Clay’s Secret to Scaling to $3B (Head of Marketing Explains)

TLDR: The community playbook that built a $3B valuation

Bruno Estrella, Head of Marketing at Clay, joined as employee #20 and helped architect the community-driven growth engine behind Clay's explosive growth. Before Clay, Bruno built similar community-driven growth engines at Webflow, working with a team of 12 people on the growth marketing side.

Listen to this episode to learn why community-led growth only works for specific product types, how Clay's creator program economics changed the game for partner agencies, and the exact LinkedIn engagement workflow Clay uses to align their entire GTM team on qualified prospects.

Meet the guest: Bruno Estrella, Head of Marketing at Clay

Bruno Estrella is Head of Marketing at Clay, where he joined as employee #20 and transitioned from growth marketing to leading the entire marketing function. His background includes building community-driven growth engines at Webflow and running an outbound agency, which gave him unique insight into the problem Clay solves.

Bruno's outbound agency experience helped him immediately recognize Clay's potential when he first saw the product in mid-2023. The waterfall enrichment logic and Claygent capabilities represented solutions to problems he'd been solving manually for years with engineers and spreadsheets.

Chapters

[00:23] Bruno's excitement about finally joining the podcast after postponing

[01:41] How Bruno joined as employee #20 and transitioned from growth marketing to Head of Marketing

[03:11] The community playbook origins: What Bruno learned at Webflow and why it only works for flexible, powerful products

[06:48] How Bruno's outbound agency background helped him spot Clay's $3B potential

[19:21] Enterprise vs PLG revenue split: How six-figure enterprise deals complement self-serve growth

[22:24] The challenge of scaling PLG and sales-led motions simultaneously without killing brand love

[28:26] What doesn't work: Complex processes too early, over-reliance on attribution models, and the human-intensive challenges of community programs

[36:39] Clay's internal marketing stack: Qualified engagement tracking and named account targeting through LinkedIn API integration

[44:07] The future of AI product growth: Speed of execution, novelty effects, and which products will survive

Key Insights

Community-led growth only works when your product enables users to build businesses on top of it.

Bruno explains the fundamental requirement most companies miss: "Most of the communities that are centralized around a product is because the product is flexible and powerful and the product enables people to actually build businesses on top of the product." Clay's community thrives because agencies have scaled to millions in revenue using the platform.

When users can build independent businesses on a product, they naturally invest time learning advanced workflows, creating organic demand for knowledge sharing. Without this business-building capability, community efforts become forced rather than organic.

Clay's creator program economics changed everything for ecosystem partners.

"Then you have like brand validation from Clay. Whenever there's a client that comes and visit your profile or your website, there's clear validation," Bruno explains. Clay's 20% commission for 12 months provides substantial recurring income while the brand association adds credibility that helps partners win clients.

As we discuss in the episode, our business at Understory has generated millions of dollars from being recognized as a top Clay agency. The program works because Clay validates partners' expertise through table submissions and client service quality, maintaining brand integrity while enabling partner growth.

Attribution models fail for PLG products with long, complex buyer journeys.

Bruno learned this the hard way: "When you have pure click-through and attribution models as your core, as your Bible for decision-making, you just fail so much to see the bigger picture." When examining Clay's click-based and cookie-based attribution models, LinkedIn appears as only a small portion, yet when talking to customers directly, LinkedIn is clearly central to their core ICP's activity.

Rather than relying solely on attribution and tracking, SaaS growth leaders benefit from balancing quantitative tracking with regular qualitative customer interviews to understand true influence patterns.

Enterprise motion becomes inevitable as PLG success attracts larger companies.

"Every PLG company in the world has to get into an SLG motion," Bruno notes, citing Figma, Airtable, and Notion. Clay's enterprise deals now reach six figures because large companies like Google, HubSpot, and OpenAI require security questionnaires, procurement processes, and hands-on customer success.

The challenge becomes balancing both motions without letting enterprise focus kill the community-driven PLG engine that creates brand awareness. As we discuss in the episode, we've seen this firsthand building Clay implementations for publicly traded companies where a single workflow augmented 20 people.

Clay's "qualified engagement" metric aligns their entire GTM team on one audience.

Through LinkedIn's official API in Clay, they track everyone tagging Clay, mentioning Clay, and engaging through comments and likes, then cross-reference with their named account list. "I can now go on top of our social and top of funnel team to be like, hey, you need to get a lift of qualified engagements, which are the same companies that the growth team is supposed to book meetings and generate pipeline," Bruno explains.

At Understory, we run a similar workflow that tracks engagement with GTM engineering and paid media content, enriches profiles through Claygent, and routes qualified prospects to outbound campaigns.

Speed of execution trumps sophisticated processes in early-stage growth.

Coming from Webflow where Bruno managed around 12 people, he initially tried implementing complex growth processes at Clay. "The reality is that when you are so early, you have to focus. Basically what I was doing is like, okay, let's actually look at revenue week over week. Let's look at the channels. Let's build the attribution," he reflects on the mistake.

Early-stage companies need brute force execution over analytical sophistication. This applies especially to AI products where market conditions change rapidly and first-mover advantages disappear quickly.

AI products grow through user-generated content and virality, not traditional channels.

"The way that AI products grow today are through user generated content and through virality. You tell others. And the underlying thing is because you want to look good. You want to sound smart," Bruno explains. Users share AI-powered workflows to demonstrate thought leadership and expertise, creating organic growth loops.

This pattern differs significantly from traditional SaaS growth and explains why companies like Clay, Cursor, and others scale so rapidly. The novelty effect creates initial adoption, but sustained growth requires solving genuine business-critical problems.

Community operations are incredibly human-intensive and mistake-prone.

Despite Clay's success, Bruno emphasizes the operational complexity: "It's very intensive operation. And so there's a lot of mistakes like, the wrong tool, the wrong person managing this, the wrong processes." Managing the partner program requires evaluating multiple dimensions: technical skill in Clay and client service quality. "We have to kick people out. It's such a tough conversation," Bruno admits.

The economics work at scale, but the operational complexity and human-intensive nature make community-led growth strategies challenging to execute.

Long-term thinking and willingness to sacrifice short-term compensation accelerate career growth.

When asked about career advice, Bruno emphasizes compound thinking: "You need to sort of think of, like, what are the conditions that I'm gonna put myself into these next few years that are gonna compound over time." He moved to San Francisco earlier in his career to immerse himself in the epicenter of his field.

As we discuss in the episode, Alex made a similar decision, leaving a $500,000 opportunity to build Understory, initially making only $2,000 his first month. Optimizing for learning environments and network development often provides better long-term returns than maximizing current salary.

Want more insight on implementing community-driven growth and GTM engineering in your SaaS strategy? Listen to the full episode on YouTube and subscribe to Understory's podcast for more insights on AI automation and SaaS growth strategy.

Looking to implement Clay-powered workflows that drive qualified pipelines? Book a call with Understory to explore how our GTM engineering expertise can build the automated outbound systems Bruno describes.