Brié, BjarneDistelmans, TinekeStouthuysen, KristofVerdonck, TimGrumiau, ChristopherThoppan Mohanchandralal, Sudaman2023-03-032023-03-032022http://hdl.handle.net/20.500.12127/7192This case is suitable for courses at the graduate and executive levels, at the intersection of strategic (management) accounting, data science, and machine learning. Because the problem in the case study is closely related to sales and marketing, the case can also be used for courses in these subject areas. If students have some programming experience, it can enhance the case discussion, although it is not required. This case helps participants become more familiar with the application of data science and machine learning to address real-word business problems. Although the case focuses specifically on an example from the insurance industry, it can be relevant for anyone who wants an enhanced understanding of how a business can move toward a more data-driven decision-making process. Specifically, after completion of this case, students will be able to o understand how to handle several data sets from scratch, using a general workflow; o discuss the challenges of working with raw data; o gain preliminary insights into structured data by making use of exploratory data analysis; o work with unsupervised learning techniques to cluster customers into segments; o understand how to train, use, and interpret supervised learning algorithms in a binary classification problem; o use the insights derived from machine learning analyses to formulate concrete solutions to a business problem; and o understand how machine learning can add value to the decision-making process.In October 2019, the regional chief data and analytics officer at Allianz AG, Belgium, attended a two-hour strategy meeting with the Allianz Benelux chief executive officer, who had expressed concerns about the company’s digitalization strategy. A few days earlier, the marketing department had found that online sales channel results had fallen unexpectedly. The chief executive officer was worried that the company could lose market share if it did not react accordingly, which would damage the company’s competitive position in the market. Therefore, the regional chief data and analytics officer was asked to gather a team to investigate why online sales were low and to design an effective customer acquisition strategy. In addition to his data office staff, the regional chief data and analytics officer asked for the business transformation unit to provide assistance. He had to consider how best to approach this challenging task.enMachine LearningCustomer Acquisition StrategyInsuranceData ScienceW27305286361249027119751220053