Jon Miller, who helped popularize the MQL, now compares its linear funnel to the geocentric model of the solar system. He argues it was a once-useful simplification that no longer reflects the complex, nonlinear reality of B2B buying, as it ignores the most important, untrackable parts of the journey.

Traditional funnels jump from a marketing signal (like an MQL) to an opportunity, creating a blind spot. They miss the 'Engagement' period of initial interaction and the 'Prospecting' phase of active sales pursuit. Ignoring these stages makes it impossible to diagnose performance issues or identify improvement levers.

A critical insight from Refine Labs is that what marketers call a "funnel" isn't a map of customer behavior, but a framework for an internal sales process. This common misinterpretation leads marketing teams to incorrectly believe they are modeling the buyer's journey when they are merely tracking their own operational stages.

Most GTM systems track initial outreach and final outcomes but fail to quantify the critical journey in between. This "ginormous gray area" of engagement makes it impossible to understand which activities truly influence pipeline, leading to flawed, outcome-based decision-making instead of journey-based optimization.

"Path dependency" is when past decisions, like adopting the MQL waterfall, constrain current strategy even though the market has changed. GTM teams get stuck trying to optimize a legacy, linear framework for today's non-linear buyer, preventing real innovation and ensuring suboptimal results.

The marketing funnel's resilience isn't just inertia. It's systemically reinforced from both ends of a marketer's career. Universities teach it as a foundational concept, and leadership (CEOs, boards) demands its simplicity for reporting, leaving practitioners in the middle unable to drive change without significant career risk.

With buyers completing nearly 80% of their research using tools like Generative AI before vendor contact, the linear funnel is dead. Traditional metrics like MQLs and SQLs are meaningless. Go-to-market strategies must be rewritten to influence buyers during their independent, non-linear discovery phase.

The issue with metrics like MQLs is rooted in CRM architecture. A single lead record cannot accurately reflect the non-linear reality of a buyer's journey, which involves multiple cycles of engagement and disqualification. Historical data gets overwritten, obscuring the true path to conversion.

AI is making buyer journeys non-linear and compressed. Instead of a linear funnel, GTM strategy must shift to a continuous, customer-centric "flywheel" model. Buyers conduct deep research upfront, making direct sales engagement optional for some and requiring an always-on, value-first approach.