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Artificial intelligence (AI) is rapidly transforming the playing field of marketing and market
research. Where strategy once revolved around experience, intuition, and manual research,
we now see models that recognize patterns, make predictions, and generate content. Generative AI swiftly develops variations of campaigns, analyzes consumer trends, and helps brands tailor products and communication more precisely to specific target audiences. What once seemed like a vision of the future has become an everyday reality. During our annual symposium, we dive into the facts behind the AI trend together with leading scientists and experts from practice.
Program
13:30-14:00 Registration
14:00-14:05 Opening remarks by Yvonne van Everdingen
14:05-14:35 Doug Guion
14:40-15:10 Bas Donkers
15:15-15:45 Jan Zwang
15:45-16:00 Break
16:05-16:35 Andrea Weihrauch
16:35-17:05 Jori van de Spijker
17:10-17:40 Vera Blazevic
17:45-17:50 Closing remarks Yvonne van Everdingen
From 17:50 Networking drinks
Jori van de Spijker (DVJ Insights)
How AI and human insight turn creativity into business growth
In this session, Jori van de Spijker shows how leading brands can use AI not just to work faster, but to better understand what makes advertising truly effective. Drawing on large-scale validation across advertising databases, he shares how new AI-driven measures of uniqueness and cognitive demand help explain why some campaigns break through and others do not. The talk makes the case that the real value of AI lies in uncovering things we could not measure before, and that its impact only becomes meaningful when combined with human judgment and action.
Jan Zwang (VodafoneZiggo)
AI from promise to delivering business value
In this presentation Jan Zwang will take you in the journey of VodafoneZiggo in use of AI in all aspects of the marketing&customer journey from concept testing to customer experience. And tools used from mass qual methods to a smart AI driven insight portal. What are the lessons learned and the expectations not fulfilled (yet).
Doug Guion (Yabble)
The Showroom No One Is Talking About: Reframing What AI Can Actually Do for Researchers
The trust deficit around AI in research is not a technology failure, it is a vocabulary problem. It is what happens when the entire category gets reduced to a conversation about large language models, as though the LLM were the only make and model in a very large showroom. Understanding that distinction is what makes everything that follows in this session believable. Reframing AI as an enabler for the frameworks researchers have always used, making what was previously impossible feel like a natural extension of work they already know how to do. Through examples from concept testing, package evaluation and audience modelling, this session explores that expanded frontier and makes a firm case that the barrier is no longer capability but the much more human skill of knowing which tool to pick up, and when.
Bas Donkers (Erasmus Universiteit Rotterdam)
Large Language Model Models for Marketing
The model behind an LLM is not only good for modeling language, but also for various other marketing phenomena. In this presentation, Bas will show how it can be effectively applied to recommendation systems and to attribution modeling and optimization.
Andrea Weihrauch (Universiteit van Amsterdam)
Increased Representation in Technology – Opportunity or Risk?
As AI becomes increasingly integrated into everyday interactions, many systems are designed to appear more human-like—through chatbots, avatars, and voice assistants. While this can improve usability and engagement, it also embeds specific human characteristics, including gender and ethnicity. Notably, many AI agents are designed as female and often reflect White-Caucasian features—for example, the original voice of Apple’s Siri was based on American Susan Bennett. Although humanizing AI is generally seen as beneficial (as long as it avoids the “uncanny valley”), we still know little about the implications of these demographic choices. How do they shape user perceptions and biases? And what risks do they pose in reinforcing stereotypes or excluding certain groups?
Vera Blazevic (Radboud Universiteit)
Promises and perils of human-AI collaboration in marketing & innovation
Generative artificial intelligence is reshaping the way we market, innovate, and imagine — accelerating marketing and innovation processes, breaking through the limits of human information processing, and unlocking creative possibilities through cognitive stimulation with easily accessible external knowledge. But every revolution carries a shadow. From AI systems that hallucinate facts with alarming confidence, to the quiet erosion of the human skills and social connections that make great teams great — the risks are real. And as AI supercharges personalised fraud, consumers and organisations alike find themselves more vulnerable than ever. In my presentation, I will shed light on both sides of this transformation to provide a balanced and realistic picture of human-AI collaboration.