The One-Page Market Report: Turn an MLS Export Into Something You Can Hand a Client

Jerad Larkin
10 hours ago
5 min read

A full market analysis is great for you. It is usually too much for a client.

This one does the opposite. One page. Six numbers that matter, a price band breakdown, how fast homes are actually selling, and what sellers are really paying in concessions. Clean enough to print, hand across a kitchen table, or attach to an email without any explanation.

It is also deliberately unbranded, which means you can put your own name and logo on it, or hand it over as neutral third-party-looking data. Both are useful depending on the conversation.

When to use this instead of the full analysis

Monthly neighborhood update you email to a farm
A leave-behind after a listing appointment
Something to hand a buyer who keeps asking whether prices are coming down
An open house handout that makes you look like the market expert in the room

If you want the deep version with segment breakdowns and buyer and seller takeaways, use the market analysis prompt instead. That one is built to feed Gamma. This one is built to be printed.

You need one thing first

A closed-sales export from your MLS. Run your search, select all, and export using Full Export, not the short version. The short export drops seller concessions and days on market, and those are two of the four sections in this report.

Upload that file, switch to a Thinking model, and paste the prompt below.

The prompt

ONE-PAGE MARKET ACTIVITY REPORT

I am uploading MLS closed-sales data. Build me a one-page, print-ready market activity report for the area and period below.

AREA: [zip code, city, county, or neighborhood]
PERIOD: [for example, May 2026, or Q1 2026]

Filter the data to that area before you calculate anything. Use the postal code column for a zip, the city column for a city, the subdivision column for a neighborhood, or the whole file if it is a single county. If the area returns zero rows, tell me instead of guessing, and suggest what to check: spelling, leading zeros, or whether I pulled the right county file.

Do not fabricate any number. Every figure must come from the data I uploaded. If a column is missing, say which one and skip that section rather than estimating.

BUILD THESE FOUR SECTIONS, IN THIS ORDER

Section 1: The snapshot. Six numbers only.
- Total closings
- Median close price
- Average close price
- Median days on market
- Average days on market
- Median price per square foot

For price per square foot, use above grade finished square footage. If that is missing for a specific listing, use total living area for that listing only.

Section 2: Price bands. A table showing how many homes closed in each band, what percent of total that is, and the median days on market within that band. Use these bands by default:
Under $400K | $400K to $600K | $600K to $800K | $800K to $1M | Over $1M

LUXURY AUTO-DETECT: before you build this table, check two things. If the median close price is $900,000 or higher, OR if 40 percent or more of the closings are over $1M, switch to these bands instead:
Under $750K | $750K to $1M | $1M to $2M | $2M to $3M | $3M to $5M | $5M+

Tell me in one line which band set you used and why.

Section 3: Speed to close. How many homes sold in each window, with the percent of total. Use these buckets by default:
0 to 7 days | 8 to 14 days | 15 to 30 days | 31+ days

If luxury mode fired, use these instead:
Under 14 days | 15 to 30 days | 31 to 60 days | 61 to 90 days | 90+ days

Section 4: Seller concessions. Only if the data has a concessions column.
- What percent of closings included a concession
- Median concession amount among those that had one
- Average concession amount among those that had one
- Total count of closings with a concession

If there is no concessions column, say so in one line and skip the section.

WRITE A SHORT READ-OUT

Under each section, add one or two plain-language sentences a homeowner would understand. Not analysis jargon. Something like: most homes here are closing in under two weeks, and the ones that sit past thirty days are almost all above $800K.

If luxury mode fired, adjust the tone. In a high-end market, a longer days-on-market number is normal due diligence, not a warning sign. Do not frame it as a problem.

FORMATTING RULES

- Everything must fit on one page. Be ruthless. Tables over paragraphs.
- No branding, no names, no logos, no attribution. I will add my own.
- Use plain language a client can read without me in the room.
- Do not use em dashes.
- End with a single footer line noting the data source and the period covered.

After you build it, list any number you were not fully confident in and tell me which column it came from, so I can verify before I send this to anyone.

The luxury detection is the clever part

Standard price bands are useless in Cherry Creek. If every home is over a million dollars, an over $1M bucket tells your client nothing.

So the prompt checks the data first and switches to luxury bands automatically when the median crosses $900K or 40 percent of sales are over a million. It also changes the tone, because 60 days on market means something completely different at $3M than it does at $500K. Same prompt, right report, no thinking required from you.

Adjust those thresholds to your market. In some parts of the Front Range $900K is not luxury, and in others it very much is.

Making it a PDF

Once you have the output, you have two easy routes. Paste it into Gamma.app and let it design the page, or paste it into a doc, add your headshot and brokerage info, and print to PDF. Either way you are about five minutes from something you can hand someone.

Or skip all of it

If you are running Claude Cowork on your desktop, I packaged this as a skill that goes further than the prompt does. You hand it the export, it runs the analysis and builds the finished one-page PDF for you. No copying, no pasting into a design tool, no formatting.

Download the skill file at bit.ly/mls-report-on-autopilot and upload it into Cowork.

That is the whole difference between Level 2 and Level 3 in one example. Same job. At Level 2 you run the prompt and format the result. At Level 3 you hand over the file and get back a finished report.

Check the numbers

The prompt ends by asking the AI to flag anything it was not confident about and name the column it came from. Read that list every time. MLS exports are messy, columns get renamed, and a blank square footage field will quietly skew your price per square foot.

You are putting your name on this and handing it to a client. Spend the two minutes.

I teach this live in my AI classes and workshops across the Front Range. If you want help getting it running, reach out anytime.

Jerad Larkin

Account Executive, Chicago Title of Colorado

303.630.9430 | Info@MileHighTitleGuy.com | MileHighTitleGuy.com

This content is for general informational and educational purposes only. It reflects my personal opinions and industry experience and is not legal, financial, or tax advice. AI gives you a strong starting point, but you are responsible for verifying every number before you share it with a client, including Fair Housing, MLS, and brokerage compliance. When in doubt, check with your broker.

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