Real Estate AI Lead Prospect Scoring (Microsoft Excel)

Description

This workflow fetches a list of real estate prospect leads from an Excel sheet. AI evaluates each prospect by scoring them based on Budget, Purchase Purpose, Purchase Timeline, Interest Level, and Response Speed. It uses a predefined scoring rubric to classify leads as HOT, WARM, or COLD, and provides actionable remarks.

Workflow Steps:

1. Fetch the list of lead prospects from the Excel sheet.
2. Use AI to evaluate each prospect based on the scoring rubric.
3. Compute the lead score and categorize as HOT, WARM, or COLD.
4. Return the output for each prospect in a strict JSON format with specified fields, including Customer ID, AI Lead Score, Lead Category, and Remarks.

Benefits for Customers / Users

• Enhanced prioritization – Quickly identify high-priority leads.
• Efficient follow-up – Focus resources on the most promising prospects.
• Data-driven insights – Make informed decisions with AI-backed scoring.
• Automated processing – Reduce manual effort in lead evaluation.
• Structured output – Receive results in a clear, standardized format.
• Flexible evaluation – Adapt to missing data with available metrics.

Workflow Prerequisite

1. Access to Microsoft Excel and the specific prospect sheet.
2. OpenAI API credentials.
3. Excel credentials and necessary permissions to retrieve data.

Requirements

1. Excel Sheet

Must include the following columns:

• Customer ID
• Customer Name
• Customer Phone Number
• Customer Email
• Budget Range
• Purpose of Purchase
• Timeline to Purchase
• AI Lead Score
• AI Lead Category
• Remarks

2. OpenAI Credential

• API Key access
• Proper configuration for secure access

3. Excel Credential

• Permission to access and retrieve data from necessary sheets