Back to Catalog

Revive expired real estate listings with OpenAI and Gmail follow-ups

MarthMarth
600 views
2/3/2026
Official Page

How it works

  1. This automation helps revive expired property listings by:
  2. Reading listing data from a Google Sheet that tracks all properties.
  3. Filtering listings where the last_activity date is older than 30 days.
  4. Generating a personalized email using OpenAI (GPT-4) to re-engage the owner.
  5. Sending the email to the property owner using Gmail or SMTP.
  6. (Optional): Updating the listing's status to followed_up in the Sheet once the email is sent.
  7. This workflow ensures no opportunity is missed by proactively reactivating cold leads.

Set Up Steps

  1. Prepare your Google Sheet

    • Create a Google Sheet with these columns:
      • title, owner_name, email, property_type, location, last_activity
    • Fill in sample data for testing.
  2. Connect Google Sheets in n8n

    • Add a Google Sheets node.
    • Use the "Read Rows" operation to load the listing data.
  3. Filter listings inactive for 30+ days

    • Use a Set node to convert last_activity to a Date.
    • Add an IF node or Code node to check if the listing is older than 30 days.
  4. Generate email content with OpenAI

    • Add an OpenAI node.
    • Use dynamic input (e.g. owner name, property type) to create a follow-up message.
  5. Send the email

    • Add a Gmail node or SMTP node to send the email to the property owner.
  6. (Optional) Update status

    • Use a Google Sheets "Update Row" node to change the listing's status to followed_up.
  7. Test the full workflow

    • Manually trigger the workflow or schedule it to run daily/weekly.

Revive Expired Real Estate Listings with OpenAI and Gmail Follow-ups

This n8n workflow automates the process of identifying expired real estate listings, generating compelling follow-up emails using OpenAI, and sending those emails via Gmail. It helps real estate agents efficiently re-engage with potential clients whose listings have lapsed.

What it does

This workflow simplifies and automates the following steps:

  1. Triggers on a schedule: The workflow is designed to run automatically at predefined intervals.
  2. Reads data from Google Sheets: It fetches a list of real estate listings, likely including their status and contact information, from a specified Google Sheet.
  3. Filters listings: It applies a conditional check to identify listings that meet specific criteria (e.g., "expired" or "lapsed").
  4. Generates follow-up email content with OpenAI: For each filtered listing, it uses OpenAI to craft a personalized and persuasive email message aimed at reviving the listing.
  5. Sends follow-up emails via Gmail: The generated email content is then sent to the listing owner using Gmail.

Prerequisites/Requirements

To use this workflow, you will need:

  • n8n Instance: A running n8n instance.
  • Google Sheets Account: A Google account with access to Google Sheets where your real estate listing data is stored.
  • Gmail Account: A Google account with access to Gmail for sending follow-up emails.
  • OpenAI API Key: An OpenAI API key with access to their language models for generating email content.

Setup/Usage

  1. Import the workflow: Download the provided JSON and import it into your n8n instance.
  2. Configure Credentials:
    • Google Sheets: Set up a Google Sheets credential. Ensure it has access to the spreadsheet containing your listing data.
    • Gmail: Set up a Gmail credential.
    • OpenAI: Set up an OpenAI credential with your API key.
  3. Configure Google Sheets Node:
    • Specify the Spreadsheet ID and Sheet Name where your real estate listing data resides.
    • Ensure the data includes columns for listing status (e.g., "Status"), contact email (e.g., "Email"), and any other relevant details for the OpenAI prompt (e.g., "Address", "Listing Description").
  4. Configure If Node:
    • Adjust the conditions in the "If" node to accurately identify expired or lapsed listings based on your Google Sheet data (e.g., {{ $json.Status === 'Expired' }}).
  5. Configure OpenAI Node:
    • Customize the prompt to guide OpenAI in generating effective follow-up emails. You can reference data from the Google Sheets node (e.g., Write a compelling email to {{ $json.ContactName }} about their expired listing at {{ $json.Address }} to encourage them to relist.).
  6. Configure Gmail Node:
    • Map the recipient email address from your Google Sheet data (e.g., {{ $json.Email }}).
    • Map the subject and body of the email to the output of the OpenAI node.
  7. Configure Schedule Trigger:
    • Set the desired interval for the workflow to run (e.g., daily, weekly).
  8. Activate the workflow: Once configured, activate the workflow to start automating your expired listing follow-ups.

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.

Ranjan DailataBy Ranjan Dailata
161

Generate 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

Daniel NkenchoBy Daniel Nkencho
601

Automate 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

Wessel BulteBy Wessel Bulte
247