Clay

Clay — Technical Use Cases

1. Waterfall Enrichment Pipeline

Chain 200+ data providers in a single workflow. Clay cascades through providers sequentially, writing the first successful result back to your CRM (Salesforce) or data warehouse (Snowflake), maximizing field coverage while minimizing redundant API spend.

2. Agentic GTM Workflows (Claygents)

Build multi-step, AI-driven agents that autonomously execute research, enrichment, scoring, and sequencing tasks. Claygents support conditional branching and can be triggered via API or CLI, making them composable with existing data pipelines and coding-agent frameworks.

3. CRM Data Quality Automation

Schedule recurring enrichment jobs that detect and overwrite stale or missing fields in Salesforce, keeping CRM data fresh without manual intervention.

4. Inbound Lead Scoring & Routing

Configure rule-based or AI-assisted scoring models inside Clay. Qualified leads are automatically routed to the correct rep or sequence, reducing time-to-contact.

5. Outbound Personalization with Live Intent Signals

Leverage the MCP layer to inject real-time intent signals into outreach sequences. Personalization variables are resolved at send time, enabling dynamic, context-aware messaging at scale.

6. Ad Audience Sync

Programmatically sync enriched and scored segments to Meta and Google ad audiences, keeping paid targeting aligned with CRM segmentation logic.