<?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/c12aae50fd6e4a9d946098650b3da31f&quot; frameborder=&quot;0&quot; width=&quot;1920&quot; height=&quot;1440&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>1440</height><width>1920</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>1440</thumbnail_height><thumbnail_width>1920</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/c12aae50fd6e4a9d946098650b3da31f-a26cd2006114c07a.gif</thumbnail_url><duration>248.058</duration><title>Ongoing Enrichment Automation Explained</title><description>In this video, I dive into the complexities of ongoing enrichment automation, emphasizing the importance of defining re-enrichment frequencies for different types of records. I discuss how granular decisions, like validating emails every three months, can significantly impact data accuracy. Additionally, I highlight the need for overwrite rules when updating existing data, using practical examples to illustrate my points. Please take note of the factors to consider when deciding whether to overwrite data, as this will be crucial for our processes moving forward.</description></oembed>