ListingPrompt / Guides
Real estate field guideReal estate market update template
A monthly market update keeps you in front of homeowners in your farm area without asking for anything. The hard part is turning a table of numbers into something people read. This template does that in a few minutes with ChatGPT, and you send it through Mailchimp or whatever email tool you use.
The prompt
Here are this month's stats for [area]: [median price, DOM, inventory, sold count vs last year]. Write a 250-word homeowner newsletter: one headline insight, what it means for sellers and buyers, one local tip, and a soft CTA for a free home value estimate. Friendly, no jargon.
Step by step
- Pull the four numbers from your MLS stats for the same area and period each month: median price, days on market, inventory and sold count compared with last year.
- Paste them into the prompt with the area name and date range.
- Check that every number in the draft matches your source, and add the source and date in a footnote.
- Add your own local tip if the AI's is generic: a new park, a road project, a seasonal reminder.
- Send it in Mailchimp to your farm list, with the home value CTA linked to your valuation page or calendar.
Why one insight beats a data dump
Homeowners don't want a spreadsheet. They want to know whether now is a good time to sell, and what their home might be worth. The template asks for one headline insight and two short takeaways, which is about the right amount for a monthly email that people open on their phone.
Make it yours
Keep the same structure every month so readers know what to expect. Rotate the local tip. Once a quarter, ask the model to compare the quarter with the same quarter last year for a slightly longer issue.
Mistakes to avoid
Letting AI 'fill in' a number you didn't provide. If it mentions a statistic, it must come from your data.
Predicting prices. Describe what the numbers show; don't forecast.
Mailing people who didn't opt in. Use a list you're allowed to email.
Save it as a reusable assistant
Retyping prompts is where most agents give up. In ChatGPT, create a project or custom GPT for this task, paste the prompt into its instructions, and add one or two examples of output you were happy with. In Claude, a project with the same instructions does the job. From then on you only paste the facts. Keep a short note of what you changed each time you edit the instructions, so you can go back if a change makes the drafts worse.
A two-minute review checklist
Before anything AI-drafted leaves your hands, run through the same five checks. Is every fact, number and feature in the draft something you supplied or can verify? Does it describe the property and the service rather than the kind of person who should buy? Is it the right length for where it's going: MLS field, text message, email or caption? Does it sound like you, or like an ad? And does it include anything your brokerage or state requires, such as brokerage name, license number or a staging disclosure? If any answer is no, fix it or ask the model for a revision with that specific instruction.
Keep a running list of the fixes you make most often. After a week or two, add them to the prompt itself. That's how a generic prompt becomes your prompt, and it's the single biggest improvement you can make to AI output.
Before you use it
Every prompt on this site is a starting point, not a finished product. AI drafts fast, but you are the licensed professional: check every fact against the MLS and your own notes, keep Fair Housing rules in mind, and follow your brokerage's and your state's advertising rules. Treat the output as a first draft from a quick junior assistant who has never seen the property.
Frequently asked questions
- What should a real estate market update include?
- Median price, days on market, inventory and sales compared with last year, one plain-English insight, and what it means for buyers and sellers.
- How long should a market update email be?
- About 250 words works well for a monthly homeowner email.
- Can AI pull the market stats for me?
- Use your MLS or another source you trust for the numbers, then let AI write. That way every figure is verifiable.