Henry Schuck (CEO of ZoomInfo): Building A Billion Dollar Data Company

Data Quality

ZoomInfo's approach to data quality is a blend of human insight and machine learning. Henry Schuck explains that while contributory networks provide raw data, the challenge lies in refining it to ensure accuracy. Machine learning systems are employed to predict data accuracy, but human intervention is crucial to validate these predictions 1. This iterative process enhances the system's ability to discern accurate data over time. Schuck emphasizes, "Our data is 95% accurate," highlighting the company's commitment to quality 2.

   

Networks

Contributory networks play a pivotal role in ZoomInfo's data collection strategy. Henry Schuck cites examples like Costar and Koopa, which leverage collective input to enhance data accuracy 3. Trust is essential in these networks, and Schuck notes that starting with non-sensitive data helps build this trust. He explains, "You gain trust that way, and then you can sort of move on to more sensitive information" 4. This approach ensures that contributors feel secure, fostering a robust data-sharing ecosystem.

   

Privacy

Privacy and transparency are at the forefront of ZoomInfo's operations. Henry Schuck stresses the importance of being ahead of regulations and providing users with control over their data 5. Business contact information, while less sensitive, is handled with care, and users are notified when their data is collected. Schuck states, "We give data subjects control over their information," underscoring the company's commitment to transparency 6. This proactive approach not only complies with privacy laws but also builds trust with users.