Profile
Aurélie Lemmens is an Associate Professor of Marketing at the Rotterdam School of Management, Erasmus University (The Netherlands). She holds a Ph.D. degree from K.U. Leuven (Belgium) and a M.Sc. degree in management from Solvay Business School (Belgium). She previously held appointment at the Erasmus School of Economics in Rotterdam (The Netherlands), Tilburg University (The Netherlands), and was a visiting scholar at Harvard Business School (USA).
Aurélie Lemmens’s current research focuses on the development of predictive and prescriptive analytics to address key business decisions and on the fairness of the algorithms used to design and evaluate policies. She is particularly interested in the design of new methodologies that can guide organizations in their customer-centric decision making. A substantial part of her research has involved the use of machine learning, active learning, ensemble learning, meta learning and large-scale cluster and grid computing. Her publications on these topics have appeared in leading academic journals, such as Marketing Science, the Journal of Marketing Research and the International Journal of Research in Marketing.
She has been a recipient of the 2012 IJRM Best Paper Award and the ERIM Open Science Award 2021. She also received several best teaching awards (2017 and 2019) for her course on Conjoint Analysis. Finally, she was awarded several prestigious grants, including a Marie Curie from the European Research Council, a Veni and a Vidi grants from the Dutch Science Foundation, NWO. She also advises companies on their customer relationship management activities, in particular proactive churn management and personalized targeting optimization. At Erasmus, she is teaching Customer Analytics in Business Analytics Msc and Customer-Centric Marketing in the Marketing Management Msc.
For more information, please find my CV here or visit www.aurelielemmens.com.
Publications
Article (14)
Academic (14)
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Lemmens, A., & Gupta, S. (2020). Managing churn to maximize profits. Marketing Science. https://doi.org/10.2139/ssrn.2964906
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Ascarza, E., Neslin, S., Netzer, O., Anderson, Z., Fader, P., Gupta, S., Hardie, B., Lemmens, A., Libai, B., Neal, D., Provost, F., & Schrift, R. (2018). In pursuit of enhanced customer retention management. Customer Needs and Solutions, 5(1-2), 65-81. https://doi.org/10.1007/s40547-017-0080-0
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Glady, N., Lemmens, A., & Croux, C. (2015). Unveiling the relationship between the transaction timing, spending and dropout behavior of customers. International Journal of Research in Marketing, 32(1), 78-93. https://doi.org/10.1016/j.ijresmar.2014.09.005
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Verbeke, W., Bagozzi, RP., van den Berg, W., & Lemmens, A. (2013). Polymorphisms of the OXTR gene explain why sales professionals love to help customers. Frontiers in Behavioral Neuroscience, 7, 171. https://doi.org/10.3389/fnbeh.2013.00171
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Lemmens, A., Croux, C., & Stremersch, S. (2012). Dynamics in the international market segmentation of new product growth. International Journal of Research in Marketing, 29(1), 81-92. https://doi.org/10.1016/j.ijresmar.2011.06.003
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Bijmolt, THA., Leeflang, PSH., Block, F., Eisenbeiss, M., Hardie, BGS., Lemmens, A., & Saffert, P. (2010). Analytics for customer engagement. Journal of Service Research, 13(3), 341-356. https://doi.org/10.1177/1094670510375603
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Stremersch, S., & Lemmens, A. (2009). Sales Growth of New Pharmaceuticals Across the Globe: the Role of Regulatory Regimes. Marketing Science, 28(4), 690-708. https://doi.org/10.1287/mksc.1080.0440
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Lemmens, A., Croux, C., & Dekimpe, MG. (2008). Measuring and Testing Granger Causality over the Spectrum: An Application to European Production Expectation Surveys. International Journal of Forecasting, 24(3), 414-431. https://doi.org/10.1016/j.ijforecast.2008.03.004
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Lemmens, A., Croux, C., & Dekimpe, MG. (2007). Consumer Confidence in Europe: Unity or Diversity. International Journal of Research in Marketing, 24(2), 113-127. https://doi.org/10.1016/j.ijresmar.2006.10.006
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Gelper, S., Lemmens, A., & Croux, C. (2007). Consumer Sentiment and Consumer Spending: Decomposing the Granger Causal Relationship in the Time Domain. Applied Economics, 39(1), 1-11. https://doi.org/10.1080/00036840500427791
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Croux, C., Joossens, K., & Lemmens, A. (2007). Trimmed Bagging. Computational Statistics & Data Analysis, 52(1), 362-368. https://doi.org/10.1016/j.csda.2007.06.012
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Lemmens, A., & Croux, C. (2006). Bagging and Boosting Classification Trees to Predict Churn. Journal of Marketing Research, 43(2), 276-286. https://doi.org/10.1509/jmkr.43.2.276
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Lemmens, A., Croux, C., & Dekimpe, MG. (2005). On the Predictive Content of Production Surveys: a Pan-European Study. International Journal of Forecasting, 21(2), 363-375. https://doi.org/10.1016/j.ijforecast.2004.10.004
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Pieters, C., Pieters, R., & Lemmens, A. (Accepted/In press). Six Methods for Latent Moderation Analysis in Marketing Research: A Comparison and Guidelines. Journal of Marketing Research. https://doi.org/10.1177/00222437221077266
Conference proceeding (2)
Academic (2)
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Puha, Z., Kaptein, M., & Lemmens, A. (2021). Batch Mode Active Learning for Individual Treatment Effect Estimation. In G. Di Fatta, V. Sheng, A. Cuzzocrea, C. Zaniolo, & X. Wu (Eds.), Proceedings - 20th IEEE International Conference on Data Mining Workshops, ICDMW 2020 (pp. 859-866). [9346484] IEEE Computer Society. IEEE International Conference on Data Mining Workshops, ICDMW Vol. 2020-November https://doi.org/10.1109/ICDMW51313.2020.00123
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Croux, C., Joossens, K., & Lemmens, A. (2004). Bagging a stacked classifier. In Proceedings in Computational Statistics (pp. 839-855)
Working paper (2)
Academic (2)
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Lemmens, A., & Gupta, S. (2019). Managing churn to maximize profits. Harvard Business School. http://hdl.handle.net/1765/121652
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Pieters, C., & Lemmens, A. (2015). Acquiring customers via word-of-mouth referrals. Marketing Science Institute.
Courses
Customer Analytics
- Study year: 2022/2023, 2021/2022
- Code: BM21BAM
- Level: Master
Customer Centricity
- Study year: 2022/2023, 2021/2022, 2020/2021, 2019/2020
- Code: BMME144
- Level: Master, Master, Master, Master
BAM Master Thesis & Internship
- Study year: 2022/2023, 2021/2022
- Code: BMMTIBAM
- Level: Master
Past courses
BAM Master Thesis & Internship
- Study year: 2021/2022, 2020/2021
- Code: BMMTBAM
- ECTS: 16 Level: Master
Customer Analytics - Extra assignment
- Study year: 2021/2022
- Code: BM21BAME
- Level: Master
Customer Analytics
- Study year: 2020/2021
- Code: BM11BAM
- ECTS: 6 Level: Master
Advanced Marketing Decision Models
- Study year: 2019/2020
- Code: BERMASC044
- ECTS: 4 Level: Master
Featured in the media
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The right way to manage customer churn for maximum profit
An article co-written by Aurelie Lemmens of RSM that describes how companies can more than double profits from customer retention, without expending any additional money or effort.
Monday, 13 July 2020 -
The Right Way to Manage Churn for Maximum Profit
An article discussing research which was co-written by Aurelie Lemmens of RSM, the paper describes how companies can more than double profits from customer retention, without expending any additional money or effort. …
Monday, 6 July 2020
Featured on RSM Discovery
Interview with Dr. Aurélie Lemmens on Customer Analytics
If you target the right customers with your retention efforts, you could increase your profits by 4 per cent.
