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Case Study

How AI Agents Solved Lead Generation for a Zero-Budget Marketplace

Turning public county data into qualified landowner leads — automatically.

ClientReserved
IndustryHunting & Land Access
FocusAI Automation
01

The Problem

Reserved is a two-sided marketplace focused on private land access. To grow, it needed to onboard landowners at scale — but faced a familiar challenge.

  • No paid advertising budget
  • No existing lead list
  • Highly fragmented, offline audience
  • Geographic precision was critical

The customers existed. Reaching them efficiently did not.

02

Why Traditional Solutions Failed

Standard lead generation approaches created friction instead of leverage.

  • Purchased lead lists were expensive and outdated
  • CRMs organized contacts but didn't generate them
  • Manual research was slow and inconsistent
  • Outsourced SDRs were costly and hard to control

Tools created more work — not outcomes.

03

The Insight

The problem wasn't access to data. Counties already publish detailed, up-to-date land ownership records.

The real challenge was operationalizing that data — turning raw records into real conversations, consistently and automatically.

04

The Solution

Thompson Software Design built an automated lead generation system designed to do the work a full lead generation team would normally handle.

01Ingest county-level public data
02Filter and enrich landowner records
03Score leads based on relevance
04Generate personalized outreach
05Run automated follow-ups
06Track responses and engagement

Powered by autonomous AI agents operating continuously.

05

The Results

  • Zero paid advertising spend
  • County-by-county data ingestion at scale
  • Consistent outbound outreach without manual input
  • Massive time savings vs. manual research
  • Repeatable, scalable acquisition pipeline

Within weeks, the system was ingesting county-level records and running continuous outbound outreach without manual intervention.

06

Why This Matters

This system is not specific to hunting or land.

Any business with high-value customers hiding in public, geographic, or registry-based data can apply the same approach.

If your customers already exist in public data, we should talk.

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