{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/b0c90371522743c79b4088793760739c\" frameborder=\"0\" width=\"1660\" height=\"1245\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":1245,"width":1660,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":1245,"thumbnail_width":1660,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/b0c90371522743c79b4088793760739c-0b8b337abe02458a.gif","duration":267.17,"title":"How we compute metrics and dimensions in Ocular","description":"This Loom explains Ocular data models using Sales and Net Revenue as the core example. Net Revenue is revenue after deducting returns, cancellations, and applied taxes, requiring data stitched across multiple sources such as Shopify order info, warehouse dispatch data, returns management, and shipment or courier partner updates. It emphasizes that if an item is returned, not dispatched, or cancelled, net revenue becomes zero, which becomes complex at scale across thousands of orders and channels. The author highlights that Ocular computes these definitions near real time without spreadsheet consolidation, enabling analyses like Net Revenue by channel for last quarter at a monthly level."}