Building a 2-Table ABM Pipeline for RevOps Leaders with No Prior Experience Using Clay

·May 18, 2026 05:32 PM·

Hello everyone! First time posting here 👋 ~2 hours. Free plan. Zero Clay experience going in. Built a 2-table ABM pipeline targeting RevOps leaders at 20 B2B SaaS companies: Account Intelligence → enriched with Apollo firmographics, Claygent research on funding rounds, hiring signals, and tech stack, then scored and tiered every account using an AI-powered ICP formula Contact Enrichment → found decision-makers using People Search with title and seniority filters, ran a 5-provider email waterfall, generated AI personalized outreach The number that stuck with me as it is not a minor improvement. That gap is why waterfalls matter. Single provider → 36% email coverage Five-provider waterfall → 71% Figured the best way to break into GTM is to start building in it. What would you add or do differently?

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4 comments

· Sorted by Oldest

Adam S.
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One thing worth exploring, the public presence of these RevOps contacts online. I built an contact targeting table and had Clay prioritize the targets based on how much available content there is online for them. So for example if they have been interviewed on podcasts, linkedin posts, interviews for articles etc. That is good additional info to layer in when building out messaging
Alisha G.
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Hi Adam, Love that idea, Adam. This will make the personalization way more authentic when there's actual content to reference. How did you pull the public presence data — Claygent or a specific integration?
Adam S.
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I use this information to help form my scoring criteria for accounts. The column is called Leadership Accessibility. I use Claygent to go out and search for the following: Positive signals include: - Named CIO, CISO, or senior IT / security leader - Leaders quoted in news articles or press releases - Participation in industry panels, associations, or public forums - Evidence of leadership visibility or thought leadership Keep in mind that for me, this really just identifies the names of the active leaders in the market. Once Clay identifies those names and title, I then have ChatGPT do a deeper dive. This could probably be all done within Clay, I just haven't taken the time to do it.
Alisha G.
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That's a smart way to layer in intent signals — using public presence as a proxy for accessibility makes the scoring much more meaningful. I like the idea of combining Claygent for discovery and ChatGPT for the deeper dive. I will try to add a Leadership Accessibility column to my next build and see how it changes the tiering. Thanks for breaking that down!