<?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/1b6cf699217942b1a8a942fcdcaebf25&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/1b6cf699217942b1a8a942fcdcaebf25-eab4aeafee0d4b21-full.jpg</thumbnail_url><duration>82.733333</duration><title>CSV Clean + HubSpot Automation w/ Make.com</title><description>Most revops in this cycle are fighting a lazy battle against garbage data, so I showed how I clean it up so it is usable on day one. I start in the terminal, then run a Python cleaning process to fix errors like phone numbers, emails, and other bad fields, so the sheet imports cleanly. After that, I send it into an automated pipeline in Make.com that maps properties into perfectly structured HubSpot records. I did not ask you to take any action, just shared the workflow.</description></oembed>