buyer-prospector

Buyer Prospector

Pull active real estate buyer data for any US county from a nationwide database of 84,000+ buyer records across 1,471 counties. The skill filters buyers by the user's target county, categorizes entities, and walks through a structured research workflow to identify the actual decision-makers behind LLCs, trusts, and corporations — turning raw transaction data into a skip-traceable buyers list.

When to Use

• User wants to find active buyers in a specific county/state
• Building a buyers list for a new market
• Need to identify who's buying properties in an area
• Prospecting cash buyers for wholesaling deals
• Researching investor activity in a target county

What the User Needs to Provide

At minimum, the user needs to tell you:

1. County name (e.g., "Knox", "Harris", "Maricopa")
2. State (e.g., "TN", "TX", "AZ")

Optional preferences:

• Minimum purchase threshold (default: 2 purchases in 6 months)
• How many records to research (batch size)
• Whether they want the full research workflow or just the analysis

Workflow Overview

1. Filter nationwide data for the target county
2. Run entity analysis (categorize + prioritize)
3. Review results with user
4. Research decision-makers for High priority entities
5. Update the Excel workbook with findings
6. Deliver completed buyer analysis

Step 1: Filter and Analyze

Run the analysis script on the bundled nationwide dataset. The script path is relative to this skill's directory:

python <skill-path>/scripts/analyze_buyers.py <skill-path>/data/nationwide_buyers.csv \
  --county "<county_name>" \
  --state "<state_abbrev>" \
  --output "<output_path>"

Example:

python <skill-path>/scripts/analyze_buyers.py <skill-path>/data/nationwide_buyers.csv \
  --county "Knox" \
  --state "TN" \
  --output "Knox_TN_Buyer_Analysis.xlsx"

The --min-purchases flag defaults to 2. If the user wants a broader or narrower list, adjust accordingly.

Save the output Excel file to the user's workspace so they can access it.