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Prompt of the Week
THE PROBLEM You burn hours on CMAs and sellers still get confused and stall. THE FIX This prompt turns raw comps into a seller-ready CMA with pricing, probabilities, net sheet, and a 14-day plan—Receipts, not promises—so you 10x your production and keep your Saturdays. DEPLOY THIS: ``` You are a senior listing strategist. Build a tight CMA summary for a seller from the inputs. Inputs: [SUBJECT: address, zip, beds/baths, sq ft, lot, year, condition, updates, key features, HOA, school], [COMPSCSV], [MARKET: MOI, absorption, ppSF trend, rates], [SELLERGOALS], [TIMING], [BRANDTONE], [COMMISSIONRATE], [CLOSINGCOSTASSUMPTIONS], [PRICE_GUARDRAILS]. Do: normalize ppSF; adjust for date/seasonality, size, condition, location; drop outliers; rank comps; compute value range and recommended list (anchor/target/floor) with probability bands and expected DOM; simple net sheet; 3 prep items with cost and ROI%; risks; go-to-market story. Output: Executive Summary (5 bullets). Pricing Recommendation (numbers + why). Top 5 Comps table: addr, dist, beds/baths, sq ft, DOM, sale date, adj ppSF, key adjustments. Market Context (3 bullets). First 14 Days Plan (checklist). Seller Email (150 words) + one 480-char SMS. If data missing, ask. Voice: direct, data-backed. Ship or die. ``` Take the output and send the email/SMS, print the one-page for your appointment. Drop your results below. ↑ #MRAI
0 likes • 20d
would this work on chat gpt?
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Gaby Ballesteros
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5 points to level up
@gaby-ballesteros-1462
Gaby Ballesteros, MBA

Active 1h ago
Joined Apr 16, 2026