This n8n workflow automates the process of optimizing YouTube video titles and descriptions to enhance SEO and viewer engagement. When triggered manually, the workflow retrieves pending video data from a Google Sheet, including URLs, titles, descriptions, and target keywords. It then makes an HTTP request to fetch the YouTube video page data, parsing the HTML to extract the current video title and description. Using language models, the workflow generates more attention-grabbing titles and engaging, SEO-friendly descriptions based on the original content, keywords, and latest trends. These optimized titles and descriptions are then merged, and the relevant data updates are written back into the Google Sheet, marking each video as ‘Done’ after processing. Practical use cases include content creators or digital marketers who want to streamline their YouTube channel SEO efforts, ensuring each video is optimized for searchability and viewer clicks without manual editing. This workflow saves time, improves video discoverability, and boosts channel growth.
YouTube Video Optimization Workflow for Increased Engagement
Node Count | 11 – 20 Nodes |
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Nodes Used | @n8n/n8n-nodes-langchain.chainLlm, @n8n/n8n-nodes-langchain.lmChatDeepSeek, aggregate, code, googleSheets, httpRequest, manualTrigger, merge |
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