The Scenario
A growth analyst studying content-to-conversion patterns has 25 YouTube videos in an Excel workbook — top performers in the project management software niche, collected over the past three weeks. The research hypothesis is that transcript characteristics — vocabulary density, topic breadth, mention of specific features — predict engagement rate. To test it, the analyst needs both the full transcript text and the view count, like count, and duration for each video, in the same row, without a separate data collection step for each data type.
The bad version:
- Fetch transcripts first. Export to CSV. Import into the workbook. Map to the right rows.
- Fetch metadata separately. Export. Import. Run a VLOOKUP to join on video ID.
- Discover the video IDs are formatted differently in the two exports — one has the full URL, one has the bare ID. Spend 45 minutes fixing the join key.
The research presentation is in two weeks. The data pipeline was supposed to be built in one afternoon.
The Easy Way: One Prompt in SheetXAI
SheetXAI is an AI agent that lives inside your Excel workbook. It reads the video URLs in your sheet and, through its built-in Supadata integration, fetches both transcript text and video metadata for each video in a single pass — writing everything into the same row, no join step required.
Fetch Supadata transcripts and metadata for all YouTube URLs in column A and populate this Excel sheet: title in B, views in C, duration in D, and full transcript in E — flag any missing transcripts in column F
What You Get
- Column B: video title.
- Column C: view count as a raw number.
- Column D: duration in seconds or formatted as HH:MM:SS.
- Column E: full plain-text transcript for each video.
- Column F: a flag for any row where the transcript could not be retrieved — so the analyst knows exactly which videos need a workaround.
- All 25 rows in one pass, transcript and metadata aligned in the same row.
What If the Data Is Not Quite Ready
You want word count as a research variable rather than the raw transcript
The regression model needs word count as an independent variable, not the transcript text itself.
Fetch Supadata transcripts and metadata for all YouTube URLs in column A — write title into column B, view count into column C, duration in seconds into column D, and transcript word count into column E — flag any row where the transcript is unavailable in column F
Some videos have no captions and will return empty transcripts
The niche includes a mix of creators, and some do not enable auto-captions.
Fetch Supadata transcripts and metadata for all YouTube URLs in column A — write title into column B, views into column C, duration into column D, and full transcript into column E — for videos with no transcript, write 'No captions' in column E and flag the row in column F
You want like-to-view ratio alongside the other variables
Engagement rate is the dependent variable in the model and needs to be in the same row as the transcript data.
Fetch Supadata transcripts and metadata for all YouTube URLs in column A — write title into column B, view count into column C, like count into column D, and transcript text into column E — then calculate the like-to-view ratio as a percentage and write it into column F
You want a dataset summary at the top of the sheet before the row data
Fetch Supadata transcripts and metadata for all YouTube URLs in column A — write title into column B, views into column C, duration into column D, and transcript into column E — then in row 1 write the total video count in cell G1, the average view count in G2, and the number of rows with missing transcripts in G3, pushing the data to start at row 2
The pattern: surfacing the dataset summary at the top before the row data means the research framing is visible the moment the workbook opens.
Try It
Get the 7-day free trial of SheetXAI and open any Excel workbook with a column of YouTube URLs and ask it to pull both transcripts and metadata in one pass. For the channel-level view on any creator in your list, look at the spoke on benchmarking YouTube channel stats.