The Scenario
A market researcher studying video virality has 40 specific YouTube videos in a Google Sheet — hand-curated from a list of top-performing content in the fitness niche over the past year. The research brief requires view count, like count, duration, and upload date for each video to build a regression model. Column A has the video IDs. What it does not have is any of the actual metric data, because there is no way to get that data out of YouTube into a spreadsheet without calling an API — and the researcher is not a developer.
The bad version:
- Navigate to each video on YouTube, note the view count, like count, and duration manually.
- Discover that YouTube hides like counts for some videos. Research workarounds.
- After an hour, realise that upload dates are in relative format on the watch page ("2 years ago") and tracking down the exact date requires a different approach.
The model needs clean, consistent data. The manual approach produces inconsistent data slowly. This is not a good trade.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Google Sheet. It reads the video IDs or URLs in your sheet and, through its built-in Supadata integration, fetches structured metadata for each video and writes the fields into adjacent columns — in one operation.
For each YouTube video ID in column A, use Supadata to fetch the video metadata and write title, view count, like count, duration, and upload date into columns B through F
What You Get
- Column B: video title.
- Column C: view count as a number.
- Column D: like count (where available).
- Column E: duration in seconds or formatted as HH:MM:SS.
- Column F: upload date in ISO format, ready for date arithmetic.
- The full 40-row table populated in one pass, with consistent formatting across all rows.
What If the Data Is Not Quite Ready
Column A has full YouTube URLs instead of video IDs
The sheet was built by copying URLs from a browser, not extracting video IDs.
For each YouTube URL in column A, extract the video ID and use Supadata to fetch metadata — write title, view count, like count, duration, and upload date into columns B through F
You want to sort by view count as part of the same operation
The regression model needs the data pre-sorted from highest to lowest view count.
For each YouTube video ID in column A, use Supadata to fetch video metadata and write title, view count, like count, duration, and upload date into columns B through F — then sort all rows by column C descending
Some video IDs may be invalid or the videos may have been deleted
The original list was compiled nine months ago and some videos may no longer exist.
Use Supadata to fetch metadata for each video ID in column A — write the metadata into columns B through F for successful rows, and write 'Video unavailable' into column B for any ID that returns an error
You want engagement rate calculated alongside the raw numbers
For each video ID in column A, use Supadata to fetch view count and like count — write view count into column B and like count into column C, then calculate the like-to-view ratio and write it as a percentage into column D — flag any video with a ratio above 5% as 'High engagement' in column E
The pattern: fetch the raw data and derive the metric in one prompt, so the dataset arrives analysis-ready.
Try It
Get the 7-day free trial of SheetXAI and open any Google Sheet with a column of YouTube video IDs or URLs and ask it to pull the full metadata in one shot. To go deeper on a specific creator, look at the spoke on benchmarking YouTube channel stats.