video1.0<iframe src="https://www.loom.com/embed/612c562db8264f9fac796d1a3c71322f" frameborder="0" width="1856" height="1392" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>13921856Loomhttps://www.loom.com13921856https://cdn.loom.com/sessions/thumbnails/612c562db8264f9fac796d1a3c71322f-93a013648c9b4d06.gif124.604In this video, I walk you through our daily workflow for extracting user feedback from the App Store using ARAT. We utilize write data to scrape the latest reviews, which are then processed through our R.A.G. classification system powered by the LAMA index. This allows us to generate actionable insights and tailored responses for our technical, product management, and support teams. My goal is to convert text-based feedback into meaningful actions, addressing issues like authentication and UI bugs effectively. I encourage you to engage with this process and consider how we can further enhance our user response strategies.