{"type":"video","version":"1.0","html":"<iframe src=\"https://www.loom.com/embed/1b6cf699217942b1a8a942fcdcaebf25\" frameborder=\"0\" width=\"1280\" height=\"960\" webkitallowfullscreen mozallowfullscreen allowfullscreen></iframe>","height":960,"width":1280,"provider_name":"Loom","provider_url":"https://www.loom.com","thumbnail_height":960,"thumbnail_width":1280,"thumbnail_url":"https://cdn.loom.com/sessions/thumbnails/1b6cf699217942b1a8a942fcdcaebf25-eab4aeafee0d4b21-full.jpg","duration":82.733333,"title":"CSV Clean + HubSpot Automation w/ Make.com","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."}