Pendo

How Pendo built the go-to-market infrastructure for a multi-product AI launch

Clay Team
Clay Team
What we did

200%

Q1 sales target

55%+

new product-line revenue sourced

2x

inbound pipeline

At a glance

"Pulling our level of custom data without Clay would have taken months. Now, we can build new go-to-market infrastructure within days, allowing my team to focus 100% on sales strategy rather than data mechanics." — Zach Baumgarten, GTM Engineer

Company

Pendo is a product experience platform that helps software companies understand product usage, collect feedback, and guide users.

Industry

Product Analytics

headquarters

Raleigh, NC

When Pendo launched its new suite of AI products, the GTM team needed to know which companies to prioritize. The problem was traditional vendors couldn't provide the qualitative, specialized prospect data they needed, such as whether a company was building its own AI agents or specific mentions in financial filings. 

Pendo turned to Clay to embed AI into a structured workflow to surface these valuable insights. This allowed GTM engineer Zach Baumgarten to replace months of manual research and instead build custom account universes and signal framework to deliver a multi-product launch strategy.

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The problem
The solution
Use case
01

Defining and prioritizing accounts for new product launches

When Pendo launched Agent Analytics, the GTM team needed to identify companies building custom AI agents embedded in their own products, not companies using third-party tools. That distinction doesn't exist as a filter in any standard enrichment provider.

Zach used Claygents to research custom data points from multiple sources. Job postings surfaced which companies were hiring for agent development roles, and a custom data point summarized each posting to extract what exactly the company was building. Clay scraped 10-Ks and websites to find public companies mentioning AI agents, signaling strategic priority and a match for their offering. Marketing materials and product announcements revealed which companies were building their own agents versus buying off the shelf.

The output was a ranked list of roughly 13,000 top-fit accounts to target for each product, with prioritization based on ICP fit. Those lists were pushed into Salesforce as the source of truth for the entire sales org, with custom fields tagging accounts by their classification (AI-native, AI-forward, and so on). BDRs tasked with selling specific products now walk into calls knowing exactly what they're building toward based on their public signals.

For Agent Analytics launch, each target account was enriched with what they were building and where the product could fit. Clay-built lists helped identify over 55% of revenue sold with Agent Analytics in its first quarter, driving two-thirds of its total pipeline. The launch exceeded 200% of the Q1 sales targets. 

"Within a week, we had the accounts we wanted to target, prioritized, with personalized custom messaging specific to both the account and the contact," Zach says. "We're spending a lot of time focusing on strategy rather than the mechanics of pulling data."

The same architecture was replicated across Pendo’s full suite of new offerings. Each product has its own Clay-built account list that ranks companies against product-specific ICP criteria. That work would have taken months with manual research. Zach built the first version in Clay in two days.

Use case
02

Compressing time-to-value on inbound and event follow-up

On the inbound side, Evan builds Clay tables that turn event attendees and high-intent signals into outbound-ready sequences within hours. Previously, event follow-up meant BDRs working through generic sequences, or writing semi-customized emails at a scale that wasn't realistic given the volume.

Now, Evan can build a campaign table that pulls in the enriched data points for each prospect and generates customized messaging. The emails are ready for BDRs to review before sending, saving them hours of manual followups. He tests different AI models against the same prompts to fine-tune which produces the most effective copy for different campaign types.

For Pendo's Autumn Release campaign, this approach contributed to a +110% increase in pipeline impact. The difference wasn't just speed. "The content in the email is a lot more human," Evan says. "That's been the biggest before-and-after change on the inbound side."

Use case
03
Use case
04
Use case
05
Clay's impact

Custom data as the foundation for new GTM plays

Pendo used Clay to build a repeatable system for launching go-to-market motions on entirely new products. When the company needed to identify and prioritize accounts for Agent Analytics, the GTM team had a ranked list of 13,000 accounts in Salesforce within two days. When they needed event follow-up to convert faster, inbound pipeline doubled. 

The same architecture now underpins every new product launch, giving sales leaders a direct line from strategy to execution without waiting on manual research or traditional data vendors.

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