The Scenario
Procurement review lands on your desk every quarter. This time there are 120 product page URLs across three supplier sites — someone on the team collected them two weeks ago and put them in a Google Sheet, tabs organized by supplier. The task is a purchase comparison report. Price and in-stock status, current as of this week, across all 120 products.
You didn't set up the sheet. You inherited it from someone who left in February. The column structure varies slightly by tab. And the board presentation is Thursday.
The bad version:
- Open each product URL one by one, find the price and availability text on the page, note whether "In Stock" or "Out of Stock" or something like "Ships in 3–5 days" appears, switch back to the sheet, type it in.
- Realize partway through that one supplier shows prices with tax included and another doesn't, and now your comparison table is comparing different numbers.
- Hit a handful of URLs that require you to select a size or configuration variant before the price appears — those rows stay blank until someone follows up.
Thursday is not far enough away to do 120 of these by hand and still have time to write the report around the data.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads your data — across tabs if needed — and through its Apify MCP integration triggers a batch scrape run, then writes price, availability, and any flagged anomalies back into the right columns.
Scrape each product URL in column A of the 'Supplier A', 'Supplier B', and 'Supplier C' tabs using Apify. Write the product name into column B, the listed price into column C, and the availability status into column D. If a URL requires a variant selection before showing the price, mark that row "variant required" in column E.
What You Get
- Columns B, C, and D filled across all three tabs: product name, price as listed, availability status.
- Column E flagged with "variant required" for any product URL that needed a size or color selection to reveal pricing.
- All 120 URLs processed in a single Apify run — not 120 sequential browser sessions.
- No downloaded export. Results land in the sheet directly, in the tab they belong to.
What If the Data Is Not Quite Ready
Prices show in different currencies across suppliers
Scrape each URL in column A using Apify. Write the raw listed price into column C and the detected currency into column D. Flag any row where the currency differs from USD with "non-USD" in column E so I can adjust before the comparison.
Some product pages load prices via JavaScript after the initial render
For each URL in column A, use Apify's JavaScript-rendering scraper to load the full page before extracting price and availability. Write the results into columns C and D. Log "JS render used" in column E for rows where this was required.
You need to compare against your current budgeted prices
Scrape each URL in column A with Apify and write the current listed price into column C. Then compare column C against the budgeted unit price in column F. If the current price is more than 10% above budget, flag the row "over budget" in column G.
Full comparison report in one pass
Scrape all URLs in column A across the 'Supplier A', 'Supplier B', and 'Supplier C' tabs using Apify's JavaScript-rendering scraper. Write product name to column B, listed price to column C, currency to column D, and availability to column E. Flag "variant required" in column F where applicable, "JS render needed" in column G, and any price that's more than 15% above the budgeted figure in column H. Compare results across tabs and add a summary row at the bottom of each tab showing average price and total SKUs flagged.
When the cleanup and the comparison logic are part of the same prompt, you get the finished report — not the raw data that still needs a second pass.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with supplier product URLs, then ask it to scrape current prices and availability with Apify and write the results directly into the comparison table. See also the spoke on running a specific Apify Actor and importing its full dataset, or visit the Apify MCP overview for the complete workflow list.