{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/868fe81f0734487e80d00a52a124f194\" frameborder=\"0\" width=\"1722\" height=\"1291\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1291,"width":1722,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1291,"thumbnail_width":1722,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/868fe81f0734487e80d00a52a124f194-5a97117f4fd9d315.gif","duration":1192.836,"title":"• 4 Angle Finder Use Cases Nobody's Using (But Should)","description":"This Loom is a deep dive on using Angle Finder to generate hair loss ad angles from real customer voice. The creator first focuses on a Reddit scraping use case to pull direct quotes from customers and turn them into immediate hooks, then compares it with science based prompts for unique mechanisms, translocate prompts that pull angles from adjacent industries, and competitor or review sentiment scraping. They demonstrate creating long form direct response ads and generating related native images, noting outputs of about 2,500 to 5,300 words in the examples and completing the workflow in roughly 19 minutes. The recap emphasizes prompts should be specific about source and intent, such as cold ad angles or negative customer sentiment."}