video1.0<iframe src="https://www.loom.com/embed/6906fcbef0404ec19e8b4e02324b7e78" frameborder="0" width="1280" height="960" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>9601280Loomhttps://www.loom.com9601280https://cdn.loom.com/sessions/thumbnails/6906fcbef0404ec19e8b4e02324b7e78-5f608da1918c5a16.gif235.673In this video, I showcase how we utilize the XAPI to explore Twitter posts related to specific brands or topics. We analyze user embeddings and apply dimensionality reduction to visualize these interactions in 3D space, focusing on trends and seasonality over the past year. Our findings reveal interesting clusters, such as conversations around layoffs and brand-specific discussions. I encourage viewers to consider how these insights might align with customer segments and to think about potential extensions using unsupervised learning techniques. Thank you for watching!