Quick CMA from Comparable Sales (Explain the Price Range in Plain English)
Turn 3–8 comparable sales into a clear recommended price range with a plain-English explanation you can defend.
Prompt Overview
Tips For You
The fastest improvement comes from adding internal size, renovation/condition notes, and sale dates for each comp. Missing those often causes mispricing.
From Operations TeamNexusAi TechnologyProblem It Solves
Many CMAs fail because comps are dumped into a list without structured reasoning. This prompt turns comparable sales into a concise pricing rationale, showing what matters, what doesn’t, and why a price range is credible—without requiring a complex valuation model.
Comp Quality Sanity Check
Identifies best and weakest comps and flags missing data that can skew the range.
Plain-English Pricing Logic
Explains what actually drives value based on comps—usable in buyer/seller conversations.
Low/Mid/High Range Output
Produces a defendable range with short justification for each boundary.
Confidence Upgrade Checklist
Shows exactly what additional info would increase pricing confidence.
AI Prompt Instructions
Act as a practical CMA assistant.
You will NOT invent data. Use ONLY the comps and subject property facts I provide.
Goal: Produce a quick CMA summary and a defendable recommended price range.
Inputs:
A) Subject property (facts only):
- Address/suburb (optional):
- Property type:
- Beds/baths/cars:
- Land size / internal size (if known):
- Condition level (choose): poor | average | renovated | premium
- Key features (bullet list):
B) Comparable sales (paste 3–8, one per line):
For each comp include as much as you know:
- Sale price:
- Sale date:
- Beds/baths/cars:
- Land size / internal size:
- Condition:
- Location notes (same street / nearby / inferior/superior pocket):
- Key differences vs subject:
Required output:
1) Comp sanity check
- Which comps are strongest/weakest matches and why
- Any missing fields that could materially change pricing
2) Pricing explanation (plain English)
- What features drive value here (based on comps)
- What discounts/premiums apply and why
3) Recommended price range
- Low / Mid / High range (with brief justification for each)
- Confidence level (low/med/high) + what would increase confidence
4) One-paragraph client-ready summary
- Simple, non-technical explanation suitable for seller/buyer discussion
Rules:
- If you lack enough information, ask ONLY for the missing fields in a short bullet list.
- Do not claim market trends unless I provide trend data.
Expected Outcome
A quick CMA: strongest comps, pricing drivers, low/mid/high recommended range, and a client-ready summary paragraph.
Implementation Journey
Prepare clean comp inputs
Use ChatGPT to convert messy notes into a consistent comp list (price, date, size, condition, key differences). This prevents missed fields and improves the range accuracy.
8–12 minutesGenerate the quick CMA summary
Use Claude to run the prompt and produce the comp sanity check, value drivers, and low/mid/high price range in a structured format suitable for quick client discussion.
10–18 minutesPolish client-facing wording
Use ChatGPT to rewrite the final one-paragraph summary in your preferred tone (confident, calm, compliant) without changing numbers or assumptions.
5–8 minutes