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"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.

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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.

The most common GTM mistake is hiring execution-oriented leaders who force a pre-existing playbook onto a new company. Each company's customer journey is unique and requires a first-principles approach to design a GTM motion, rather than cutting and pasting a strategy that worked elsewhere.

Smart leaders end up in panic mode not because their tactics are wrong, but because their entire data infrastructure is broken. They are using a data model built for a simple lead-gen era to answer complex questions about today's nuanced buyer journeys, leading to reactive, tactical decisions instead of strategic ones.

The idea that GTM playbooks are broken is a dangerous myth. Veteran B2B leaders are successfully running top AI companies using the same fundamental plays (inbound, demos). The difference is adapting to new tools and overwhelming demand, not reinventing the core strategies that have always worked. The 2021 version is obsolete, but the fundamentals are not.

The go-to-market tool market is fragmented because sales tactics have a short shelf life, quickly rendering point solutions obsolete. The future belongs to integrated platforms that act as an "IDE" (Integrated Development Environment), allowing teams to rapidly experiment, iterate, and execute new GTM strategies.

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.

In B2B sales with multiple decision-makers, tracking individual MQLs is a "lazy metric" that misrepresents buying intent. Success depends on identifying and engaging the entire buying group. Marketing's goal should be to qualify the group, not just a single lead.

Core GTM tactics like outbound, events, and content marketing remain highly effective for AI companies. The failure isn't in the plays themselves, but in using outdated, generic playbooks. Success comes from applying these same plays with more intelligence, scale, and AI-driven personalization.

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.

Companies stay stuck in failing models for three reasons: 1) The system rewards controllable but ineffective activity (more calls, more MQLs). 2) Leaders fear the perceived risk of foundational change. 3) A culture of urgency favors quick tactical fixes over addressing deep, systemic issues.