The Journal of the Nuremberg Institute for Market Decisions

NIM Marketing Intelligence Review

Our latest issue

AI in Market Research

 

We examine the current opportunities and challenges of AI in market research and discuss where generative AI creates real value — and where its use can cost time, quality or credibility.

Our guest editor, Michael Haenlein, Professor of Marketing at ESCP Business School and Chair in Responsible Research in Marketing at the University of Liverpool Management School, joins leading scholars in calling for close collaboration between humans and AI — combining the speed and scale of artificial...

AI Agents AI Tools Silicon Samples Market Research Synthetic Respondents
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Guest Editors

  • Michael Haenlein, Professor of Marketing, Chair in Responsible Research in Marketing, ESCP Business School, University of Liverpool Management School

Article overview

To Boldly Go Where No Research Has Gone Before: AI in Marketing Intelligence

AI has already reshaped market research and will significantly expand its impact in the near future.

A New Frontier of Understanding: Where Generative AI Adds Real Value in Consumer Research

Used well, GenAI frees market research teams for higher-value work; used poorly, it wastes time and erodes credibility.

Your Next Respondent Might Be an LLM: Guidelines for Using Silicon Samples in Marketing Research

By simulating human responses, silicon samples can support the entire marketing research process.

New Tools, New Roles: A Manager’s Guide to Harnessing Generative AI for Marketing Insight

Without rigor around accuracy, validity and reproducibility, GenAI is more likely to mislead than to enlighten.

Human-AI Hybrids: The New Power in Marketing Research

In marketing research, AI–human hybrids outperform either side working alone.

Smarter Idea Selection: Turning Idea Overload into Innovation Advantage

AI-assisted idea screening offers a transparent, data-driven way to manage idea overload without losing strategic control.

Leaving Insight to Digital Twins? Promise, Progress and Limits of Synthetic Respondents

Today, synthetic survey data seems most suitable for early-stage concept testing or lower-stakes applications.

Between Surveys and Depth: How AI Is Rewiring Qualitative Research

Interview with David Ranftler and Paul Wesendonk, cofounders of xelper

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Dr. Christine Kittinger-Rosanelli

Managing Editor, NIM Marketing Intelligence Review

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