YouTube Comment Scraper
Scrape YouTube Comments and Video Data to a Spreadsheet
Extract comment text, author names, like counts, reply counts, timestamps, and verified badges from any YouTube video. Scroll through the comment section and DataLens will accumulate all visible comments for export to CSV or Excel.
Each example shows how a live website can become a reviewable dataset inside the DataLens AI scraping workbench.
What data gets extracted
DataLens automatically detects and extracts these fields from YouTube — no selectors, no code, no maintenance.
Decision-ready dataset
What teams can decide with YouTube data
Use YouTube as a live source for an AI scraping workbench: collect the fields, clean the noisy rows, and turn the result into market, lead, content, or operations evidence.
Spot patterns
Compare listings, reviews, creators, products, or posts across the fields that matter.
Prioritize action
Move from raw rows to ranked opportunities, risks, accounts, or content ideas.
Share proof
Keep the exported file and source context ready for teammates, clients, or follow-up analysis.
How it works
- 1
Open a YouTube video page in Chrome and scroll down to the comments section.
- 2
Launch DataLens and detect the comment card structure.
- 3
Keep scrolling to load more comments, then export to CSV or Excel.
Frequently asked questions
Use these questions to decide how a live website becomes an AI scraping workflow.
What YouTube comment data can I extract?
DataLens extracts comment text, author names, like counts, reply counts, timestamps, creator verification badges, and pinned status from YouTube video comment sections.
Do I need a YouTube API key?
No. DataLens reads the comment content rendered in your Chrome browser — no API quota, developer key, or OAuth setup required.
Can I extract thousands of YouTube comments?
Yes. Scroll through the YouTube comment section to load more comments — DataLens accumulates them in the background as they appear in the DOM.
Can I export to Excel?
Yes. Export YouTube comment data to CSV, Excel (XLSX), or JSON for sentiment analysis, NLP training, or audience research.
Related workbench workflows
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