How Pendo used Claygents to find target accounts for a new AI product
Pendo's GTM engineer used Clay's research agents to find signals no data vendor sold, such as which companies were building AI agents. He used them to build prioritized account lists for a new product suite. Clay reports strong pipeline and revenue results.
The problem
Launching an AI product suite meant targeting companies by qualitative signals, such as building custom AI agents or mentioning agents in financial filings. Standard enrichment providers didn't offer these data points.
How they did it
- Used Claygents to research custom data points across several sources.
- Analyzed job postings to find companies hiring for agent-development roles.
- Scraped 10-K filings and websites for mentions of AI agents, and checked marketing materials for build-vs-buy signals.
- Ranked the accounts and pushed them into Salesforce with custom classification fields.
Results
- Clay lists 200% of the Q1 sales target and 2x inbound pipeline.
- Identified 13,000 top-fit accounts to target for each product.
- 55% of revenue sold with Agent Analytics came in its first quarter. The source also cites a +110% increase in pipeline impact.
As reported by the source (Clay customer story); AgentGid did not measure these figures.
This suits a GTM or RevOps team with someone comfortable designing multi-source research prompts and mapping custom fields into Salesforce; the case is rated advanced. Note that the pipeline and revenue figures are Clay's own, and Clay's credits and actions are metered, so a 13,000-account scale will likely outgrow the free plan (Free + $167/mo). Regie.ai (Free + $49/mo) is a cheaper starting point.
The agent used here
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