Irina Pessin

Abstract Generative AI is eroding the visibility that marketing measurement has depended on for two decades. The behavioral signals underpinning attribution were already under pressure.  AI adds to that pressure by influencing decisions earlier in the journey, often without leaving a trace that conventional tools can capture. At the same time, brand visibility within AI […]

Introduction AI models hold tremendous potential to speed up and improve a variety of processes. Marketing is no exception, and AI tools are being rapidly adopted across a wide range of functions including analytics and decision support, whether to support human decision makers or automate processes such as AI-driven programmatic ad serving and targeting. As

Introduction Brand remains one of the most influential yet least rigorously measured drivers of enterprise value. Its effects build over time, influencing demand, pricing power, and customer loyalty well beyond standard reporting cycles. By contrast, much of today’s measurement infrastructure, particularly Marketing Mix Modeling (MMM), has historically focused on short-term, in-period responses to media and

Introduction: Economic Value, Incrementality and Returns Marketers, agencies and analytics companies dedicate significant effort to understanding and maximizing returns from marketing investments. All approaches to evaluating impact of marketing share a similar structure whether based on Marketing Mix Modeling (MMM), Multi-Touch Attribution (MTA), Experiments or other approaches: (Outcome from Marketing × Economic Value of Outcome)