The Scenario
A market research analyst at a consumer insights firm has 40 YouTube video IDs in an Excel workbook — a curated set of top-performing content in the home fitness niche, assembled over three weeks. The brief is to build a virality model, and the first variable set needed is title, view count, like count, duration, and upload date for each video. The analyst knows exactly which videos to study. Getting the data out of YouTube into the workbook in a structured format requires an API, and calling the YouTube Data API requires OAuth setup that the analyst does not have time to learn before the quarterly deadline.
The bad version:
- Look up each video on YouTube and note the statistics manually. Discover YouTube now hides like counts in the interface.
- Find a third-party YouTube stats lookup tool, paste in the first video ID, copy the result, paste into Excel. Do this 39 more times.
- Discover the tool shows view counts in abbreviated format ("4.2M") rather than the raw number needed for the model.
The quarterly presentation is in three weeks. The data collection phase was supposed to take two days.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the video IDs in your sheet and, through its built-in Supadata integration, fetches structured metadata for each video and writes it into adjacent columns — in one operation.
Pull video metadata from Supadata for every YouTube URL in column A and write title, channel name, views, likes, and duration into adjacent columns — sort by view count descending when done
What You Get
- Columns B through F populated with title, channel name, view count, like count, and duration for each video.
- Rows sorted by view count descending as part of the same operation — the highest-performing videos at the top.
- View counts as raw numbers, not abbreviated strings — ready for the statistical model.
- The full 40-row metadata table built in one pass, no pagination required.
What If the Data Is Not Quite Ready
Some video IDs in the sheet may have been deleted since the list was compiled
The niche changes fast and some videos get pulled by creators.
For each YouTube video ID in column A, use Supadata to fetch metadata and write title, view count, like count, and duration into columns B through E — write 'Video unavailable' into column B for any ID that returns an error
The sheet has full YouTube URLs in column A rather than bare video IDs
The list was assembled by copying URLs from the browser bar, not by extracting 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 engagement rate calculated as part of the same fetch
The virality model uses like-to-view ratio as a primary variable.
For each YouTube 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 as a percentage and write it into column D — flag any video with a ratio above 4% as 'High engagement' in column E
You want the metadata plus a flag for videos longer than 10 minutes
The model treats long-form content differently and needs a segment label.
For each video ID in column A, use Supadata to fetch title, view count, and duration — write title into column B, view count into column C, and duration in seconds into column D — write 'Long-form' in column E if duration is over 600 seconds and 'Short-form' otherwise
The pattern: building the segmentation logic into the same data fetch means the model input file is ready without a second cleanup pass.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook with a column of YouTube video IDs or URLs and ask it to pull the full metadata in one shot. For a channel-level view, look at the spoke on benchmarking YouTube channel stats.