ARNAUD DE BRUYN, Ph.D.
Hello and welcome !
I am Professor of Marketing and Associate Dean for the Ph.D. Program at ESSEC Business School, near Paris, France. I am also Distinguished Visiting Research Scholar at the Institute for the Study of Business Markets (Penn State University), Founder of DECISIVE SYSTEM (a European fundraising analytics company), and Principal at DecisionPro inc. (a U.S.-based marketing analytics software company).
I’m passionate about marketing analytics, especially as it applies to fundraising analytics, marketing engineering, and artificial intelligence. I am a teacher, a researcher, a consultant, a business developer, and even a software architect, depending on the time of day (or night).
In terms of research and publications, our work has been published in Journal of Marketing Research, Marketing Science, Management Science, Information Systems Research, International Journal of Research in Marketing (best paper award, Jan-Benedict Steenkamp Award for Long-Term Impact, and Emerald citation excellence award), and a few others. I am a member of the editorial review board of the International Journal of Research in Marketing (IJRM) and the Journal of Interactive Marketing.
My teaching focuses on data-driven marketing decision-making, marketing analytics and marketing models. I have developed a MOOC on marketing analytics with Coursera, and have won the Marketing Beast Teacher Award at ESSEC.
As a personal note, I was born in Belgium in 1973, and my native language is French.
ENGINIUS
Enginius is an online marketing analytics platform designed to help instructors and students learn and experience segmentation, positioning, conjoint analysis, predictive modeling, optimal pricing, etc.
With Enginius, we have worked very hard to make the output clear, concise, and full of business insight. No statistical jargon or technical mumbo-jumbo. And if one part of the analysis is a bit more involved, all the required explanations are right there in the report.
The reports can be viewed in a browser, or generated in various formats such as PowerPoint presentations, Excel spreadsheets, Word or PDF documents, or text files ready to be downloaded.
Enginius is available on any device, at any time… PC, Mac, iPad, tablet, even on a smart phone if you want. There is no installation required, and the software is always up-to-date.
PRINCIPLES OF MARKETING ENGINEERING AND ANALYTICS
The 21st century business environment demands more analysis and rigor in marketing decision making. And the business press is abuzz with the wonders of analytics. Increasingly, marketing decision making is becoming like design engineering— putting together concepts, data, analyses, and simulations to learn about the marketplace (analytics) and to design effective marketing plans (engineering). While many view traditional marketing as art and some view it as science, the new marketing increasingly looks like engineering (that is, combining art and science to solve specific problems).
We offer an accessible overview of the most widely used marketing engineering and analytics concepts and tools and show how they drive the collection of the right data and information to perform the right analyses to make better marketing plans, better product designs, and better marketing decisions. We have designed this book primarily for the business school student or marketing manager, who, with minimal background and technical training, must understand and employ the basic tools and models associated with marketing engineering and analytics. The interested reader can go beyond the conceptual material in this book and learn how to apply these concepts using the software tools, cases and exercises available at www.DecisionPro.biz. That material, in concert with the descriptions here will both inform the reader and translate the concepts here into context-specific decisions and actions.
RESEARCH
- Ferecatu, Alina, Arnaud De Bruyn, and Prithwiraj Mukherjee (2024), “Silently Killing Your Panelists One Email at a Time: The True Cost of Email Solicitations,” Journal of the Academy of Marketing Science, 52, 1216-1239.
- Hada, Mahima, Arnaud De Bruyn, and Gary L. Lilien (2024), “Horizontal Referrals in B2B Markets,” Journal of Marketing Research, 61(1), 143-164.
- Colicev, Anatoli, and Arnaud De Bruyn (2023), “The Spillover Effects of Positive and Negative Buzz on Brand Attitudes,” European Journal of Marketing, 57(9), 2382-2406.
- De Bruyn, Arnaud, and Thomas Otter (2022), “Bayesian Consumer Profiling: How to Estimate Consumer Characteristics from Aggregate Data,” Journal of Marketing Research, 59(4), 755-774.
- Ferecatu, Alina, and Arnaud De Bruyn (2022), “Understanding Managers’ Trade-offs between Exploration and Exploitation,” Marketing Science, 41(1), 139-165.
- Mukherjee, Prithwiraj, Souvik Dutta, and Arnaud De Bruyn (2022), “Did Clickbait Crack the Code on Virality?” Journal of the Academy of Marketing Science, 50, 482-502.
- Sarkar, Mainak, and Arnaud De Bruyn (2021), “LSTM Response Models for Direct Marketing Analytics: Replacing Feature Engineering with Deep Learning,” Journal of Interactive Marketing, 53, 80-95.
- De Bruyn, Arnaud, Vijay Viswanathan, Yean Shan Beh, Jürgen Kai-Uwe Brock, and Florian von Wangenheim (2020), “Artificial Intelligence and Marketing: Pitfalls and Opportunities,” Journal of Interactive Marketing, 51, 91-105.
- De Bruyn, Arnaud, and Sonja Prokopec (2017), “Assimilation-Contrast Theory in Action: Operationalization and Managerial Impact in a Fundraising Context,” International Journal of Research in Marketing, 34(2), June, 367-381.
- Butori, Raphaëlle, and Arnaud De Bruyn (2013), “So You Want to Delight Your Customers: The Perils of Ignoring Heterogeneity in Customer Evaluations of Discretionary Preferential Treatments,” International Journal of Research in Marketing, 30(4), December, 358-367.
- De Bruyn, Arnaud, and Sonja Prokopec (2013), “Opening a Donor’s Wallet: The Influence of Appeal Scales on Likelihood and Magnitude of Donation,” Journal of Consumer Psychology, 23(4), October, 496-502.
- Kayande, Ujwal, Arnaud De Bruyn, Gary L. Lilien, Arvind Rangaswamy and Gerrit H. van Bruggen (2009), “How Incorporating Feedback Mechanisms in DSS Design Affects DSS Evaluation,” Information Systems Research, 20(4), December, 527-546.
- De Bruyn, Arnaud, Gary E. Bolton (2008), “Estimating the Influence of Fairness on Bargaining Behavior,” Management Science, 54(10), October, 1774-1791.
- De Bruyn, Arnaud, John C. Liechty, Eelko K.R.E. Huizingh and Gary L. Lilien (2008), “Offering Online Recommendations with Minimum Customer Input through Conjoint-Based Decision Aids,” Marketing Science, 27(3), May-June, 443-460.
- De Bruyn, Arnaud, Gary L. Lilien (2008), “A Multi-Stage Model of Word of Mouth through Viral Marketing,” International Journal of Research in Marketing, 25(3), September, 143-225.
- Liechty, John C., Duncan K.H. Fong, Eelko K.R.E. Huizingh and Arnaud De Bruyn (2008), “Hierarchical Bayesian Conjoint Models Incorporating Measurement Uncertainty,” Marketing Letters, 19(2), 141-155.
- Kamakura, Wagner A., Jose Afonso Mazzon and Arnaud De Bruyn (2006), “Modeling Voter Choice to Predict the Final Outcome of Two-Stage Elections,” International Journal of Forecasting, 22(4), 689-706.