Table of Contents

About Guest

Eric Quanstrom is the Vice President of Go-To-Market Engineering at Apollo.io, an AI-powered sales intelligence and engagement platform that helps businesses build pipeline and grow revenue. He leads initiatives that help Apollo's highest-revenue customers sharpen their GTM strategies, improve sales efficiency, and put data and AI to work for better revenue outcomes. Eric brings more than a decade of experience in technology, marketing, and growth, and previously served as CMO at Cience. His expertise spans demand generation, sales development, signal-based selling, and building scalable go-to-market systems.

In this Workshop

B2B SaaS GTM teams spent the last decade making outbound faster, with more data, more automation, and more channels. Yet getting a buyer's attention is harder than ever. So if sending got easier, why did getting a reply get harder, and what does it mean for B2B SaaS pipeline generation?

In this workshop, Alex Gluz speaks with Eric Quanstrom, VP of GTM Engineering at Apollo.io, about how modern B2B SaaS GTM teams win with less noise and more relevance. Eric explains why a decade of efficiency gains made outbound less effective, and why relevance is the hurdle every GTM motion has to clear. He breaks down how signal-based selling changes who you prioritize and when, from funding rounds to job change alerts, and how to use AI as a Venn diagram between what you know about the buyer and what you sell. The conversation also covers the three filters every buyer runs on outreach, how cutting tool sprawl lowers CAC, why AEO is replacing SEO, and why the future of sales is semi-automation, with humans still at the center of every meaningful buying conversation.

Workshop Highlights:

05:56 – Why relevance is the hurdle every B2B revenue motion has to clear

07:34 – How to build the buyer signals that actually matter

09:36 – Why job change alerts are the most underrated buyer signal

13:20 – Using AI as a Venn diagram between buyer signals and your value proposition

17:20 – Why me, why now, why care: the three filters that decide relevance

18:45 – How intent data, inbound and web signals sharpen lead prioritization

21:04 – How signal-based prioritization lowers CAC and grows revenue

27:40 – Why AI will tee up more human sales conversations, not replace them

31:14 – Why companies are already pulling back on token budgets and AI agents

32:29 – What's next for AI at Apollo: open integrations, AI studio, and next best action

Resources Mentioned

• Alex Gluz on LinkedIn
• Eric Quanstrom on LinkedIn
• Apollo.io
• Pocus
• Claude Code
• ChatGPT
• Codex
• Perplexity
• Gemini
• Lovable
• Replit
• Slack

Quotable Moments

"Virtually every go-to-market channel is saturated."

"It's very easy to go grab very large lists and … work your way … A to Z down them, which is in my humble opinion … the absence of strategy."

"The brain usually goes through three filters very subconsciously. Why me? Why now? Why care?"

"We want more control. We want more humanness in the process. It can't just be agents let loose on the world."

"Telling isn't selling."

Action Steps

• Start with "know thyself" before choosing signals: Define the problems, needs and objectives that make your story valuable, then map them to the triggers that show a buyer is ready.
• Set up a job change listening channel for past buyers: Champions who move to a new company already know your brand, which makes them some of the warmest prospects you can reach.
• Make every touch answer why me, why now and why care: Outreach that clears these three filters earns a reply instead of a delete.
• Cut the login tax across your sales stack: Fewer tools and seats mean less switching, lower CAC, and more time for reps to have real sales conversations.
• Architect the aha moment instead of telling: Help buyers reach their own conclusions about why you're the right fit, because ideas from their own heads land hardest.