The Scenario
You work in real estate analysis and you have 300 property addresses in column A of a Google Sheet. The investor report goes out tomorrow and whoever built the template last quarter added a "Market Health" section that everyone now expects to include current AQI readings alongside walkability scores and school ratings.
The bad version:
- Open Ambee's API console, type the first address, wait for the response, read off the AQI and PM2.5 fields, switch tabs, paste them into row 2, switch back.
- Repeat for row 3. By row 15, your browser has 11 tabs open, you've mixed up which values belong to which address twice, and column D has a PM10 reading from three addresses ago.
- Realize you still have 285 rows left and the investors' briefing is at 9 AM.
Real estate air quality analysis is not a one-address problem. The whole value is in comparing dozens of sites side by side, and that comparison only holds if all the readings came from roughly the same moment. Stagger them by an hour—or by a dozen copy-paste sessions across an afternoon—and the comparison starts lying.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent embedded directly in your Google Sheet. It reads your addresses, calls Ambee for each one, and writes the results back into your columns—without you touching an API key or writing a single formula.
Here is the prompt to run this task:
For every address in column A, look up the current AQI, PM2.5, PM10, and air quality category from Ambee and fill columns B–E
What You Get
- Column B: AQI score (0–500 integer) for each address
- Column C: PM2.5 reading in µg/m³
- Column D: PM10 reading in µg/m³
- Column E: Air quality category label ("Good," "Moderate," "Unhealthy for Sensitive Groups," etc.)
- Rows where Ambee has no nearby station data show "No data" rather than a blank
What If the Data Is Not Quite Ready
The addresses include unit numbers and suite identifiers that confuse geocoding
For every address in column A, strip unit numbers and suite identifiers before querying Ambee for AQI, PM2.5, PM10, and category, and write results into columns B–E. Flag any address that still fails geocoding in column F.
Some rows have city and state in separate columns B and C instead of a full address
Combine the city in column B and state abbreviation in column C into a single location string, fetch current AQI and PM2.5 from Ambee for each, and write AQI into column D and PM2.5 into column E
The report needs AQI data grouped by zip code, not individual address
For every unique zip code derived from the addresses in column A, fetch the average AQI, PM2.5, and PM10 from Ambee across that zip's available stations and write the summary values into a new tab called "ZIP Summary" with columns: Zip, Avg AQI, Avg PM2.5, Avg PM10
Full kill-chain: normalize addresses, fetch AQI, flag unhealthy sites, sort for investor review
Take every address in column A, standardize formatting (remove suite numbers, fix state abbreviations), look up current AQI, PM2.5, PM10, and category from Ambee and fill columns B–E, flag any row where AQI is above 100 with "REVIEW" in column F, then sort the sheet by AQI descending so the worst-performing properties are at the top
Ask for the cleanup and the action in a single prompt—SheetXAI runs both in one pass.
Try It
Open any Google Sheet with a property address list and get the 7-day free trial of SheetXAI. Ask it to enrich column B with AQI readings and column C with PM2.5 from Ambee, and your market health data lands before the morning briefing. See also: enriching locations with pollen levels or the full Ambee integration overview.