Automate real estate construction site discovery with 99acres email scraper
This n8n workflow helps users easily discover nearby residential construction projects by automatically scraping and analyzing property listings from 99acres and other real estate platforms. Users can send an email with their location preferences and receive a curated list of available properties with detailed information, including pricing, area, possession dates, and construction status.
Good to know
- The workflow focuses specifically on residential construction projects and active developments
- Property data is scraped in real-time to ensure the most current information
- Results are automatically formatted and structured for easy reading
- The system handles multiple property formats and data variations from different sources
- Fallback mechanisms ensure reliable data extraction even when website structures change
How it works
- Trigger: New Email - Detects incoming emails with property search requests and extracts location preferences from email content
- Extract Area & City - Parses the email body to identify target areas (e.g., Gota, Ahmedabad) and falls back to city-level search if specific area is not mentioned
- Scrape Construction Projects - Performs web scraping on 99acres and other property websites based on the extracted area and city information
- Parse Project Listings - Cleans and formats the scraped HTML data into structured project entries with standardized fields
- Format Project Details - Transforms all parsed projects into a consistent email-ready list format with bullet points and organized information
- Send Results to User - Delivers a professionally formatted email with the complete list of matching construction projects to the original requester
Email Format Examples
Input Email Format
To: properties@yourcompany.com
Subject: Property Search Request
Hi, I am interested in buying a flat. Can you please send me the list of available properties in Gota, Ahmedabad?
Output Email Example
Subject: 🏘️ Property Search Results: 4 Projects Found in Gota, Ahmedabad
🏘️ Available Construction Projects in Gota, Ahmedabad
Search Area: Gota, Ahmedabad
Total Projects: 4
Search Date: August 4, 2025
📋 PROJECT LISTINGS:
🔷 Project 1
🏠 Name: Vivaan Oliver offers
🏢 BHK: 3 BHK
💰 Price: N/A
📐 Area: 851.0 Sq.Ft
🗓️ Possession: August 2025
📊 Status: under construction
📍 Location: Thaltej, Ahmedabad West
🕒 Scraped Date: 2025-08-04
-------------------------------------------
🔷 Project 2
🏠 Name: Vivaan Oliver offers
🏢 BHK: 3 BHK
💰 Price: Price on Request
📐 Area: 891 Sq Ft
🗓️ Possession: N/A
📊 Status: Under Construction
📍 Location: Thaltej, Ahmedabad West
🕒 Scraped Date: 2025-08-04
-------------------------------------------
🔷 Project 3
🏠 Name: It offers an exclusive range of
🏢 BHK: 3 BHK
💰 Price: N/A
📐 Area: 250 Sq.Ft
🗓️ Possession: 0 2250
📊 Status: Under Construction
📍 Location: Thaltej, Ahmedabad West
🕒 Scraped Date: 2025-08-04
-------------------------------------------
🔷 Project 4
🏠 Name: N/A
🏢 BHK: 2 BHK
💰 Price: N/A
📐 Area: N/A
🗓️ Possession: N/A
📊 Status: N/A
📍 Location: Thaltej, Ahmedabad West
💡 Next Steps:
• Contact builders directly for detailed pricing and floor plans
• Schedule site visits to shortlisted properties
• Verify possession timelines and construction progress
• Compare amenities and location advantages
📞 For more information or specific requirements, reply to this email.
How to use
Setup Instructions
- Import the workflow into your n8n instance
- Configure Email Credentials:
- Set up email trigger for incoming property requests
- Set up SMTP credentials for sending property listings
- Configure Web Scraping:
- Ensure proper headers and user agents for 99acres access
- Set up fallback mechanisms for different property websites
- Test the workflow with sample property search emails
Sending Property Search Requests
- Send an email to your configured property search address
- Include location details in natural language (e.g., "Gota, Ahmedabad")
- Optionally specify preferences like BHK, budget, or amenities
- Receive detailed property listings within minutes
Requirements
- n8n instance (cloud or self-hosted) with web scraping capabilities
- Email account with IMAP/SMTP access for automated communication
- Reliable internet connection for real-time property data scraping
- Valid target websites (99acres, MagicBricks, etc.) access
Troubleshooting
- No properties found: Verify area spelling and check if the location has active listings
- Scraping errors: Update user agents and headers if websites block requests
- Duplicate results: Implement better deduplication logic based on property names and locations
- Email parsing issues: Test with various email formats and improve regex patterns
- Website structure changes: Implement fallback parsers and regular monitoring of scraping success rates
n8n Email Processing and External API Interaction Workflow
This n8n workflow automates the process of reacting to incoming emails by making an HTTP request to an external API and then sending a response email. It acts as a bridge between your email inbox and an external service, allowing for custom actions to be triggered by specific email events.
What it does
This workflow simplifies and automates the following steps:
- Monitors Incoming Emails: It continuously checks a specified IMAP email account for new emails.
- Triggers on New Email: When a new email arrives, the workflow is activated.
- Executes Custom Logic (Placeholder): A
Sticky NoteandCodenode are present, suggesting a place for custom logic or data manipulation based on the incoming email content. Currently, these are placeholders and do not perform active operations in the provided JSON. - Makes an HTTP Request: It sends an HTTP request to an external API endpoint. This step is where the core action triggered by the email would typically occur (e.g., sending data, initiating a process, querying information).
- Sends a Response Email: After the HTTP request is made, the workflow sends an email. This could be used to confirm the action, provide results from the API call, or notify relevant parties.
Prerequisites/Requirements
To use this workflow, you will need:
- IMAP Email Account: An IMAP-enabled email account for the "Email Trigger (IMAP)" node to monitor. You'll need the IMAP server details and credentials.
- SMTP Email Account: An SMTP-enabled email account for the "Send Email" node to send outgoing emails. You'll need the SMTP server details and credentials.
- External API Endpoint: The URL and any necessary authentication/parameters for the "HTTP Request" node to interact with your desired external service.
Setup/Usage
- Import the Workflow: Import the provided JSON into your n8n instance.
- Configure Credentials:
- Email Trigger (IMAP): Set up an IMAP credential for the email account you wish to monitor.
- Send Email: Set up an SMTP credential for the email account you wish to send emails from.
- Configure "HTTP Request" Node:
- Update the
URL,Method(e.g., GET, POST),Headers, andBodyof the HTTP request to match the requirements of your external API. - If the API requires authentication, configure it within this node (e.g., Basic Auth, OAuth2, API Key).
- Update the
- Customize "Code" Node (Optional): If you need to process or transform the incoming email data before making the HTTP request, or process the HTTP response before sending an email, add your JavaScript logic to the "Code" node.
- Configure "Send Email" Node:
- Specify the
To,From,Subject, andBodyfor the outgoing email. You can use expressions to dynamically include data from the incoming email or the HTTP request response.
- Specify the
- Activate the Workflow: Once configured, activate the workflow to start monitoring your email inbox.
Related Templates
Track competitor SEO keywords with Decodo + GPT-4.1-mini + Google Sheets
This workflow automates competitor keyword research using OpenAI LLM and Decodo for intelligent web scraping. Who this is for SEO specialists, content strategists, and growth marketers who want to automate keyword research and competitive intelligence. Marketing analysts managing multiple clients or websites who need consistent SEO tracking without manual data pulls. Agencies or automation engineers using Google Sheets as an SEO data dashboard for keyword monitoring and reporting. What problem this workflow solves Tracking competitor keywords manually is slow and inconsistent. Most SEO tools provide limited API access or lack contextual keyword analysis. This workflow solves that by: Automatically scraping any competitor’s webpage with Decodo. Using OpenAI GPT-4.1-mini to interpret keyword intent, density, and semantic focus. Storing structured keyword insights directly in Google Sheets for ongoing tracking and trend analysis. What this workflow does Trigger — Manually start the workflow or schedule it to run periodically. Input Setup — Define the website URL and target country (e.g., https://dev.to, france). Data Scraping (Decodo) — Fetch competitor web content and metadata. Keyword Analysis (OpenAI GPT-4.1-mini) Extract primary and secondary keywords. Identify focus topics and semantic entities. Generate a keyword density summary and SEO strength score. Recommend optimization and internal linking opportunities. Data Structuring — Clean and convert GPT output into JSON format. Data Storage (Google Sheets) — Append structured keyword data to a Google Sheet for long-term tracking. Setup Prerequisites If you are new to Decode, please signup on this link visit.decodo.com n8n account with workflow editor access Decodo API credentials OpenAI API key Google Sheets account connected via OAuth2 Make sure to install the Decodo Community node. Create a Google Sheet Add columns for: primarykeywords, seostrengthscore, keyworddensity_summary, etc. Share with your n8n Google account. Connect Credentials Add credentials for: Decodo API credentials - You need to register, login and obtain the Basic Authentication Token via Decodo Dashboard OpenAI API (for GPT-4o-mini) Google Sheets OAuth2 Configure Input Fields Edit the “Set Input Fields” node to set your target site and region. Run the Workflow Click Execute Workflow in n8n. View structured results in your connected Google Sheet. How to customize this workflow Track Multiple Competitors → Use a Google Sheet or CSV list of URLs; loop through them using the Split In Batches node. Add Language Detection → Add a Gemini or GPT node before keyword analysis to detect content language and adjust prompts. Enhance the SEO Report → Expand the GPT prompt to include backlink insights, metadata optimization, or readability checks. Integrate Visualization → Connect your Google Sheet to Looker Studio for SEO performance dashboards. Schedule Auto-Runs → Use the Cron Node to run weekly or monthly for competitor keyword refreshes. Summary This workflow automates competitor keyword research using: Decodo for intelligent web scraping OpenAI GPT-4.1-mini for keyword and SEO analysis Google Sheets for live tracking and reporting It’s a complete AI-powered SEO intelligence pipeline ideal for teams that want actionable insights on keyword gaps, optimization opportunities, and content focus trends, without relying on expensive SEO SaaS tools.
By Ranjan DailataGenerate song lyrics and music from text prompts using OpenAI and Fal.ai Minimax
Spark your creativity instantly in any chat—turn a simple prompt like "heartbreak ballad" into original, full-length lyrics and a professional AI-generated music track, all without leaving your conversation. 📋 What This Template Does This chat-triggered workflow harnesses AI to generate detailed, genre-matched song lyrics (at least 600 characters) from user messages, then queues them for music synthesis via Fal.ai's minimax-music model. It polls asynchronously until the track is ready, delivering lyrics and audio URL back in chat. Crafts original, structured lyrics with verses, choruses, and bridges using OpenAI Submits to Fal.ai for melody, instrumentation, and vocals aligned to the style Handles long-running generations with smart looping and status checks Returns complete song package (lyrics + audio link) for seamless sharing 🔧 Prerequisites n8n account (self-hosted or cloud with chat integration enabled) OpenAI account with API access for GPT models Fal.ai account for AI music generation 🔑 Required Credentials OpenAI API Setup Go to platform.openai.com → API keys (sidebar) Click "Create new secret key" → Name it (e.g., "n8n Songwriter") Copy the key and add to n8n as "OpenAI API" credential type Test by sending a simple chat completion request Fal.ai HTTP Header Auth Setup Sign up at fal.ai → Dashboard → API Keys Generate a new API key → Copy it In n8n, create "HTTP Header Auth" credential: Name="Fal.ai", Header Name="Authorization", Header Value="Key [Your API Key]" Test with a simple GET to their queue endpoint (e.g., /status) ⚙️ Configuration Steps Import the workflow JSON into your n8n instance Assign OpenAI API credentials to the "OpenAI Chat Model" node Assign Fal.ai HTTP Header Auth to the "Generate Music Track", "Check Generation Status", and "Fetch Final Result" nodes Activate the workflow—chat trigger will appear in your n8n chat interface Test by messaging: "Create an upbeat pop song about road trips" 🎯 Use Cases Content Creators: YouTubers generating custom jingles for videos on the fly, streamlining production from idea to audio export Educators: Music teachers using chat prompts to create era-specific folk tunes for classroom discussions, fostering interactive learning Gift Personalization: Friends crafting anniversary R&B tracks from shared memories via quick chats, delivering emotional audio surprises Artist Brainstorming: Songwriters prototyping hip-hop beats in real-time during sessions, accelerating collaboration and iteration ⚠️ Troubleshooting Invalid JSON from AI Agent: Ensure the system prompt stresses valid JSON; test the agent standalone with a sample query Music Generation Fails (401/403): Verify Fal.ai API key has minimax-music access; check usage quotas in dashboard Status Polling Loops Indefinitely: Bump wait time to 45-60s for complex tracks; inspect fal.ai queue logs for bottlenecks Lyrics Under 600 Characters: Tweak agent prompt to enforce fuller structures like [V1][C][V2][B][C]; verify output length in executions
By Daniel NkenchoAutomate Dutch Public Procurement Data Collection with TenderNed
TenderNed Public Procurement What This Workflow Does This workflow automates the collection of public procurement data from TenderNed (the official Dutch tender platform). It: Fetches the latest tender publications from the TenderNed API Retrieves detailed information in both XML and JSON formats for each tender Parses and extracts key information like organization names, titles, descriptions, and reference numbers Filters results based on your custom criteria Stores the data in a database for easy querying and analysis Setup Instructions This template comes with sticky notes providing step-by-step instructions in Dutch and various query options you can customize. Prerequisites TenderNed API Access - Register at TenderNed for API credentials Configuration Steps Set up TenderNed credentials: Add HTTP Basic Auth credentials with your TenderNed API username and password Apply these credentials to the three HTTP Request nodes: "Tenderned Publicaties" "Haal XML Details" "Haal JSON Details" Customize filters: Modify the "Filter op ..." node to match your specific requirements Examples: specific organizations, contract values, regions, etc. How It Works Step 1: Trigger The workflow can be triggered either manually for testing or automatically on a daily schedule. Step 2: Fetch Publications Makes an API call to TenderNed to retrieve a list of recent publications (up to 100 per request). Step 3: Process & Split Extracts the tender array from the response and splits it into individual items for processing. Step 4: Fetch Details For each tender, the workflow makes two parallel API calls: XML endpoint - Retrieves the complete tender documentation in XML format JSON endpoint - Fetches metadata including reference numbers and keywords Step 5: Parse & Merge Parses the XML data and merges it with the JSON metadata and batch information into a single data structure. Step 6: Extract Fields Maps the raw API data to clean, structured fields including: Publication ID and date Organization name Tender title and description Reference numbers (kenmerk, TED number) Step 7: Filter Applies your custom filter criteria to focus on relevant tenders only. Step 8: Store Inserts the processed data into your database for storage and future analysis. Customization Tips Modify API Parameters In the "Tenderned Publicaties" node, you can adjust: offset: Starting position for pagination size: Number of results per request (max 100) Add query parameters for date ranges, status filters, etc. Add More Fields Extend the "Splits Alle Velden" node to extract additional fields from the XML/JSON data, such as: Contract value estimates Deadline dates CPV codes (procurement classification) Contact information Integrate Notifications Add a Slack, Email, or Discord node after the filter to get notified about new matching tenders. Incremental Updates Modify the workflow to only fetch new tenders by: Storing the last execution timestamp Adding date filters to the API query Only processing publications newer than the last run Troubleshooting No data returned? Verify your TenderNed API credentials are correct Check that you have setup youre filter proper Need help setting this up or interested in a complete tender analysis solution? Get in touch 🔗 LinkedIn – Wessel Bulte
By Wessel Bulte