Automated Lead Scoring with MLS Data and AI
detail.loadingPreview
Automate and enhance your lead scoring process by integrating MLS data with powerful AI. This workflow ingests lead information via a webhook, leverages large language models and vector databases to analyze property details, and intelligently scores leads before logging the results directly into Google Sheets.
About This Workflow
Unlock the power of AI for your real estate lead generation with this advanced n8n workflow. Designed to automate the complex task of lead scoring using Multiple Listing Service (MLS) data, it starts by ingesting lead information through a webhook. The data is then intelligently processed: first chunked by a text splitter, then transformed into semantic embeddings using OpenAI. These embeddings are stored and queried in a Pinecone vector database, creating a dynamic, searchable knowledge base of MLS data. A sophisticated LangChain agent, powered by a HuggingFace large language model and equipped with conversational memory and vector store tools, analyzes the lead data against your MLS knowledge. Finally, the AI-generated lead scores and insights are automatically appended to a Google Sheet, providing a streamlined, data-driven approach to prioritizing your sales efforts.
Key Features
- Real-time Lead Ingestion: Trigger the workflow instantly via a webhook when new lead data is available.
- Advanced AI-Powered Data Processing: Utilizes text splitting and OpenAI embeddings to semantically understand MLS data.
- Persistent Knowledge Base for MLS Data: Stores and queries property information efficiently using Pinecone vector database.
- Intelligent Lead Scoring with LangChain Agents: Leverages large language models (HuggingFace) and an AI agent to analyze and score leads based on contextual MLS data.
- Automated Result Logging: Automatically appends lead scores and AI insights to a specified Google Sheet for easy tracking and analysis.
How To Use
- Webhook Node: Configure the
Webhooknode to listen for incoming lead data (e.g., from a CRM, website form, or other systems) at the specifiedpath. The incoming data should contain the MLS information relevant for scoring. - OpenAI Embeddings Node: Ensure you have valid OpenAI API credentials configured for the
Embeddingsnode. This node converts your textual lead data into numerical vectors for AI processing. - Pinecone Vector Store Nodes: Set up your Pinecone API credentials for both the
InsertandQuerynodes. Verify that theindexName(lead_scoring_with_mls_data) matches your Pinecone setup. TheInsertnode builds your MLS knowledge base, whileQueryretrieves relevant information. - HuggingFace Chat Node: Provide your HuggingFace API credentials to enable the
Chatnode, which powers the large language model for the AI Agent. - Agent Node: Customize the
textparameter in theAgentnode to define your specific lead scoring rules, criteria, and desired output format based on the incoming{{ $json }}data and retrieved MLS context. - Google Sheets Node: Configure your Google Sheets OAuth2 API credentials. Specify the
documentId(your Google Sheet ID) andsheetNamewhere the final lead scores and insights from the AI Agent will be logged.
Apps Used
Workflow JSON
{
"id": "10fa04dc-8bdc-49ca-b08a-4bcdc73fff50",
"name": "Automated Lead Scoring with MLS Data and AI",
"nodes": 23,
"category": "Sales",
"status": "active",
"version": "1.0.0"
}Note: This is a sample preview. The full workflow JSON contains node configurations, credentials placeholders, and execution logic.
Get This Workflow
ID: 10fa04dc-8bdc...
About the Author
DevOps_Master_X
Infrastructure Expert
Specializing in CI/CD pipelines, Docker, and Kubernetes automations.
Statistics
Related Workflows
Discover more workflows you might like
AI-Powered Upwork Proposal Automation Suite
This n8n workflow leverages AI to automate the entire freelance proposal process, from crafting personalized application text to generating professional Google Doc proposals and visual workflow diagrams. It significantly reduces manual effort, allowing freelancers to scale their client acquisition rapidly and effectively.
AI-Powered Stack Overflow Lead Generation
Unleash the power of AI to automatically scrape valuable lead data from Stack Overflow user profiles. This workflow intelligently identifies and extracts key information like names, locations, skills, and reputation, then seamlessly organizes it into your Google Sheet for effortless lead management.
Automate Local Business Outreach with AI-Powered Yelp Scraper
This workflow automates the process of scraping local business details from Yelp using AI, then leverages that data to send personalized partnership proposals via Gmail. It's perfect for sales and marketing teams looking to streamline lead generation and outreach campaigns.