Profile for Marco Vriens

Marco Vriens profile photo

Specialty area(s)

Analytics, Branding, Neuro Science, Machine Learning

Brief biography

Dr. Vriens has worked for Microsoft, and GE Healthcare and was the Global Chief Research Officer at Ipsos prior to joining UWL. He teaches Marketing Research & Marketing Analytics. He is the editor of Handbook of Marketing Research (Sage, 2006), and the author/co-author of The Insights Advantage: knowing how to win (2012) and From Data to Decision: Handbook for the modern business analyst (2018, Cognella Academic Publishing). He has published in many journals on a variety of topics including Branding, Analytics & Eye tracking/consumer decision making.

Research and publishing

Vriens, M., Chen, S. and Schomaker, J. (2019). The evaluation of a brand association density metric. Journal of Product and Brand Management, 28, 1, 104-116.

Vriens, M. Chen, S. and Vidden, C. (2018). Mapping brand similarities: Comparing consumer online comments versus survey data. International Journal of Market Research, 1-10.

Chen, S., Vidden, C., Nelson, N., and Vriens, M. (2018). Topic modeling for open-ended survey responses. Applied Marketing Analytics, Vol. 4, No. 1, pp. 53-62.

Vriens, M. and A. Martins Alves (2017). Modeling the implicit brand: Capturing the hidden drivers. Journal of Product and Brand Management, Vol 26, No. 6, pp. 600-615.

Vriens, M., Martins Alves, A. and Chen, S. (2017). Brand segmentation using implicit measures. Applied Marketing Analytics, 3, 2, 172-182.

Vriens, M., Vidden, C., Chen, S., and Kaulartz, S. (2017). Assessing the Impact of a Brand Crisis using Big Data: The case of the VW Diesel Emission Crisis. DMA Annual Analytics Journal, 107-118.

Vidden, C., M. Vriens, S. Chen (2016). Comparing Clustering Methods for Market Segmentation:
A simulation study. Applied Marketing Analytics, 2, 3, 225-238.

Vriens, M. and A. Martins Alves (2015), “Integrated Competition and Customer Analysis: Managing market share efficiently”, Applied Marketing Analytics, Vol. 1, No. 4, pp. 350-362. (link: http://www.henrystewartpublications.com/ama/).

Vriens, M. and D. Rademaker (2015), To Be Determined (What executives need to know about advanced analytics, part 2), Marketing Insights magazine, October, 16-21.

Vriens, M. and P. Kidd (2014), “The Big Data Shift: What every marketer needs to know about advanced analytics”, Marketing Insights magazine, Fall.

Vriens, M. and J. Brazell (2013), “Integrated Analytics for Better Decisions”, Marketing Insights magazine, Fall, 32-38.

Vriens, M. and P. Kidd (2013), “Using Smart Analytics to Re-charge your Tracking Studies”, Quirks Magazine, May, 22-25.

Vriens, M. (2013), “The Cure for Infophobia: Why Companies Avoid Using Data for Decision-Making”, Quirks Magazine, March, 62-67.

Vriens, M. and R. Verhulst (2008), “Unleashing Hidden Insights”, Marketing Research Magazine, Winter 12-17.

Hamilton, J., M., Vriens, M. Tramp (2007), “Building a Research Community”, Marketing Research Magazine, Fall, 16-22.

Vriens, M. (2003), “Strategic Marketing Research”, Marketing Research Magazine. Winter, pp. 20-25.

Vriens, M. and C. Frazier (2003), “The Hard Impact of the Soft Touch: How To Include Brand Positioning Attributes in Conjoint Analysis”, Marketing Research Magazine, Summer, 22-27.

Vriens, M., M. Grigsby, and P.H. Franses (2002), “Time Series Models for Advertising Tracking Data”, Canadian Journal of Marketing Research, 20, 2, 62-71.

Vriens, M. and E. Melton (2002), “Managing Missing Data: Improving Data Quality with Multiple Imputation”, Marketing Research Magazine, Fall, 12-17.

Vriens, M. and M. Grigsby (2001), “Building Profitable Online Customer-Brand Relationships”, Marketing Management, December, 34-39.

Vriens, M., M. Wedel, and Z. Sandor (2001), “Split-Questionnaire Designs: A New Tool for Survey Design and Panel Management”, Marketing Research, Summer, 14-19.

Vriens, M. and F. ter Hofstede (2000), “Linking Attributes, Benefits, and Values: A Powerful Approach to Market Segmentation, Brand Positioning and Advertising Strategy Development”, Marketing Research Magazine, Fall, 3-8.

Oppewal, H. and M. Vriens (2000), “Measuring Perceived Service Quality Using Integrated Conjoint Experiments”, International Journal of Bank Marketing, Vol. 18, No. 4, pp. 154-169.

Haaijer, R., M. Wedel, M. Vriens, and T. Wansbeek (1998), “Utility Covariances and Context Effects in Conjoint MNP Models”, Marketing Science, Vol. 17, No. 3, pp. 236-252.

Vriens, M., H. Oppewal and M. Wedel (1998), “Ratings-Based versus Choice-Based Latent Class Conjoint Models: An Empirical Comparison”, Journal of the Market Research Society, July, Vol. 40, No. 3, pp. 237-248.

Vriens, M., Loosschilder, E. Rosbergen and D.R. Wittink (1998), “Verbal versus Realistic Pictorial Representations in Conjoint Analysis with Design Attributes”, Journal of Product Innovation Management, Vol. 15, No. 5, pp. 455-467.

Vriens, M., J.R. Bult, J.C. Hoekstra and H. Van der Scheer (1998), “Conjoint Experiments for Direct Mail Optimization”, European Journal of Marketing, Vol. 32, No. 3-4, pp. 323-339.

Wedel, M., M. Vriens, T. Bijmolt, W. Krijnen and P.S.H. Leeflang (1998), “Assessing the Effects of Abstract Attributes and Brand Familiarity in Conjoint Choice Experiments”, International Journal of Research in Marketing, Vol.15, pp. 71-78.

Vriens, M., M. Wedel and T. Wilms (1996), “Metric Conjoint Segmentation Methods: A Monte Carlo Comparison”, Journal of Marketing Research, Vol. 33, no. 1 (February), pp. 73-85.

Loosschilder, G., E. Rosbergen, M. Vriens and D.R. Wittink (1995), “Pictorial Stimuli in Conjoint Analysis - to Support Product Styling Decisions”, Journal of the Market Research Society, 37, 1, 17-34.

Vriens, M. (1994), “Solving Marketing Problems with Conjoint Analysis”, Journal of Marketing Management, 10, 37-55.

Wittink, D.R., M. Vriens and W. Burhenne (1994), “Commercial Use of Conjoint Analysis in Europe: Results and Critical Reflections”, International Journal of Research in Marketing, 11, 1, 41-52.

DeSarbo, W.S., M. Wedel, M. Vriens and V. Ramaswamy (1992), “Latent Class Metric Conjoint Analysis”, Marketing Letters, 3, 3, 273-288.

Muffels, R. and M. Vriens (1991), “Labor-Market Behavior of Long-Term Unemployed: A Multidisciplinary Approach”, Journal of Socio-Economics, 325-345.

Moed, H.F. and M. Vriens (1989), “Possible Inaccuracies Occurring in Citation Analysis”, Journal of Information Science, 15, 94-107.

Giesen C., A. Maas and M. Vriens (1989), “Stress among Farm Women: A Structural Model Approach”, Behavioral Science, pages 53-62.

 

Kudos

published

Marco Vriens, Marketing and Chad Vidden, Mathematics & Statistics, co-authored the article "What I see is what I want: Top down attention biasing choice behavior" in Journal of Business Research published on Sept. 9, 2019 by Elsevier.

Submitted on: Jan. 22

published

Marco Vriens, Marketing and Chad Vidden, Mathematics & Statistics, co-authored the article "The Linux Compete strategy: An analytics case study" in the journal, Applied Marketing Analytics, Vol. 5 Number 2, Pages 129-136 published on Sept. 1, 2019 by Henry Steward Publications.

Submitted on: Jan. 22

published

Marco Vriens, Marketing, and Chad Vidden, Mathematics & Statistics, co-authored the article "What I See is what I want: Top Down Attentional Biasing Choice Behavior" in Journal of Business Research published on Sept. 2, 2019 by Elsevier Publishing. When making a purchasing decision, people typically scan the available options before deciding. Previous studies have shown that bottom-up stimulus-driven factors can influence choice behavior through their effect on attention, but studies that investigate the effect of top-down attention are scarce. Here, we investigated the role of top-down attention in a choice task using fixation behavior as a proxy of attention. On each trial, participants chose a preferred food item among two similarly valued options. Attention was manipulated using directional, and neutral cues. Although the cues were task-irrelevant, participants viewed cued items longer than non-cued ones. This attentional effect also translated into a choice effect: Participants were faster and more likely to choose a cued versus non-cued item. In conclusion, task-irrelevant cues effectively impacted top-down attention and choice behavior as a result, suggesting that cues can be used to guide attention to consumer products and affect purchasing decisions.

Submitted on: Sept. 3, 2019