I built a free 10-park DFW mobile home community sample — what data would you add?

Question

Hi everyone!  I'm a Fort Worth–based investor who owns two waterfront Texas short-term rentals and spends a lot of time evaluating niche real estate and small-business opportunities.

One frustration I kept running into with manufactured-home communities was fragmented research. So I built a free 10-community DFW sample with fields such as location, community type, estimated lot count, occupancy indicators, rent information where publicly available, demand drivers, and investor signals.

The file is compiled from public sources. Estimates are labeled, and I would not treat it as a substitute for underwriting, title work, or direct verification.

I'm sharing the sample because I'd value feedback from operators and buyers:
• Which fields would actually help you screen a deal?
• What would make a dataset like this trustworthy enough to use?
• Are there fields you would remove?

If anyone wants the sample, I can't attach here but I can send it over. No pitch required and honest criticism is useful!

Joshua Moore · Answer

Really appreciate this — most useful feedback I've gotten so far.

The provenance point hits home. Every record currently has methodology notes and sources, but you're right that it's not per-field source + date + confidence. That's a clear upgrade and I'm building it into the next tranche.

On the decision-data side: the current edition has owner/operator where determinable, years in business, and rent info where public — but transaction history, debt clues, and rent-change history are gaps, honestly. If you had to pick three fields to add first, which would they be? I want to prioritize whatever actually changes a go/no-go decision.

Happy to send you the sample if you want to see the current structure.

Michael Eskenasy · Answer

Joshua, I think the biggest upgrade is moving from property data to decision data.

I’d want to know not just lot count and occupancy, but who owns it, when they bought it, debt/financing clues, last sale price, assessed value trajectory, utility structure, infrastructure age, rent-change history, nearby supply, zoning constraints, flood/environmental exposure, and what has changed around the park over time.

The trust piece is provenance. Every important field should show source + date + confidence level, so an investor can tell the difference between a county record, an operator statement, and an estimate.

That’s actually close to how we think about real-estate intelligence: the raw dataset is useful, but the real value comes when you can reconstruct the asset chronologically and see what changed, who acted, and where the pressure points are.

You’re building in the right direction.

Joshua Moore · Answer

Adding a peek at what one record looks like:

Harston Woods — Euless, TX (Tarrant County)

• 413 lots, operating since 2000
• Lot rent: $590–$715/mo (varies by source)
• Occupancy: ~90% (estimated — I show my work in the methodology column)
• Projected annual revenue: ~$2.88M (372 occupied lots x $645 avg x 12)
• Operator: KCWS Homes, LLC / Champion Homes, with new-home sales active on site
• Demand drivers: minutes from DFW Airport, SH-183/360 corridor, HEB ISD

Every record in the sample has the same 18 columns: lot count, rent, occupancy estimate, owner/operator, phone, park type, investor signals, demand drivers, and the source behind each fact. Where I estimated, it's labeled as an estimate.

Happy to send the full 10-park file to anyone who wants to poke holes in it — just reply here or DM me.