The Scenario
You're a PR analyst at an agency and a client coverage report is due at noon. The client was mentioned in 60 articles last month — you know this because your media monitoring tool logged the URLs. What it didn't do is extract the headline, author, publication date, and a one-sentence summary for each article. That part it left for you.
It's 9:15 AM. You have the 60 URLs in column A of your Google Sheet. The client's account manager is going to paste these into a slide deck at 12:30.
The bad version:
- Open article 1, find the headline (it's in the browser tab, but the page's H1 says something different), decide which to use, find the byline (sometimes it's above the headline, sometimes below, sometimes it's a staff account), check the publish date (is that the published date or the updated date?), write a one-sentence summary
- Repeat for article 2, which loads behind a soft paywall and requires dismissing a signup modal before you can read it
- By article 15 you are writing summaries from headlines alone because there is no time to read 45 more articles before noon
The account manager wants the report to reflect what was actually written, not what you guessed from the first paragraph.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent inside your Google Sheet. It reads your article URL list and uses its built-in ScrapeGraph AI integration to extract headline, author, publish date, and article summary from each page — then writes the fields directly into your columns.
Paste this into the SheetXAI sidebar:
For each news article URL in column A, use ScrapeGraph AI SmartScraper to extract headline, author name, publish date, and a one-sentence summary, then write into columns B, C, D, and E
What You Get
- Column B fills with article headlines (the H1 title from the article body, not the browser tab text)
- Column C fills with author names as they appear in the byline
- Column D fills with publish dates in a consistent format
- Column E fills with one-sentence summaries extracted from the article's opening or abstract
- Articles behind hard paywalls are flagged in column F rather than left blank, so you know exactly which ones need a manual check
What If the Data Is Not Quite Ready
Publish dates are formatted inconsistently across publications
Normalize all date values in column D to YYYY-MM-DD format; flag any date that appears to be an "updated" date rather than an "originally published" date in column F
Some articles were syndicated and the byline shows a wire service instead of a journalist name
For rows in column C where the author name matches "AP", "Reuters", "Staff", "Wire", or similar, flag the cell in column G as "syndicated" and leave the author value unchanged
The client only wants articles from specific publications
Filter the 60 rows to keep only articles where the domain in column A matches this list of approved publications: [list]; move non-matching rows to a second sheet called Excluded
Full pipeline: scrape, normalize dates, flag paywalls, and add publication domain
For all 60 URLs in column A: run ScrapeGraph AI SmartScraper to extract headline, author, publish date, and one-sentence summary; write to columns B through E; normalize dates in column D to YYYY-MM-DD; extract the publication domain from each URL and write it to column F; flag hard paywall pages in column G; sort the result sheet by publish date descending
The report is ready before the account manager opens her first slide.
Try It
If you have article URLs from a media monitoring tool and a client coverage report due today, Get the 7-day free trial of SheetXAI and extract all the structured metadata in one shot. For related tasks, see how to convert article URLs to Markdown or generate a Markdown comparison table from sheet data.