Stacking Growth | The B2B Marketing Podcast

Megan Bowen doesn't call self-care optional. As CEO of Refine Labs, she calls it a leadership obligation — skip it, and the fallout shows up in your company's culture whether you notice or not.

On this episode of Lodestar, Cliff Simon talks with Megan Bowen about scaling a B2B agency to 300+ clients, becoming majority owner in 2025, and the philosophy behind Refine Labs' 50%+ jump in retention: people first, customers second, company bottom line third — the reverse of how most B2B orgs are actually run. They also get into AI-driven martech consolidation, why buyer research shouldn't be an annual event, and the daily non-negotiables (meditation, long walks, lifting) that keep Megan out of burnout.

Topics covered: Marketing Maturity Model · internal alignment via data · HubSpot vs. Marketo · AI and martech consolidation · majority ownership transition · talent destination culture · people-pleasing recovery · CEO mental health · building a company that outlasts its founder

FAQ

Q: What does Megan Bowen mean by "people success is customer success is company success"?
A: It's a reversal of the typical B2B priority order (customer bottom line → company bottom line → team as afterthought). Megan argues that prioritizing the team first is what actually drives sustainable customer and company outcomes.

Q: How did Refine Labs improve retention by over 50%?
A: By investing heavily in people-first infrastructure — new roles, leadership layers, and tools — built out significantly more in the past year than in the agency's prior two years combined.

Q: What daily habits does Megan Bowen use to manage stress as a CEO?
A: Meditation (a single 23-minute session she returns to), walking 5-10 miles a day, weightlifting four days a week, and protecting daily alone time to decompress from being "on" socially all day.

Q: Why is Megan Bowen building Refine Labs to operate without her?
A: She sees long-term resilience as the goal — a company whose existence isn't solely dependent on its founder, which requires deliberately empowering the team to make decisions without her.

#Lodestar #B2BLeadership #CEOPodcast #RefineLabs #GTMStrategy #FounderWellbeing #B2BSaaS #MarketingLeadership #BurnoutPrevention #PeopleFirstCulture

Generative Engine Optimization (GEO) is the practice of structuring B2B content so AI tools like ChatGPT, Gemini, Claude, and Perplexity cite your brand by name, instead of just ranking your website in Google. This episode breaks down David Kirkdorffer's incredible playbook on why traditional SEO alone no longer guarantees visibility, now that 89% of B2B buyers use generative AI somewhere in their purchase process (Forrester) and Google's AI Overviews appear in 74% of problem-solving search queries (Search Engine Journal).

We cover:

• The difference between SEO (ranking in search results) and GEO (being cited inside AI-generated answers)
• The three things AI models actually look for before mentioning a brand: credibility, consistency, and structure
• Why gated PDFs, tabbed website content, and un-transcribed webinars are invisible to AI, even when the content itself is strong
• How to manually test whether your brand shows up when buyers ask ChatGPT, Gemini, and Perplexity about your category
• Three fixes any B2B marketing team can make this week to improve AI visibility

Whether you're a CMO, content marketer, or SEO lead trying to understand what Generative Engine Optimization (GEO) means for your 2026 strategy, this episode gives you the framework and the first three action items.

Ben Reed walks through his full journey as the first (and for a while, only) marketer at FieldPulse — a construction/trades field service software startup competing against Service Titan, Jobber, and Housecall Pro — through 300%+ revenue growth and a team of 12, and into his first 60 days as VP Marketing at Ressio.

In this roundtable, Ben covers:

• Finding a $5–10K ACV market gap between larger and smaller competitors
• Why he hired a videographer as his second marketing hire
• How FieldPulse's YouTube content started outranking Google search results
• Turning field events from badge-scanning into 100+ qualified meetings per show
• His Meta Ads playbook, campaign objective strategy, and the Andromeda algorithm shift
• Scaling a marketing team from 1 to 12 people, tied to revenue targets
• What he's doing differently in his first 60 days at Resio: product marketing, positioning, SEO, and customer ambassadors

A tactical breakdown for B2B marketing leaders on go-to-market strategy, ICP positioning, demand generation, paid social, field events, and team scaling in a competitive vertical SaaS market.

#B2BMarketing #DemandGeneration #GTMStrategy #MarketingLeadership #PaidSocial #FieldMarketing #ProductMarketing #SaaSMarketing #MetaAds #ICP

Everyone's plugging Meta, Google, and LinkedIn straight into AI via MCP and asking it where to spend their next ad dollar. Matt Chanella breaks down why that's exactly backwards — and why AI is going to make your ads more expensive, not more effective.

In this episode of B2B Reality Check, Matt unpacks the two traps every B2B ad team falls into when they outsource strategy to AI:

→ AI generates infinite creative variations — far more than you could ever run to statistical significance
→ AI ad reporting always defaults to raw conversion volume, with zero context on campaign goals, funnel stage, or lead quality

Matt walks through why offline conversion tracking is the bare minimum, how to structure your AI context (project files, skills, clean conversion hierarchy) before you ever ask it to analyze spend, and why AI should be a thinking partner — not the decision-maker — for your ad strategy.

In this episode:

• Why lower barriers to entry for AI-generated ads don't mean better ad performance
• The statistical significance problem with AI-generated creative testing
• Why AI ad reporting can't distinguish high-intent conversions from low-intent ones (scroll depth, newsletter signups vs. booked meetings)
• How to give AI the right context before letting it touch your ad reporting
• Why not every campaign (YouTube pre-roll, CTV, LinkedIn thought leadership) is designed for direct response

FAQ

Q: Can AI accurately tell me where to spend my next ad dollar?
A: No — AI tools connected to your ad platforms track conversion volume and signal, but they can't tell you conversion quality: how many conversions become booked meetings, opportunities, or closed deals.

Q: Why shouldn't I let AI generate all my ad creative variations?
A: AI can produce far more creative iterations than you could ever run to statistical significance. Without a proper testing ramp and enough audience/budget to reach significance, you can't actually determine a winning message.

Q: What's the minimum conversion tracking needed before using AI for ad strategy?
A: Offline conversion tracking is the minimally viable setup — and even then, it should only be used for reporting, not for AI to dictate strategy.

Q: Why does AI ad reporting always favor lead-gen campaigns?
A: AI has no context on campaign objectives, measurement methodology (multi-touch, influenced, incrementality), or whether a campaign was designed for direct response versus brand consideration (the 95-5 principle). It defaults to whichever campaign produced the most raw conversions.

Q: How do I set AI up correctly before using it for ad reporting?
A: Build a project or skill collection with full context on your ad goals, objectives, segmentation, targeting, and measurement approach — before you ever ask it to analyze performance.

🔔 Follow Matt Chanella and Refine Labs for more B2B Reality Check breakdowns.
📩 Sign up for the Refine Labs newsletter and register for our B2B roundtable events.
👉 Follow our CEO Megan Bowen for more GTM insight.

#B2BMarketing #AIAdvertising #DemandGeneration #MarketingStrategy #B2BRealityCheck #GTMStrategy #AdOptimization #PerformanceMarketing #MarketingAnalytics #B2BSaaS #RefineLabs #LinkedInAds #ConversionTracking #MarTech

Most ABM programs fail before the first campaign launches — because the account list is wrong, the incentives are broken, and marketing is measuring the wrong things.

In this episode, Matt Sciannella sits down with Sidney Waterfall (Head of Marketing, Open Brand) and Sam Kuehnle (VP Marketing, Loxo) — two former Refine Labs marketers now running completely different ABM motions at completely different companies — to break down what a real ABM program looks like in 2025.

They cover:
— How to build and tier a target account list (and why sales shouldn't do it alone)
— The commission structure mistake that was silently killing 4x pipeline growth
— Why Sidney refused a marketing-attributed pipeline goal — and what she tracks instead
— The 80/20 LinkedIn ad strategy Loxo uses to stay visible in a crowded market
— Meta ads for a 3,000-account B2B list: what happened when they tried it
— How AI is actually being used inside real ABM programs right now

Whether you're managing 20 strategic accounts or a universe of 200,000, this episode has something to pressure-test in your current motion.

Keywords: ABM strategy, account-based marketing, B2B demand generation, pipeline growth, B2B marketing podcast, target account list, marketing attribution, PLG SLG, LinkedIn ads B2B, in-house marketing strategy.

Marketers own promotion — but most B2B promotion is just coercion dressed up as demand gen. Matt and Liam unpack why the standard playbook of fear messaging, demo CTAs, and incentivized meetings fails, and what a real offer actually looks like when it's built from genuine customer understanding. One of the most practically useful conversations on B2B advertising and offer design you'll find. Keywords: B2B offer design, demand generation, performance marketing, B2B advertising, outbound, demo offers, buyer psychology, SaaS marketing

Place in B2B used to mean partnerships, system integrators, and analyst relations. Now everyone's adding AEO and GEO to the list. But Matt and Liam question whether being mentioned by an LLM actually changes buying behavior — or whether it's just a new version of the same old "just get in front of people" fallacy. A grounded, skeptical conversation about what distribution really means when your product lives in the cloud.

Keywords: GEO, AEO, B2B distribution strategy, B2B SaaS go-to-market, AI search marketing, brand consideration

Pricing is the most avoided conversation in B2B marketing. It's handed down from finance, rubber-stamped by sales, and marketers are expected to promote whatever number comes out. Matt and Liam make the case that pricing is actually a marketing problem — and that the explosion of "no decision" outcomes in B2B SaaS is largely a symptom of not understanding how buyers think about value relative to cost.

Keywords: B2B SaaS pricing, pricing strategy, marketing and finance alignment, go-to-market, buyer psychology

"A CRO told us the word our customers cared about most was extensibility. I'm a marketer — I've never used that word in my life."When was the last time marketing had a real say in what got built? In most B2B SaaS companies, engineers and founders own the product, and marketers inherit whatever comes out the other end. Matt Sciannella and Liam Moroney explore what it would look like for marketers to genuinely influence product direction — not by taking over, but by asking the questions nobody else is asking. Keywords: B2B marketing strategy, product marketing, market research, customer discovery, SaaS go-to-market.

Megan Bowen is the CEO and majority owner of Refine Labs, one of the few B2B demand generation agencies that has built its entire model around the problem most agencies refuse to name: demand capture is easy to measure, demand creation is not — and most companies are spending almost entirely on the former.

In this episode, Megan explains why AI doesn't scare her, how the Brand Demand Expand framework maps to core business fundamentals, and what it actually looks like to help a $500M company change how it measures marketing ROI. She also shares the three skills she believes every B2B marketer needs to develop right now, her no-asshole client rule, and the change management playbook she's used to turn around demand gen programs from the inside.

If your pipeline has plateaued and your demand gen team can't explain why, this episode is for you.

Topics: B2B marketing, demand generation, brand strategy, marketing attribution, change management, AI in marketing, agency leadership, GTM strategy, marketing skills, customer success, pipeline growth