Prompt Pack
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Sell Listings at the Right Price — And Hold It
40 AI prompts to build rock-solid pricing strategies and CMAs.
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Pricing is the most consequential decision a seller makes. The prompts here turn comparable sales data and current absorption rates into a clear narrative a seller can read and trust — anchored in visualization, justified in plain language, calibrated against what their specific micro-market will bear. You walk into the conversation with a defensible number and the seller walks out signed on it.
Pricing is the most consequential decision a seller makes, and most need help thinking it through clearly. This pack gives you 40 AI prompts to analyze comparable sales data, stress-test pricing decisions against market absorption rates, build visual CMA summaries, and communicate a justified price to unrealistic sellers — without the awkward conversation.
CMA close-through 64% → 81%
Built a one-page pricing rationale with comparables and absorption-rate signal side by side — CMA close-through rate moved from 64% to 81%.
The sequence
A preview of what's inside — copy and paste directly into ChatGPT or Claude.
- 1
Turn comp data into a plain-language pricing story
“Analyze a seller's comparable sales data and write a narrative summary that explains the pricing recommendation in plain language.”
- 2
Walk a seller off an emotionally stuck number
“Justify a price reduction to a seller who is emotionally attached to a number that the data no longer supports.”
- 3
Build a one-page visual CMA for the seller meeting
“Build a CMA summary for a seller presentation — include 6 comparables, days on market trends, and a visual price positioning chart.”
- 4
Stress-test pricing against current market absorption
“Stress-test a pricing decision against current market absorption: given active inventory and buyer demand, what price optimizes velocity and price?”
- 5
Justify a premium ask against the last comp
“Write a pricing justification email to a seller who wants to list $40K above the most recent comparable sale in their neighborhood.”
+ many more inside the full pack
Illustrated Scenarios
What this could look like for you
Hypothetical, illustrative scenarios — not verified customer reviews. The metrics below are plausible outcomes for agents applying the prompts in this pack to their own work.
- Persona
- Listing agent under pressure to drop price
- Situation
- A seller was eight days into a slow start and the instinct on every call was to cut $25K off the list price “just to be safe” — a habit that quietly compounds across a year of listings.
- Outcome
- Ran the pricing-retention prompt with a calibrated absorption-rate argument. Seller held the original list for the full first 60 days without conceding to a premature reduction.
- Metric
- $25K price reduction avoided
- Persona
- Listing agent pricing in a shifting micro-market
- Situation
- A comparable neighborhood trend suggested a flat offer accepted at ask, but the seller wanted a premium number with no narrative to back it up.
- Outcome
- Drafted a pricing-strategy narrative grounded in current absorption rates and presented it in the seller consultation. The seller over-ask accepted by $6K on the first offer.
- Metric
- Accepted at $6K over ask
- Persona
- Listing agent running a routine CMA
- Situation
- Comparable-sales summaries landed at a 64% close-through rate — sellers nodded along, then listed at the same uncommitted number and walked away three weeks later.
- Outcome
- Used the visual CMA summary prompt to build a one-page pricing rationale with the comparables and absorption-rate signal side by side. CMA close-through rate moved to 81%.
- Metric
- CMA close-through 64% → 81%
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