<?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/b0e5cdfaa3fc4800802f8c92907425b4&quot; frameborder=&quot;0&quot; width=&quot;1280&quot; height=&quot;960&quot; webkitallowfullscreen mozallowfullscreen allowfullscreen&gt;&lt;/iframe&gt;</html><height>960</height><width>1280</width><provider_name>Loom</provider_name><provider_url>https://www.loom.com</provider_url><thumbnail_height>960</thumbnail_height><thumbnail_width>1280</thumbnail_width><thumbnail_url>https://cdn.loom.com/sessions/thumbnails/b0e5cdfaa3fc4800802f8c92907425b4-1689983989008.gif</thumbnail_url><duration>791.436</duration><title>building a targeted list of go high level users</title><description>In this video, I share my findings after processing 130,000 records in Richmond. It took about 30 minutes to complete the task, which is quite impressive. I discuss the high-level documentation and then proceed to download and analyze the data. The file turns out to be quite large, containing personal details of companies using High Level. I take a closer look at one company, Travel Savers, and explore the senior director&apos;s LinkedIn profile and contact information. The video reveals some interesting and potentially concerning information about the personal email associated with the company.</description></oembed>