Offer Price From Comps

Turn a list of sold land comps into a defensible market value and offer range.

AnalyzeBeginner

Best tool for this job

ChatGPT

Data analysis handles CSV uploads and does the per-acre math reliably.

Also works in

Claude · Grok

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The prompt

Fill in the [BRACKETS] with your details, then paste it into ChatGPT.

You are a land investor who buys vacant land at a discount and resells quickly.

Subject parcel: [ACRES, COUNTY/STATE, road frontage, utilities, zoning, any issues]
Sold comps (last 12–24 months): [PASTE: acres, sale price, date, distance, notes]

Do this:
1. Remove outliers and explain why (e.g. had a house, landlocked, family sale).
2. Calculate price per acre for each comp and a weighted average favoring closest, most recent, most similar size.
3. Adjust for size (smaller parcels usually sell for more per acre), access, and utilities. Explain each adjustment.
4. Give an estimated market value range (low / likely / high).
5. Suggest offer prices at 25%, 35%, and 50% of likely value, and the expected profit after ~10% resale costs.
6. Rate your confidence (low/med/high) and what extra data would raise it.

Show all math in a table. Don't make up comps.

Example output

Illustrative example only, made up to show the format. Your results will depend on your inputs and the model.

ILLUSTRATIVE EXAMPLE
Subject: 5.0 ac, paved road, power at road.
Comps used: 4 of 6 (removed one with mobile home, one 40 ac tract).
Weighted $/ac: $8,900 → likely value ~$44.5K (range $38K–$50K)
Offers: 25% = $11.1K | 35% = $15.6K | 50% = $22.3K
Confidence: Medium — only 4 comps within 5 miles.