Welcome to AutomateRE, your weekly playbook for using AI in real estate.
Big week in AI and Real Estate. Last Tuesday, ProspectsPLUS! (the direct mail company that's been around since you were licensed) launched something called Listing Lens AI. The pitch: it tells you which homeowners on your farm are most likely to list. They'll sell you a subscription for it.
This is issue #13. Let's get into it.
Quick Win: The 7 most likely sellers in your sphere… ranked, with what to text each one first
Here's the prompt:
You are a top-producing real estate agent who studies your sphere obsessively. You will score everyone in this list on their likelihood of listing a home in the next 90 days, then tell me what to do about it.
MY MARKET: [CITY, STATE, ZIP]
MY SIDE: [LISTING AGENT / BUYER AGENT / BOTH]
TODAY'S DATE: [YYYY-MM-DD]
WHAT "LISTING" MEANS HERE: a primary residence, second home, or investment property the contact owns.
MY SPHERE (paste rows, minimum: name + property address + last touch date. Bonus columns make scoring much sharper):
[Name | Property address | Year purchased | Last contact date | Notes (job change, divorce, kid graduating, mentioned moving, new baby, downsizing parents, etc.) | Estimated equity range | Relationship strength 1-5]
YOUR JOB:
1. SCORE every contact 1-10 on "likely to list in next 90 days," using these signals (in order of weight):
- Time in home + life stage (5-7 years in home + kid hitting kindergarten or senior year of HS = high)
- Stated intent: anything in notes that sounds like "we've been thinking about moving"
- Forced moves: job change, divorce, death in family, new baby, downsizing parents
- Equity position: high equity + long ownership = unlocked seller
- Relationship temperature: warm contacts list faster than cold ones; flag cold ones as "warm-up first"
- Anything else you can infer from the notes
2. RETURN A RANKED TABLE with these columns:
Rank | Name | Score | The ONE signal that moved them up | Probable trigger ("kid is a HS senior — 18-month window") | Confidence (low/medium/high)
3. TOP 7, for each of the top 7, give me:
- First-touch text (under 200 characters, no real estate-y language, sounds like a friend, references the specific signal)
- Best day/time to send (when most people read but don't feel pitched)
- The follow up if they reply warm
- The follow up if they don't reply in 7 days
4. PASS: list anyone scoring 3 or below as "not this quarter" with one sentence on when to revisit.
TONE: A trusted friend who happens to sell houses. Never starts a message with "Just checking in." Never uses "touch base." Never says "the market is hot." If a message could plausibly come from a non agent friend, it's right.Result:A 30-row sphere list becomes a 7 name shortlist with a personalized first message for each, the kind of message that gets replied to instead of left on read.
Industry Intel: AI moved into the listing discovery layer of real estate this week
Two announcements landed on the same Tuesday, and together they tell you exactly where this is headed. AI is moving into the parts of the agent's job you thought were uncopyable: knowing who's about to list, when, and how to reach them. This week's signal: the platforms either start selling you that answer, or they start handing AI the keys to find it.
ProspectsPLUS! launched Listing Lens AI, a "predict your next listing" tool
ProspectsPLUS!, the direct mail platform Jim Morton has been running for three decades, just shipped a predictive intelligence tool that scores homeowners on likelihood-to-list. The play: agents subscribe, ProspectsPLUS! ranks the farm, and the same platform that sends the postcard decides who gets one.
SmartZip has done this for years for the farming crowd; the wrinkle is that a direct-mail-first company is the one moving. This is the surest sign predictive seller intelligence has crossed into table stakes.
Your move: You don't need to subscribe. Your past-client list is a better signal than any farm. The Quick Win above scores it in 90 seconds for free, and the workflow below keeps it fresh every week, so the highest-scoring 7 sellers in your sphere never go cold while you're paying someone else to score people who don't even know your name yet.
FBS launched the Flexmls MCP Server to turn MLS data into a chatbot for 330,000+ agents
The same week, FBS rolled out the Flexmls MCP Server: a connector that lets agents on Flexmls plug ChatGPT, Claude, or Gemini directly into their MLS account. You ask questions like "which 4-bedroom homes in 45208 had price drops in the last 30 days where the listing agent has fewer than 5 closed deals?" in plain English, with your real MLS data and get an answer in seconds. It's live in beta and rolling out across the MLSs FBS powers.
Your move: Inside our AI for RE community program we teach you how to use these tools. We have a new module coming out this week with the best use cases for the MLS MCP and how to set them up.
You can join here: Join the Sphere AI Community
Automate This: Score every Sunday, the 7 most likely listers in your phone, ranked, in a 5 minute email
Every week, we help you automate one part of your job. This week: a workflow that re-scores your entire sphere every Sunday morning and lands the top 7, with a drafted first-touch text per person in your inbox before you finish coffee.
The problem: Every agent says their network is their best source of business. Most of them call it 2 or 3 times a year. The CRM has 600 names in it. Six are about to list. You don't know which six. So you do nothing, or you blast a generic newsletter, and somebody else's name is on the listing agreement when your old client decides it's time. The data is already in your phone. You just don't have a system that surfaces the right names on the right week.
The solution: We built you an automation workflow for n8n:
You keep a sheet in Google Sheets: one row per past client, sphere contact, or warm lead, with name, property address, year purchased, last contact date, life-event notes, equity range, and relationship strength. (Five minutes a week to keep it current.)
Every Sunday at 7 AM, the workflow pulls every row where status = "active" and runs the entire list through the Quick Win prompt above in one batch.
AI returns a ranked table for the whole sphere, plus the top 7 with a personalized first-touch text per person, the best send-time, and a 7-day non-reply follow-up.
The workflow writes the full ranking back to a "Sphere Score" tab in the same sheet (so you can see who's heating up week over week), and emails you a clean one-pager with just the top 7 names and their drafted texts like copy, paste, send.
Optional: it logs every send to a "Touches" tab so you know who you contacted, when, and what you said. Two weeks of that and the AI starts factoring your own follow-up history into next Sunday's ranking.
Time to set up: 30-45 minutes
Time saved: 90 minutes per Sunday, plus the listings you would've missed because the right name never made it to the top of your call list.
Want it? Reply to this email with "SELLERSCORE" and we'll send you the workflow file + setup guide.
Next week: an AI that builds a full listing presentation (comps, value range, your three-page value-add, all on-brand) for each of your top 7, the moment their score crosses warm.
That's it for issue #13. Try the prompt before your next showing. Reply if you want the workflow. And we'll see you next Tuesday.
- NextAutomation Team
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