Yo everyone! I just finished building a new Make.com workflow for outbound campaigns and wanted to share the sauce. If you do any kind of cold email, you know the pain of scraped data making you sound like a robot (e.g., "Hey! I noticed you work at Elate Staffing Solutions Ltd..."). I built this Growth System to bridge the gap between raw scraped data and perfectly formatted, human-sounding cold emails. Here is the breakdown of how the automation flows: - Trigger (Apify): The workflow kicks off the second an Apify actor finishes scraping a list of target leads. - Validation (Mails.so): It automatically grabs the dataset and runs every email through an HTTP request to an API to check if it's deliverable. Gotta protect that domain reputation! 🛡️ - The Magic Sauce (GPT-4o): Here’s my favorite part. If the email is valid, the data gets passed to GPT-4o. I wrote a prompt that normalizes the company name by stripping out the generic corporate jargon (Inc, LLC, Ltd) and focusing on the most memorable element. So, "Walmart Inc" becomes "Walmart", and "JP Morgan Chase Bank" becomes "JPM". - CRM Push (Instantly): Finally, it pushes the validated email, first name, last name, and the cleaned company name directly into an Instantly campaign. I'm implementing this as part of the backend for my AI automation agency, Zestflow. Honestly, the AI company name cleaner alone is a massive game-changer for keeping personalization looking authentic at scale. Are you guys doing anything similar to clean up your lead lists before sending them to your sending tools? Drop your workflows or tech stacks below!

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