The challenge was not finding Amazon sellers.
There were already hundreds of thousands of them.
The challenge was figuring out: Which sellers matter? Who should we contact? Why should we contact them now?
A raw marketplace dataset became a continuously enriched prospecting engine.
- Data sourcing: Amazon seller and marketplace data pulled from multiple sources.
- Enrichment: Company domains, decision makers, titles, LinkedIn profiles, technologies and additional company information.
- Signal detection: Business changes, listing activity and other signals used to identify higher-intent prospects.
- Verification: Multi-provider email enrichment and verification waterfalls to improve contact coverage.
- AI research: Claygent used to research companies and generate additional context for personalization.
- Outbound: Qualified prospects automatically pushed into the outbound infrastructure with personalized messaging.
