<?xml version="1.0" encoding="UTF-8"?><oembed><type>video</type><version>1.0</version><html>&lt;iframe src=&quot;https://www.loom.com/embed/bdb32d2e9a214440a13f2935a3ab59c1&quot; frameborder=&quot;0&quot; width=&quot;1152&quot; height=&quot;864&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>864</height><width>1152</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>864</thumbnail_height><thumbnail_width>1152</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/bdb32d2e9a214440a13f2935a3ab59c1-001069d3ed423e44.gif</thumbnail_url><duration>263.7376</duration><title>Customer Retention and Analytics Insights</title><description>In this video, I present the retail customer attention analytics focused on understanding customer behavior and lifetime value through transaction data. I analyzed customer churn across various regions and channels, revealing that certain areas contribute more to customer loss. Additionally, I segmented customers by purchase frequency, finding that high-frequency customers exhibit stronger loyalty. I recommend prioritizing retention efforts for high CLV customers, improving performance in underperforming regions, and enhancing loyalty engagement strategies. I also included detailed documentation of my analysis and calculations for your review.</description></oembed>