Suspect Data/List Clean Up

Hi James, Thanks for your job posting and I have some questions for your project:

Are there any specific rules or criteria you want me to use when identifying duplicates (e.g., exact matches only, similar names, or email variations)?

Which email validation service or software do you prefer, or should I recommend the most reliable option for your list?

Do you need the final dataset to include only active emails, or should it retain all entries with a flag indicating their validation status?

Best.

Hey James, Before beginning the cleaning process, it’s essential to clarify how you’d like duplicates defined should they be removed based on email address only, or also by name and company? Understanding the source of your 18,000 suspects (e.g., opt-in, purchased, scraped) will ensure compliance with data regulations like GDPR, and confirm whether pre-validation is permitted. Additionally, knowing your intended use cold outreach, re-engagement, or transactional messaging will shape the validation depth, including handling of role-based emails (e.g., info@), catch-all domains, and spam trap checks. Finally, should invalid contacts be suppressed or deleted, and do you prefer the final list in CSV or another format? Clarifying these points ensures a precise, compliant, and effective clean.