Demand by Omni Lab

Every revenue team has had the argument. Marketing says they sourced it. Sales says they sourced it. The CRM has one field, one answer, and neither side trusts the number. What looks like a reporting problem is usually something deeper — a structural conflict baked into how teams are measured, compensated, and held accountable.

Nick Turner from Dreamdata works at the intersection of this problem every day. Dreamdata is a B2B revenue attribution platform built to give go-to-market teams a clearer picture of how pipeline actually forms across long, multi-touch buying journeys. Nick brings a practitioner's view on why the attribution fight persists, what it quietly costs companies who let it fester, and where the current model breaks down most visibly.

In this episode, we get into the mechanics of the fight — why comp structures reinforce it, why better tooling does not automatically end it, and what it would actually take for sales and marketing to stop competing over credit and start competing for revenue together.

Sales teams have been stuck in the same operational loop for years. Reps spend the majority of their time on research, list building, and administrative work instead of selling. Most organizations have accepted this as normal. The question is whether AI is finally changing the math or just adding more tools to a broken system.

Liam Collins from Instantly.ai joins the show to break down where AI is actually delivering in the sales process versus where the hype is outrunning reality. He brings a practitioner's view of what it takes to build modern GTM systems, from autonomous agents that handle full workflows to no-code tools that put that power in the hands of business operators without engineering support.

This episode covers what the shift toward GTM Engineering means for revenue teams, how the best salespeople are evolving from prospectors into system designers, and what a leaner, more automated go-to-market organization looks like in practice.

Most B2B attribution tools are built for enterprise buyers with large budgets, long sales cycles, and a dedicated ops team to hold it all together. The result is a market where smaller and mid-market SaaS companies running serious LinkedIn programs have had to either overpay, underinvest, or work around tools that were never designed for them.

Adam Holmgren is the co-founder of Fibbler, an attribution tool for marketing teams. Rather than going after the same enterprise buyers as the incumbents, Adam and his team made a deliberate bet on product-led growth and transactional pricing in a market where competitors anchored deals at north of $10k ACV. That decision shaped everything from the first feature they built to their approach to early customer research.

In this episode, Adam walks through how the idea for Fibbler was validated, why LinkedIn pipeline influence was the first and only focus before anything else was added, and what it actually looks like to build GTM strategy around a segment your competitors have largely ignored.

Most marketing teams are optimizing for the wrong thing. Traffic looks good in a dashboard, but it tells you almost nothing about whether the right companies are finding you, engaging with your content, or moving toward a buying decision. The obsession with volume has pushed marketers toward channels that are easy to measure and away from channels that actually influence pipeline.

Jamie Pagan from Leadfeeder joins the show to challenge how B2B SaaS marketers evaluate channel performance. The conversation centers on a deceptively simple framework: there is a difference between being present in a channel and being visible to the buyers who matter. Most teams are doing the former and calling it demand generation.

In this episode, we get into how to judge any channel using three signals: engagement, intent, and ICP fit. We walk through a real example in which a small channel outperformed one that generated 80 times more traffic. And we get into how AI tools like the Leadfeeder MCP, paired with Claude, are changing the way marketers can actually interrogate their data, moving from static dashboards to real conversations with the numbers.

Most B2B SaaS marketing teams say they run ABM. Very few actually do. The line between demand gen and ABM has blurred for over a decade, partly because vendors had a financial interest in keeping it that way, and partly because treating ABM as a targeted campaign is easier than treating it as a business strategy. The result is many small account lists dressed up as strategic programs with nothing underneath.

This episode explains what that distinction means in practice. The conversation covers how a real ABM program starts with a business objective, not a platform, and why that changes who owns it, who funds it, and what it can actually accomplish. Tyler Pleiss brings a practitioner perspective on where these motions break down and what it costs companies when they get the framing wrong.

Listeners will come away with a clearer framework for deciding which motion fits their current situation, how to structure the internal conversation around ABM ownership, and what to look for when a program has drifted from strategy back into campaign mode.

Most marketing teams are optimizing for the wrong thing. Traffic looks good in a dashboard, but it tells you almost nothing about whether the right companies are finding you, engaging with your content, or moving toward a buying decision. The obsession with volume has pushed marketers toward channels that are easy to measure and away from channels that actually influence pipeline.

Jamie Pagan from Leadfeeder joins the show to challenge how B2B SaaS marketers evaluate channel performance. The conversation centers on a deceptively simple framework: there is a difference between being present in a channel and being visible to the buyers who matter. Most teams are doing the former and calling it demand generation.

In this episode, we get into how to judge any channel using three signals: engagement, intent, and ICP fit. We walk through a real example in which a small channel outperformed one that generated 80 times more traffic. And we get into how AI tools like the Leadfeeder MCP, paired with Claude, are changing the way marketers can actually interrogate their data, moving from static dashboards to real conversations with the numbers.

Most marketing teams are optimizing for the wrong thing. Traffic looks good in a dashboard, but it tells you almost nothing about whether the right companies are finding you, engaging with your content, or moving toward a buying decision. The obsession with volume has pushed marketers toward channels that are easy to measure and away from channels that actually influence pipeline.

Jamie Pagan from Leadfeeder joins the show to challenge how B2B SaaS marketers evaluate channel performance. The conversation centers on a deceptively simple framework: there is a difference between being present in a channel and being visible to the buyers who matter. Most teams are doing the former and calling it demand generation.

In this episode, we get into how to judge any channel using three signals: engagement, intent, and ICP fit. We walk through a real example in which a small channel outperformed one that generated 80 times more traffic. And we get into how AI tools like the Leadfeeder MCP, paired with Claude, are changing the way marketers can actually interrogate their data, moving from static dashboards to real conversations with the numbers.

Most B2B SaaS marketing teams say they run ABM. Very few actually do. The line between demand gen and ABM has blurred for over a decade, partly because vendors had a financial interest in keeping it that way, and partly because treating ABM as a targeted campaign is easier than treating it as a business strategy. The result is many small account lists dressed up as strategic programs with nothing underneath.

This episode explains what that distinction means in practice. The conversation covers how a real ABM program starts with a business objective, not a platform, and why that changes who owns it, who funds it, and what it can actually accomplish. Tyler Pleiss brings a practitioner perspective on where these motions break down and what it costs companies when they get the framing wrong.

Listeners will come away with a clearer framework for deciding which motion fits their current situation, how to structure the internal conversation around ABM ownership, and what to look for when a program has drifted from strategy back into campaign mode.

ABM was supposed to fix the waste in B2B marketing. And when it's done right, it does. The problem is that most teams aren't doing it right, and deep down, they already know it.

Lists of target accounts that sales never bought into. Intent data subscriptions that surface the same signals every competitor is already acting on. Coordinated campaigns that look impressive in a deck but never quite produce the pipeline they promised. These aren't signs that ABM doesn't work. There are signs that the strategy got watered down somewhere between the whiteboard and execution.

Andrei Zinkevich has spent years working with B2B SaaS teams on full-funnel demand generation and ABM strategy. He's seen both ends of the spectrum: programs that quietly burn budget for months while leadership reverse-engineers metrics to justify the spend, and programs that get it right by making a few uncomfortable changes first. His view is clear: the strategy isn't the problem. The implementation usually is.

In this episode, we get into the hard questions. Is intent data creating smarter outreach or just faster spam? Are companies confusing account volume with strategic focus? And if ABM requires true sales and marketing alignment, which most organizations don't have, what has to change before the rest of it can work?

In this episode of Demand, host Jonathan Bland sits down with Kurt Dunphy, the driving force behind Spellbook - the AI-powered legal companion that's revolutionizing how commercial lawyers work. Kurt shares the remarkable story of how Spellbook achieved 20x growth since Q1 2023 through a strategic pivot in their approach to AI and branding.

Discover how Spellbook transformed from a promising legal tech solution into an indispensable AI companion for commercial lawyers worldwide. Kurt candidly discusses the challenges of aligning his team during the pivot, the stress of making bold strategic decisions, and the unexpected wins that followed. He reveals the moment they realized a pivot was necessary and the uncommon insights gained along the way.

For B2B marketing leaders and growth professionals, this episode offers valuable lessons in:

- Recognizing and acting on market signals that demand strategic shifts

- Managing team dynamics during major pivots

- Scaling growth through precise positioning and messaging

- Leveraging AI trends to accelerate market penetration

- Building and maintaining momentum after a successful pivot