The Scenario
You manage the assortment for a mid-market retail category. Twice a month, your director asks for a product landscape update — what is Amazon showing for your core search terms, what are competitors listing at, how do the ratings look. You have 15 search result page URLs across Amazon and Walmart in your Google Sheet. Each page has 40 to 60 products on it.
Last time you did this by hand. It took most of a Wednesday.
The bad version:
- Open each search page, scroll through all the results, manually copy product names, prices, and ratings into a sheet row by row — or try to use a browser extension that breaks on dynamically loaded content
- Get through Amazon page one and realize the prices are loading after the initial page render via JavaScript, so your copy-paste picked up "Loading..." instead of the actual price on 20 rows
- Finish three pages, look at the clock, decide the rest can wait until tomorrow — meaning your "bi-weekly" landscape update is now running late and your sample size is too small to be meaningful
The Wednesday afternoon you spent on this is not analysis time. It is transcription time. And next month you will spend another Wednesday doing it again.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the search result page URLs from column A, calls Scrapfly with JavaScript rendering enabled for each one, extracts every product listing on the page, and writes them all into a flat product table — one row per product.
For each search result page URL in column A, use Scrapfly with JavaScript rendering to extract all listed product names, prices, and star ratings, and write every product as a new row in a sheet called Product Listings
What You Get
- A new sheet called Product Listings with one row per product found across all 15 search pages
- Column A contains the product name
- Column B contains the listed price
- Column C contains the star rating
- Column D contains the source search result page URL so you can trace which page each product came from
- All 15 pages run in a single pass — products from all pages land in the same flat table without manual merging
What If the Data Is Not Quite Ready
Prices are still returning as placeholders or empty
Some e-commerce search pages use aggressive lazy loading for prices. If column B has blank cells or placeholder text:
For each URL in column A, use Scrapfly with JavaScript rendering and a 6-second wait after page load to allow dynamic prices to render, then extract all product names and prices and write one row per product into the Product Listings sheet
You want to filter out sponsored listings before writing
Search result pages mix organic and sponsored products. If you only want organic results:
For each URL in column A, use Scrapfly with JavaScript rendering to extract all product listings — exclude any products tagged as Sponsored or Ad — and write product name, price, and rating into the Product Listings sheet
The 15 pages cover different search terms and you want that tracked
Your URL list has three Amazon searches and four Walmart searches across five different search terms. You want to know which products show up across multiple terms:
For each URL in column A, extract all product listings using Scrapfly — include the search term from column B as a source column in the Product Listings sheet — then in a second sheet called Overlap, list any product name that appeared on more than one search term
You want the full landscape report — extraction, deduplication, and competitive summary — in one pass
For each URL in column A, use Scrapfly with JavaScript rendering to extract all product listings and write one row per product into the Product Listings sheet, then deduplicate by product name, calculate the average price per product across all pages it appeared on, and write a summary table into a sheet called Landscape Summary with columns for Product Name, Average Price, Rating, and Pages Found On
One prompt, one run — the scrape, the deduplication, and the summary land together.
Try It
Get the 7-day free trial of SheetXAI and open your search result page URL list, then ask it to extract all product listings across every page using Scrapfly and write them into a flat table. If you also need to track competitor prices on individual product pages, see the spoke on bulk scraping competitor product prices.