Find the owners most likely to want your commercial listing: have an AI prospecting agent list nearby owners who fit a trade-up profile, pull public contact records into one call list, and log every call: AI agent prompt

Commercial brokers often have a listing and no obvious buyer, and building a list of nearby owners who might want it used to take hours of record searching. AI Business Plays writes up a self-reported LinkedIn post by Rudy Martinez, an industrial commercial real estate broker in Southern California. He asked an AI prospecting agent (Terrakotta) to find industrial owners within 10 miles of his Azusa, California listing who would want to trade up into an 8,000 square foot facility. It returned 624 owners in 30 seconds and found phone numbers for each from Secretary of State records. On his 21st cold call he reached the owner of a 3,100 square foot building 2.2 miles away who wanted to sell as soon as possible, and he won the roughly $1M listing. He also uses an AI notetaker on his calls. It is self-reported, and the deal is a listing, not a closed sale yet. Check your local cold-calling rules and the Do Not Call list, and verify every owner record before you call.

SalesCommercial property owner prospectingintermediate

The prompt

Help me find property owners who are likely to want, or trade up into, my commercial listing. My listing: [address, property type, size in square feet, key features, price or lease rate]. The owner most likely to want it: [e.g. an owner-user of a smaller industrial building nearby who is outgrowing it]. Search area: [distance, e.g. within 10 miles]. 1) List up to [number] properties in that area that fit the profile, with the address, size, owner name or owning company, and the public source for each (county assessor, business registry or Secretary of State record). Don't guess an owner or a phone number; leave it blank if you can't find a public record. 2) Rank the list by how likely the owner is to want my property, with a one-line reason each (size gap, age of building, how long they've owned it). 3) Turn the top 25 into a call list with a 2-sentence opener for each that mentions their building. 4) Give me a simple call log table: owner, date called, outcome, interest level, next step. Remind me to check my local cold-calling rules and the Do Not Call list before I dial.
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Works with: Terrakotta, ChatGPT, Claude, Perplexity, AI notetaker

Real-world example: aibusinessplays.com/plays/commercial-broker-ai-prospecting-finds-1m-li

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