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AI agent for real estate agents

Listing Presentation Prep Agent

A presentation packet with strong comps, a defensible price range and proof of past results

Listing Presentation Prep Agent: what goes in, what the agent does and what you get

What it does

A listing presentation is the agent's pitch for the job, yet most are rebuilt from scratch with a few weak comps. This agent prepares the packet for a specific home. It pulls recent sales, active listings and pending sales near the property, then scores each comp on distance, age, size, condition and date. It swaps weak comps for better ones until at least four strong ones remain, and shows how the price range changes. It adds market trends such as days on market and list-to-sale ratio, and pulls results from the agent's past listings for the proof section. It builds the packet and a pricing page. The agent approves everything before it is shared. Edge case: the best comp is a unique renovated home, so it is shown as a stretch comp, not a core one.

How it works

Follow the arrows from top to bottom. The orange dashed arrow is the loop: when a check fails, the agent goes back and tries again.

Start and resultWhat it doesA check on its own workWaits for your OKGoes back and retries
Yes, continueYes, continueApprovedNoNo 1 STARTS WHEN Listing appointment booked 2 USES A TOOL Pull subject property details and nearby sales andlistings 3 DOES Score each comp on distance, age, size, conditionand date 4 CHECKS THE RESULT Are there at least four strong comps? If not: widen the area, period or size range and notethe change. Back to step 3. 5 DOES Calculate the price range and compare with theseller's expectation if known 6 USES A TOOL Add market trends and the agent's past results 7 DOES Assemble the presentation and pricing pages 8 CHECKS THE RESULT Do all numbers in the packet match the source data? If not: correct the figure and rebuild the page. Back tostep 3. 9 YOU APPROVE Agent approves the packet before it is shared 10 RESULT Listing presentation packet ready
Read the steps as a list
  1. Listing appointment booked
  2. Pull subject property details and nearby sales and listings
  3. Score each comp on distance, age, size, condition and date
  4. Are there at least four strong comps?If not: widen the area, period or size range and note the change. Back to step 3.
  5. Calculate the price range and compare with the seller's expectation if known
  6. Add market trends and the agent's past results
  7. Assemble the presentation and pricing pages
  8. Do all numbers in the packet match the source data?If not: correct the figure and rebuild the page. Back to step 3.
  9. Agent approves the packet before it is sharedThe agent waits here for your OK.
  10. Listing presentation packet ready

How it decides

A comp is core when it is within one mile, built within 15 years of the subject, within 20 percent of the size and sold in the last six months. Weak comps are replaced before the range is shown.

  • Count a comp as core only within one mile, six months and 20 percent size difference
  • Show unusual comps as stretch comps, not core
  • Give a range, not a single price
  • Replace any comp with a stale or incomplete record

Make it yours

Every agent is a starting point. You choose these settings for your own situation.

  • Comp distance and period limits
  • Minimum number of comps (default 4)
  • Past results to include
  • Packet branding

What keeps you in control

It always asks you first

  • Agent approves the packet and price range before sharing
  • Agent approves any statement about past results

Hard limits

  • Never state a price as a guarantee
  • Do not share seller data outside the packet
  • Cite sources for every comp

It stops when

  • Done: packet approved and sent to the seller
  • Stop: not enough comparables exist and the agent decides how to present

Set it up

We guide you through the set-up, step by step

Members get the full set-up guide for this agent. No technical skills needed: you copy, paste and upload.

10 minto set it up in your AI
5 AIsChatGPT, Claude, Copilot, Gemini, Grok
  • One set of instructions to paste into your AI, with the clicks for ChatGPT, Claude, Microsoft 365 Copilot, Gemini and Grok
  • The agent then walks you through connecting your own data, one source at a time
  • A downloadable copy with the flow chart, the rules and the full guide
Get access to this agent

An example run

What happensA 3-bed ranch on Maple Lane has only two close comps. The agent widens from 0.5 to 1.2 miles and 12 months, finds four, and drops one with a finished basement the subject lacks. The range comes out at $412,000 to $428,000. A check catches a typo of $4,180 per square foot, fixed before the agent approves.

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