For years, much of marketing has been trapped in a deterministic mindset—rigid GTM (go-to-market) playbooks, account-based marketing (ABM) strategies driven by linear logic, and an obsession with predictable, mechanistic funnels. The problem? These models assume markets behave like clockwork, ignoring the messiness of reality.
Markets are complex adaptive systems. They don’t follow static cause-and-effect rules; they shift unpredictably, shaped by external forces, emergent customer behaviours, and adaptive operations. Yet, many commercial strategies still cling to frameworks that treat marketing as an isolated function rather than a sensory, proposition and communications network, a collection of disciplines within a broader, integrated commercial system.
The Fallacy of Deterministic Marketing Models
Many traditional, more formulaic GTM and ABM strategies rest on flawed assumptions:
Predictability Bias – These models assume that with enough data, outcomes can be predicted. But markets operate in complex domains (as per the Cynefin framework), where patterns only emerge retrospectively, not through linear forecasting.
Over-Optimisation for Efficiency – ABM and GTM often optimise for narrow, short-term gains, creating rigid systems that fail when market conditions change. Complex systems require resilience over efficiency—a principle well understood in adaptive strategy.
Ignoring External Forces – Deterministic models treat customer journeys as self-contained processes when, in reality, external shocks (economic shifts, competitive moves, geopolitical events) reshape demand in unpredictable ways.
Misunderstanding Market Science – Real-world marketing science often defies intuition. The Double Jeopardy Law, uncovered by Ehrenberg-Bass research, demonstrates that smaller brands suffer from both lower market penetration and weaker customer loyalty—not because of flawed engagement strategies, but due to the structural realities of competitive markets. Conventional ABM models, which emphasise deep relationships with small customer pools, often ignore this fundamental insight: sustainable growth comes from increasing reach, not just refining targeting. This is yet another example of how some approaches misinterpret complexity, leading to misguided commercial strategies.
A More Adaptive Approach: Marketing as a Sensor in an Integrated System
Marketing isn’t a set of pre-defined tactics—it should function as a real-time sensing mechanism, feeding insights into an adaptive commercial system that integrates propositons, communication, sales, operations, product, service and strategy. This shift means:
Focus on context and complexity - Rather than seeing the world through restrictive B2B amd B2C lenses, marketing should focus on understanding the changing context of markets, customers, buyers, influencers, customers and users and the relative complexity of their decision-making and behaviours.
Moving from funnels to networks – Instead of treating customers as passive targets within a linear journey, marketing should recognise interconnected decision-making ecosystems, where relationships, trust, and emergent behaviours shape demand.
Prioritising rapid learning over rigid execution – Strategies should be designed for continuous sensing, experimentation, and adaptation, borrowing from complex adaptive systems thinking.
Integrating commercial functions – Marketing alone can't drive growth. It must work within an interconnected system where sales, product, and operations evolve together based on market feedback.
The Future: Adaptive, Integrated Commercial Strategy
The world is too unpredictable for deterministic marketing playbooks. What’s needed is a more adaptive, integrated commercial strategy, where marketing serves as an intelligence network rather than a rigid execution engine. Organisations that embrace this complexity—rather than resist it—will outmaneuver those still clinging to obsolete, mechanistic frameworks.
It’s time to ditch the deterministic nonsense. The future belongs to those who can sense, adapt, and act—not those who assume markets are predictable.
Footnote: There may be markets or instances in marketing where the context and market complexity, decision-making processes and behaviours are simple or complicated, but not complex or chaotic. This is where best pratcice and good practice may work, where the casue and effect are obvious or where the cause and effect can be understood through analysis or expert knowledge. The problem is that the economic, technological and social context of markets keeps changing, markets are becomming more complex and more competitive, more innovative, with many moving parts. Customer and consumer behaviours are changing too, decision-makers and Decision-making Units must deal with increasing volatility, uncertainty, complexity and ambiguity.
Sources
Cynefin Framework - Snowden, D. J., & Boone, M. E. (2007). A Leader’s Framework for Decision Making. Harvard Business Review.
Complexity Theory - Stacey, R. D. (1996). Strategic Management and Organisational Dynamics. Financial Times/Prentice Hall.
Marketing Science - Sharp, B. (2010). How Brands Grow: What Marketers Don’t Know. Oxford University Press.
Ehrenberg-Bass Institute - Ehrenberg, A. S. C., Uncles, M. D., & Goodhardt, G. J. (2004). Understanding Brand Performance Measures: Using Dirichlet Benchmarks. Journal of Business Research.
The Fallacy of Predictability in Marketing - Taleb, N. N. (2007). The Black Swan: The Impact of the Highly Improbable. Random House. McKinsey & Company (2022). The State of AI in 2022 – and a Half Decade in Review.
Adaptive Strategy & Commercial Integration - Reeves, M., Love, C., & Tillmanns, P. (2012). Your Strategy Needs a Strategy. Harvard Business Review. Kotler, P., Kartajaya, H., & Setiawan, I. (2017). Marketing 4.0: Moving from Traditional to Digital. Wiley.
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