案例文章——RealPro客户福利计划:通过订阅服务重新点燃购物者忠诚度

Q3 Social Sciences
Arnd Huchzermeier, Jannik Wolters, M. Uphues
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引用次数: 0

摘要

在本案例研究中,学生们将基于数据的见解与战略考虑相结合,在德国杂货零售连锁店Real做出基本的商业决策。为了应对客户数量的减少和收入的减少,Real开发了RealPro客户福利计划,以实现快速转变。对于固定的年费,RealPro会员可以在各种食品类别的非机动商品上获得20%的实质性和永久性折扣。学生们采用数据分析方法从所提供的数据集中提取见解,其中包含RealPro实际市场测试的销售点信息。基于这些见解,必须就RealPro程序的推出和设计做出决定。我们提供Excel和R两种格式的数据分析解决方案,可分析7.5万笔客户交易。在案例扩展中,学生可以应用差分法和两种协变量平衡算法进行深入的统计分析。为此,我们提供了一个包含83000笔交易的额外的不平衡数据集,学生可以在该数据集上测试和分析倾向得分匹配和熵平衡模型。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Case Article—The RealPro Customer Benefits Program: Rekindling Shopper Loyalty Through a Subscription Service
In this case study, students combine data-based insights with strategic considerations to make fundamental business decisions at the German grocery retail chain Real. In response to dwindling numbers of customers and reduced revenues, Real developed the RealPro customer benefits program to achieve a quick turnaround. For a fixed annual fee, RealPro members receive substantial and permanent discounts of 20% on nonpromoted items from a broad range of food categories. Students employ data analytics methods to extract insights from the provided data set, which contains point-of-sale information from the actual market test of RealPro. Based on these insights, decisions concerning the rollout and design of the RealPro program must be made. We provide data analysis solutions in both Excel and R to analyze 75 thousand customer transactions. In the case extension, students can apply the difference-in-differences method and two covariate balancing algorithms for in-depth statistical analyses. For this purpose, we provide an additional unbalanced data set with 83 thousand transactions, on which the students can test and analyze propensity score matching and entropy balancing models.
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来源期刊
INFORMS Transactions on Education
INFORMS Transactions on Education Social Sciences-Education
CiteScore
1.70
自引率
0.00%
发文量
34
审稿时长
52 weeks
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