What I like most about Clay is how useful it is for building and adjusting data enrichment workflows. It gives us room to test, refine, and troubleshoot as we go. The support also makes a major difference. When we run into issues, it is easy to get practical help from someone who understands the product.

Claygent’s ability to handle real, live websites without breaking is what stands out. It doesn’t just pull from static APIs—it scrolls, clicks, waits for dynamic content, and extracts what a human would actually see. That means we can scrape JavaScript-heavy career pages, funding announcements, or tech stack listings that most enrichment tools simply miss. The natural language interface is a practical advantage. My campaign managers—none of whom write Python—build their own workflows without waiting for me or our data team. They describe what they want, and Claygent executes. On the ad side, dynamic exclusion lists have directly improved our ROAS. We sync CRM data to LinkedIn and Meta, and Clay automatically pushes “current customer” segments as exclusions. No manual CSV uploads. No accidental spend on existing accounts. For a German agency operating under GDPR, this level of control—combined with full documentation of each data source—is something I can actually present during compliance audits.

What I like most about Clay is how seamlessly it aggregates data from 50+ enrichment sources into one cohesive spreadsheet-style interface. Rather than jumping between LinkedIn, Clearbit, and Apollo, I can pull accurate emails, phone numbers, and company insights all in one place, which makes the whole workflow feel much more streamlined.