YouTube Parser Online

This tool analyzes public YouTube video pages to extract structured metadata and content signals for SEO and research. It accepts a single URL or a batch of URLs and returns a consistent data model including title, channel, publish date, duration, category, view counts, like/dislike counts, and comment count. It also checks caption availability and retrieves transcripts when provided by YouTube, along with tags and the description length, which helps infer topic focus. Conceptually, the tool parses embedded page data (and public API surfaces where accessible) to normalize values such as duration to seconds and publish dates to ISO8601. The primary beneficiaries are content teams, SEO practitioners, and researchers who need repeatable, exportable data to inform video optimization and content strategy. Unique value lies in the combination of public-page parsing with optional transcript extraction and batch processing, enabling rapid comparative analysis across multiple videos. Core features include individual video data extraction, batch processing, transcript inclusion, and export formats like JSON or CSV. Common use cases include auditing existing video catalogs for SEO gaps, benchmarking performance against competitors, and extracting topic signals for feed planning. The tool avoids UI concepts and focuses on domain data, normalization rules, and export-ready outputs to feed analytics pipelines and dashboards.