The Scenario
A franchise development analyst got a new brief this morning: identify which metro areas are oversaturated in three restaurant categories before the ownership group decides where to open the next five locations. She has 150 city-and-category pairs in column A. The investment committee meets in four days.
The bad version:
- Search "pizza restaurants in Austin" on Yelp, read the first 5 listings, copy the business name, star rating, and review count into columns B through D for each result — that is 15 data points per row
- Work through the first 20 rows, then hit a wall: Yelp's desktop interface loads additional results dynamically, meaning what you see at first is not necessarily the full top 5, and you are not confident the data is consistent
- Finish 40 rows across the afternoon, still 110 rows short, knowing the committee needs the saturation analysis, not a progress update
An investment committee does not want to hear that the data was hard to collect. They want a decision-ready view of the market.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the query list in column A, calls SerpApi's Yelp endpoint for each one, and writes the business listing data back — all 150 rows, consistently. One prompt.
For each query in column A, search Yelp via SerpApi and fill in the top 5 business names, star ratings, and review counts into the next 15 columns
What You Get
- Columns B, E, H, K, N receive business names for Yelp positions 1 through 5
- Columns C, F, I, L, O receive the corresponding star ratings
- Columns D, G, J, M, P receive the review counts
- Queries returning fewer than 5 results leave the later column groups blank rather than padding with placeholder data
What If the Data Is Not Quite Ready
Queries in column A mix formats — some have "restaurants in City," some just have "City"
Standardize each query in column A to "category in city" format before searching Yelp via SerpApi, then write the top 5 business names, ratings, and review counts into the next 15 columns
You also need address for geographic clustering
For each query in column A, search Yelp via SerpApi and write the top 5 business names, addresses, star ratings, and review counts across the next 20 columns
You only want businesses with more than 100 reviews (to filter noise)
Search Yelp via SerpApi for each query in column A, filter results to businesses with more than 100 reviews, and write up to 5 qualifying business names and review counts into the next 10 columns
Full saturation analysis in one prompt
Search Yelp via SerpApi for each query in column A, write the top 5 business names and review counts into the next 10 columns, sum the total review counts per row into column L, and flag in column M any row where the total reviews exceed 5,000 as a potentially saturated market
Saturation scoring and data collection in one pass.
Try It
Get the 7-day free trial of SheetXAI and open your market research sheet before the investment committee meeting, then ask SheetXAI to pull Yelp data for every location query. Also see the spoke on pulling Google Maps data for cross-validation, or the hub overview of all SerpApi workflows.