Video search result extraction
Collect video titles, view counts, upload dates, channel names, and thumbnails from YouTube search results and category pages.
YouTube Scraper
Extract YouTube video and channel data into structured spreadsheets
DataLens lets you collect YouTube video metadata, channel statistics, and comment threads from your browser. Extract titles, view counts, like counts, upload dates, descriptions, and channel subscriber counts into CSV or Excel without any code.
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Comment and engagement data
Extract full comment threads including commenter names, text, like counts, reply counts, and timestamps from any video.
Channel analytics data
Pull channel names, subscriber counts, video counts, and video performance metrics from channel pages.
Real-world use cases
A content strategist researching a competitor's channel exports all video titles, view counts, and upload dates to identify which content formats consistently outperform — sorting by view count to find the top 20 videos and analyzing title patterns, topic types, and posting frequency.
A UX researcher studying customer sentiment exports comment threads from product demonstration videos — sorting by like count to surface the most-endorsed viewer reactions, then categorizing by theme to identify feature requests and pain points that appear most frequently.
An academic researcher building a natural language dataset exports comments from multiple channels across a topic area, creating a large structured corpus of real-world opinion text for NLP training — without navigating YouTube Data API quotas or approval processes.
How it works
- 1
Open YouTube in Chrome and navigate to a search results page, a channel video grid, or a video page with its comment section. For comment extraction, scroll past the video description to trigger the comment section to render — YouTube comments are lazy-loaded and will not appear until you scroll.
- 2
Open DataLens from the Chrome toolbar. Click on a video card to detect video metadata fields (title, view count, upload date, channel name) or click on a comment card to detect comment fields (author, text, likes, timestamp). DataLens shows a column preview before capturing any data.
- 3
Scroll to load more videos or comments, then click Export when you have enough records. For large video libraries or long comment threads, 5–15 minutes of scrolling will yield several hundred records. Download as CSV, Excel (XLSX), or JSON.
Frequently asked questions
These are the most common questions teams ask before using DataLens for this workflow.
What YouTube data can I extract?
From search result and channel pages you can extract video titles, view counts, like counts, comment counts, upload dates, and channel names. From video comment sections you can extract commenter usernames, full comment text, like counts, reply counts, timestamps, and verified/creator badges.
Can I scrape YouTube comments without the API?
Yes. DataLens reads the comment section as rendered in Chrome without any YouTube Data API access, quota management, or developer token. This is particularly practical now that the free YouTube API tier limits most users to approximately 10,000 units per day — far less than what many research scenarios require.
How do I extract data from YouTube search results?
Run a keyword search on YouTube, let the results grid load, then open DataLens and click on any video card. The AI detects the repeating video card structure and maps titles, view counts, upload dates, and channel names automatically. Navigate to subsequent result pages to accumulate more records.
Can I export YouTube data to Excel?
Yes. Every YouTube extraction can be exported as CSV, Excel (XLSX), or JSON with a single click. The file downloads with clean column headers and is ready to open in Excel, Google Sheets, or any BI or analysis tool.
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Use these pages to compare adjacent search intents and choose the landing page that matches your export format or extraction challenge.
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