Real Estate · Manufactured Housing · Off-Market Sourcing
Manufactured-housing parks, sourced and scored across 197 counties.
How a Midwest manufactured-housing investor replaced manual park hunting with an automated sourcing, scoring, and owner-resolution engine, with full ownership and governance of the system on their own infrastructure.
197 counties refreshed weekly into a scored, owner-resolved acquisition pipeline.
The Challenge
Manufactured-housing parks rarely trade on the open market, and the ones worth acquiring are spread thin across hundreds of rural counties. The investor was hunting them by hand: pulling county lists, guessing which parks were viable, and chasing owners whose contact details were out of date or wrong. Every step was manual, coverage was inconsistent, and the team had no reliable way to rank where to spend its limited outreach hours. The best parks were either missed or reached after someone else.
Pain Points:
- Viable parks scattered across hundreds of rural counties with no consistent source.
- No way to rank which parks deserved outreach, so effort went to whoever was easiest to find.
- Owner contact details that were stale, missing, or wrong, stalling outreach.
- Brokers’ opinions of value and offering memos assembled by hand, one deal at a time.
Our Approach
We built an end-to-end acquisition engine, delivered as a system the investor owns and governs on their own infrastructure:
Multi-County Park Sourcing
A weekly refresh across 197 counties pulls candidate parks into one normalized pipeline, replacing ad hoc county-by-county lookups.
14-Signal Scoring
Each park is scored on fourteen signals so the highest-potential acquisitions rank first and the team’s outreach hours go where they matter.
Owner Resolution & Skip-Trace
Owners are resolved and skip-traced, then verified against a maintained Known-Parks registry, so outreach reaches the right decision-maker the first time.
BOV/OM & Market-Report Generator
A broker’s opinion of value, offering memo, and market report generate on demand from the same data, turning a day of assembly into minutes.
The System in Action
Stack: Python sourcing pipelines + Supabase (Postgres) + skip-trace & verification services + on-demand document generation, deployed on the client's infrastructure
Results
County Coverage
ad hoc, county by county
197 counties refreshed weekly
Deal Ranking
gut feel
14-signal scoring
Owner Outreach
stale, missing contacts
resolved & verified
BOV / OM Output
a day of manual assembly
generated on demand