The Scenario
You're three weeks into evaluating 15 metro markets for a franchise expansion recommendation. Column A of your Excel workbook has the metro names. The task your director handed you: for each market, pull the top 10 Google Maps listings for your target service category, note the competitive density, and flag any markets where fewer than 5 rated competitors show up.
You've been doing this by hand, one city at a time, copying business names and ratings from Google Maps search results. You're on city seven.
The bad version:
- Search Google Maps for the target category near each city name, open the results, manually record 10 business names, addresses, phone numbers, and ratings into the workbook
- Keep track of which city you're on across 15 separate browser searches
- Realize you missed the phone number column for cities 2 and 4 and have to go back
You're producing a board-level recommendation on expansion sites. Walking in with a workbook that's half-populated because the data collection took longer than the analysis is not the outcome this project deserves.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Excel workbook. It reads your list of metro markets, understands what you're trying to build, and through its built-in Search API integration it runs Google Maps searches for each city and writes the listing data back in a consistent structure.
For each city in column A, search Google Maps for "HVAC contractor" using Search API and write the top 10 results — business name, address, phone number, and star rating — into the rows below each city header, starting in columns B, C, D, and E.
What You Get
- 10 Google Maps listings per city organized below each city header row, with business name, address, phone, and rating in columns B through E
- Consistent structure across all 15 markets so the competitive density comparison is immediately readable
- Any market returning fewer than 10 results reflected accurately in the row count rather than padded with blank entries
What If the Data Is Not Quite Ready
The service category name needs to vary by market based on regional naming conventions
For each row, use the city in column A and the service category name in column B (which varies by market) to search Google Maps using Search API — write the top 10 listing names, addresses, phone numbers, and ratings into the rows below each city header in columns C, D, E, and F.
You want to pull Maps listings and immediately calculate a competitive density score per market
For each city in column A, search Google Maps for "HVAC contractor" using Search API and write the top 10 listing names and ratings into rows below each city header in columns B and C, then add a "Density Score" in column D next to the city header row that counts how many of the top 10 results have a rating above 4.0.
You have a second worksheet called "Excluded Brands" and you want to filter those chains out of the results
For each city in column A, search Google Maps for "HVAC contractor" using Search API, retrieve the top 15 listings, remove any business whose name matches an entry in the "Excluded Brands" worksheet, and write the remaining top 10 into the rows below each city header in columns B through E.
You want to pull Maps data, flag low-competition markets, and generate a ranked expansion priority list — all in one prompt
For each city in column A, search Google Maps for "HVAC contractor" using Search API, write the top 10 listing names, addresses, and ratings into rows below each city header, count how many results have a rating above 4.0 and write that count in column F next to the city header, then create a new worksheet called "Priority Rankings" that lists the 15 cities sorted from lowest to highest competitor density score.
That kind of kill-chain prompt turns a three-step manual process into a single ask.
Try It
Get the 7-day free trial of SheetXAI and open your market research workbook with target cities in column A, then ask it to pull Google Maps competitor listings for each market using Search API. The geo-targeted rank research spoke covers query-city SERP pairs if that's your next step, or go back to the Search API hub to see all the workflows this integration supports.