10 buyer interactions rewired 7 years of marketing theory.

The Buyer Flywheel - Co-Created

The Buyer Flywheel emerged after 4 years of experimenting and testing, like any theory deserves. It's why I expect it to outperform linear funnels for $5-20M SaaS teams.

Origin Story

7 years of B2B SaaS marketing theory crashed into reality during 10 product-market fit calls with SMB prospects. The pattern was unmistakable: buyers and customers aren't the same entity.

• Buyers approve budgets and evaluate ROI.

• Customers use products and judge usability.

• Traditional funnels treat them as one person - us marketers have our eyes on buyers while customers are the baseline?

The Buyer's Question,"Will it pay?"

They face political risk and need business cases, financial proofs, and executive-level content that justifies the investment decision.

The Customer's Question, "Will it work?"

They face practical risk and need tutorials, onboarding clarity, and operational content that ensures successful implementation.

Great SaaS stories respect both perspectives. And the most successful lead generation happens when we co-create value with prospects.

• Not broadcast messaging.

• Not linear nurture sequences.

True collaboration becomes the foundation for the Flywheel

1. Surfaces friction,

2. Shapes resonant messaging,

3. Validates relevance through systematic experimentation, and

4. Drives lead gen

[Repeat]

Born at the Intersection of Theory and Function

Opinion-based marketing, that not this. It's research-backed methodology built on insights from the world's leading customer acquisition experts.

• Jobs-to-be-Done (JTBD)

  • Primary research with 50+ SaaS SME leaders uncovered the functional, emotional, and social jobs they hire your service to do—fueling every stage of the flywheel.

• Voice of the Customer (VoC)

  • Three feedback loops (high-touch interviews, micro-surveys/polls, and behavioral data analysis) ensure every insight is sourced from real buyer language and signals.

• Peter Fader at Wharton

  • Demonstrates that pre-purchase acquisition objectives differ fundamentally from post-purchase retention objectives. His CLV modeling inherently separates tactics before and after the first purchase. Though he never calls out the difference.

• Byron Sharp at Ehrenberg-Bass Institute

  • Argues that mental and physical availability drives buyer acquisition more effectively than traditional customer retention approaches. His empirical research shows acquisition focus outperforms retention focus for growth.

• Eva Ascarza at Harvard

  • Proves through machine learning that behavioral cues after first purchase differ dramatically from pre-purchase signals, warranting completely distinct approaches for buyers versus customers.

• ABM practitioners

  • Distinguish between buyer intent signals and customer success signals, recognizing that pre-purchase engagement tactics must differ from post-purchase expansion efforts.

| Not to mention "the user" as a separate entity from the "buyer" or the "customer." |

Academic buyer research provides the foundation, but operational discipline drives results.

Traditional approaches -> generic buyer personas, broad market segments, and campaign-and-pray tactics.

The flywheel approach -> implements channel friction sweeps, weekly resonance stand-ups, systematic insight application, and measurable progression tracking.

The difference is moving from theoretical frameworks to operational discipline that produces consistent, measurable outcomes.

All conjecture until it's proven. If you are one a SaaS SMB CXO, and are willing to dip your toe in freezing cold currents, write in, or LinkedIn DM, or a form fill will do just fine.

Whatever floats your boat.

But one thing we know...

| Executives act on clarity, not kaleidoscopes. |

KPIs (and a minimalist outlook)

The Buyer Flywheel emerged after 4 years of experimenting and testing, like any theory deserves. It's why I expect it to outperform linear funnels for $5-20M SaaS teams.

Boston Consulting Group, in their April 2025 report, "Accelerating AI-Driven Marketing Maturity," calls it.

• Marketing maturity is down 8% since 2021.

• Marketers get more dashboards, less insight. That's drowning in fast, fragmented data. Data from every channel hits like a tidal wave - websites, apps, socials, CRM, retail.

• These are non-negotiable for real impact.

• Bottom line:

  • More data ≠ better marketing.

  • More data ≠ better chances for marketing to make use of.

  • Maturity stalls when teams can’t cut the noise or execute.