Logic Connect the AI Agent Builder Node to the OpenAI Node and HTTP Request Node. Configure the OpenAI Node with the following settings: Model: gpt-3.5-turbo Prompt: Provide dynamic text based on customer inquiries (e.g., "List available pizzas," "Place an order for Margherita pizza," "Check my order status"). Temperature: Adjust based on desired creativity (recommended: 0.7). Max Tokens: Limit response length (recommended: 150). Add multiple HTTP Request Node: For Get Products: Fetch stored menu data and return details. For Order Product: Capture order details, generate an order ID, and confirm with the customer. For Get Order: Retrieve order details based on the order ID and display progress. Step 4: Testing and Deployment Click Execute Workflow to test the chatbot. Open the Chat Message node, then copy the chat URL to access the chatbot in your browser. Interact with the chatbot by asking different queries (e.g., "What pizzas do you have?" or "I want to order a Pepperoni pizza"). Verify responses and adjust prompts or configurations as needed. Deploy the workflow and integrate it with a messaging platform (e.g., Telegram, WhatsApp, or a website chatbot). Conclusion This n8n workflow enables a fully functional pizza ordering chatbot using OpenAI's GPT-3.5. Customers can view menus, place orders, and track their order status efficiently. You can further customize the chatbot by refining prompts, adding new features, or integrating with external databases for order management. 🚀 Happy automating!

This workflow helps digital marketers and outreach specialists automate the research and creation of cold email icebreakers for local businesses. What it does: Starts with a Form Trigger, where you input a search keyword (e.g., “Dentist in New York”). Uses Dumpling AI’s Google Maps API to search for local businesses matching the keyword. Extracts individual business data, including website URLs. Sends each website to Dumpling AI to extract: A website summary for personalization An email address (if available) Sends the summary and business info to GPT-4 via OpenAI to write a short, warm, and customized icebreaker message. Filters out results with missing email addresses. Logs the business name, email, website, phone number, website summary, and generated icebreaker into Google Sheets. Optionally pushes the lead and personalization to Instantly.ai for automated cold outreach. Tools Used: Form Trigger (n8n) Dumpling AI (Search & Extraction APIs) OpenAI GPT-4 (via LangChain Node) Google Sheets Instantly.ai (optional lead delivery) 🛠️ How to Customize the Workflow Change the search region or business type:* Adjust the default keyword in the *Form Trigger** or connect a different input source (like Google Sheets). Customize the prompt:* Modify the *GPT-4 node prompt** to match your agency tone or outreach style. Add or remove data fields:* Edit the *Google Sheets node** to store additional business data or remove unnecessary ones. Connect to your CRM or outreach tool:* Replace or extend the *Instantly API node** with your own CRM (e.g., HubSpot, Close, Pipedrive) using HTTP Request or native integrations. Control batching size:* The *Split In Batches node** is set to 2 by default. You can increase this to speed up processing or reduce it to avoid rate limits. This automation is ideal for sales teams, digital marketing freelancers, and agencies who want to scale lead generation while keeping emails personal and relevant.

Gmail Daily Summary Scheduler - Template Description Never miss important emails again! This intelligent automation runs every morning at 8 AM to analyze your Gmail inbox from the past 24 hours and delivers a comprehensive summary powered by Google Gemini AI. 🚀 What it does: Automatically triggers daily at 8 AM (customizable) Fetches Gmail emails from the last 24 hours AI analyzes all emails to identify themes and key updates Highlights priority emails with reasons why they're important Delivers structured output in consistent JSON format 💡 Perfect for: Busy professionals managing high email volumes Team leads who need quick inbox overviews Anyone wanting to prioritize email responses efficiently Remote workers staying on top of communications 🎯 Key Features: Smart filtering - Only processes emails from the last 24 hours AI-powered analysis - Uses Google Gemini for intelligent summaries Priority detection - Identifies urgent, time-sensitive emails Consistent output - Structured JSON with summary and highlights Fully automated - Set it and forget it 📋 Sample Output: Summary: "Today's emails covered 3 project updates, 2 meeting requests, and 1 urgent client issue requiring immediate attention." Important Emails: Subject: "Project Deadline Extension Request" | Sender: client@company.com | Reason: Client requesting timeline change for major deliverable due this week Subject: "Tomorrow's Board Meeting Moved" | Sender: assistant@office.com | Reason: Last-minute schedule change requiring immediate calendar adjustment 🛠 Prerequisites: Gmail account with API access Google Gemini API credentials Basic n8n knowledge for credential setup ⚙️ Easy to Customize: Change schedule time (default: 8 AM daily) Adjust time window (default: 24 hours) Modify AI analysis focus Add email filters by sender, subject, etc. Extend with notifications (Slack, email, etc.) 🔒 Privacy Note: This workflow processes email content through Google Gemini API. Ensure compliance with your organization's data policies. Save hours of manual email sorting every week! Import this template and start getting intelligent email summaries delivered automatically every morning.

This N8N template demonstrates how to use our tool to collect key information from any YouTube channel - including title, description, custom URL, stats (views, subscribers, videos), creation date, country, keywords, thumbnails, and channel ID. Everything is fetched and saved directly in a linked Google Sheet. Use cases are many: Whether you're part of an MCN or YouTube channel network, a digital marketing agency, an influencer analyst, or a growth-focused YouTube consultant, this tool helps you instantly access detailed channel data for scouting, benchmarking, and strategic planning. It's perfect for competitive research, brand vetting, or building your next performance dashboard. How It Works The workflow starts when you manually click Test Workflow or Execute Workflow in N8N. It reads through the list of full channel URLs or custom channel URLs from the Channel URLs tab in a connected Google Sheet. Only the URLs marked with the Ready status will be processed. The tool loops through each row and prepares the necessary data for the YouTube API call later. A Switch node detects the URL type of each input (whether it's a full or custom channel URL) and routes it accordingly. Based on the input type, the appropriate YouTube API endpoint is triggered to fetch channel metrics. It checks whether the API call is successful before continuing: If successful, the fetched data is written back to the connected Google Sheet in the same row and the row's status is updated to Finished. If it fails, the row's status is updated to Error. How To Use Download the workflow package. Import the workflow package into your N8N interface. Duplicate the YouTube - Get Channel Information Google Sheet template into your Google Sheets account. Set up Google Cloud Console credentials in the following nodes in N8N, ensuring enabled access and suitable rights to Google Sheets and YouTube services: For Google Sheets access, ensure each node is properly connected to the correct tab in your connected Google Sheet template: Node Google Sheets - Get Channel URLs → connected to Tab Channel URLs; Node Google Sheets - Update Data → connected to Tab Channel URLs; Node Google Sheets - Update Data - Error → connected to Tab Channel URLs. For YouTube access, set up a GET method to connect to YouTube API in the following nodes: Node HTTP Request - Get Comments For Video URLs 1; Node HTTP Request - Get Comments For Video URLs 2. In your connected Google Sheet, enter the full or custom channel URLs that you want to crawl and set the rows' status to Ready. Run the workflow by clicking Execute Workflow or Test Workflow in N8N. View the results in your Google Sheet: Successful fetches will update channel data in the same row in Channel URLs tab and the row's status is updated to Finished; otherwise, the row's status will be changed to Error. Requirements Basic setup in Google Cloud Console (OAuth or API Key method enabled) with enabled access to YouTube and Google Sheets. How To Customize By default, the workflow is manually triggered in N8N. However, you can automate the process by adding a Google Sheets trigger that monitors new entries in your YouTube – Get Channel Information template and starts the workflow automatically. Need Help? Join our community on different platforms for support, inspiration and tips from others. Website: https://www.agentcircle.ai/ Etsy: https://www.etsy.com/shop/AgentCircle Gumroad: http://agentcircle.gumroad.com/ Discord Global: https://discord.gg/d8SkCzKwnP FB Page Global: https://www.facebook.com/agentcircle/ FB Group Global: https://www.facebook.com/groups/aiagentcircle/ X: https://x.com/agent_circle YouTube: https://www.youtube.com/@agentcircle LinkedIn: https://www.linkedin.com/company/agentcircle

Who is this for? This workflow is ideal for sales teams, marketers, and virtual assistants who manage outbound campaigns and want to improve their cold outreach personalization. It helps automate the research and writing process for each lead, saving time while improving quality. What problem is this workflow solving? Cold outreach often lacks personalization because manually reviewing each lead's website takes time. This workflow eliminates that bottleneck by using AI to auto-generate personalized icebreakers, summaries, and outreach emails based on a lead’s website—without human research. What this workflow does This n8n workflow runs on a schedule and pulls leads from Airtable who don't yet have an "Ice breaker" field filled out. For each lead, it does the following: Trigger: Scheduled daily via the Run Daily to Process New Leads node. Search Airtable: Finds leads in Airtable where the Ice breaker field is empty using the Search Cold Leads Without Icebreaker node. Split in Batches: Iterates through each lead one by one using Loop Through Each Lead. Rate Limiting: Waits briefly before each request using Wait Before Making Request to avoid rate limits. Scrape Website: Sends each lead’s website to Dumpling AI's /scrape endpoint via the Scrape Lead Website with Dumpling AI HTTP request. Generate AI Copy: Sends the scraped content to GPT-4o using the Generate Icebreaker, Summary & Email (GPT-4o) node. It asks the LLM to create: A short personalized icebreaker A 2–3 line website summary A short email body for cold outreach Save Results: Updates the original Airtable record with the generated content using the Save AI Output Back to Airtable node. Sticky Note: Provides an overview of the workflow and usage instructions for future editors or collaborators. This loop continues for all leads found, updating Airtable with fresh AI-generated outreach content. Integration Requirements Airtable (Personal Access Token) Dumpling AI API Key (Header Auth) OpenAI (GPT-4o)

This n8n workflow allows you to update user roles in Zammad based on data from an Excel file. The workflow automates role assignments, ensuring efficient and consistent updates. Features Excel Integration**: Import user data from an Excel file containing emails and role assignments. Dynamic Updates**: Match Zammad users by email and update their roles. Error Handling**: Continue workflow execution even if some updates fail. Customizable Variables**: Configure Zammad API URL, API key, and Excel file URL. Usage Import the Workflow: Upload the provided .json file into your n8n instance. Set Variables: zammad_base_url: Your Zammad instance URL. excel_source_url: URL of the Excel file containing user data. Authentication for Zammad Create in the Node "Find Zammad User by email" and "Update User Roles" a Header Auth Authentication Name**: Authorization Value**: Bearer <put here your zammad api token> Run the Workflow: Execute the workflow to update user roles based on the Excel data. Issues and Suggestions For issues or suggestions, visit the GitHub Repository.

The Agent Decisioner is a dynamic, AI-powered routing system that automatically selects the most appropriate large language model (LLM) to respond to a user's query based on the query’s content and purpose. This workflow ensures dynamic, optimized AI responses by intelligently routing queries to the best-suited model. Advantages 🔁 Automatic Model Routing:** Automatically selects the best model for the job, improving efficiency and relevance of responses. 🎯 Optimized Use of Resources:** Avoids overuse of expensive models like GPT-4 by routing simpler queries to lightweight models. 📚 Model-Aware Reasoning:** Uses detailed metadata about model capabilities (e.g., reasoning, coding, web search) for intelligent selection. 📥 Modular and Extendable:** Easy to integrate with other tools or expand by adding more models or custom decision logic. 👨‍💻 Ideal for RAG and Multi-Agent Systems:** Can serve as the brain behind more complex agent frameworks or Retrieval-Augmented Generation pipelines. How It Works Chat Trigger: The workflow starts when a user sends a message, triggering the Routing Agent. Model Selection: The AI Agent analyzes the query and selects the best-suited model from the available options (e.g., Claude 3.7 Sonnet for coding, Perplexity/Sonar for web searches, GPT-4o Mini for reasoning). Structured Output: The agent returns a JSON response with the user’s prompt and the chosen model. Execution: The selected model processes the query and generates a response, ensuring optimal performance for the task. Set Up Steps Configure Nodes: Chat Trigger: Set up the webhook to receive user messages. Routing Agent (AI Agent): Define the system message with model strengths and JSON output rules. OpenRouter Chat Model: Connect to OpenRouter for model access. Structured Output Parser: Ensure it validates the JSON response format (prompt + model). Execution Agent (AI Agent1): Configure it to forward the prompt to the selected model. Connect Nodes: Link the Chat Trigger to the Routing Agent. Connect the OpenRouter Chat Model and Output Parser to the Routing Agent. Route the parsed JSON to the Execution Agent, which uses the chosen model via OpenRouter Chat Model1. Credentials: Ensure OpenRouter API credentials are correctly set for both chat model nodes. Test & Deploy: Activate the workflow and test with sample queries to verify model selection logic. Adjust the routing rules if needed for better accuracy. Need help customizing? Contact me for consulting and support or add me on Linkedin.

Description This workflow automatically generates comprehensive property market reports by scraping real estate listings and market data from multiple sources. It helps real estate professionals save time and provide data-driven insights to clients without manual research. Overview This workflow automatically generates property market reports by scraping real estate listings and market data. It uses Bright Data to access multiple real estate websites and compiles the data into comprehensive reports. Tools Used n8n:** The automation platform that orchestrates the workflow. Bright Data:** For scraping real estate websites and property data without getting blocked. Spreadsheets/Databases:** For storing and analyzing property data. Document Generation:** For creating professional PDF reports. How to Install Import the Workflow: Download the .json file and import it into your n8n instance. Configure Bright Data: Add your Bright Data credentials to the Bright Data node. Set Up Data Storage: Configure where you want to store the property data. Customize: Specify locations, property types, and report format. Use Cases Real Estate Agents:** Generate market reports for clients. Property Investors:** Track market trends in target areas. Market Analysts:** Automate data collection for property market analysis. Connect with Me Website:** https://www.nofluff.online YouTube:** https://www.youtube.com/@YaronBeen/videos LinkedIn:** https://www.linkedin.com/in/yaronbeen/ Get Bright Data:** https://get.brightdata.com/1tndi4600b25 (Using this link supports my free workflows with a small commission) #n8n #automation #realestate #propertymarket #brightdata #marketreports #propertyanalysis #realestatedata #markettrends #propertyinvestment #n8nworkflow #workflow #nocode #realestateanalysis #propertyreports #realestateintelligence #marketresearch #propertyscraping #realestateautomation #investmentanalysis #propertytrends #datadriven #realestatetech #propertyinsights #marketanalysis #realestateinvesting