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The upside of data privacy - delighting customers by implementing data privacy measures

机译:数据隐私的优势-通过实施数据隐私措施来取悦客户

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The targeted analysis of customer data becomes increasingly important for data-driven business models. At the same time, the customers' concerns regarding data privacy have to be addressed properly. Existing research mostly describes data privacy as a necessary evil for compliance and risk management and does not propose specific data privacy measures which address the customers' concerns. We therefore aim to shed light on the upside of data privacy. In this paper, we derive specific measures to deal with customers' data privacy concerns based on academic literature, legislative texts, corporate privacy statements, and expert interviews. Next, we leverage the Kano model and data from two internet-based surveys to analyze the measures' evaluation by customers. From a customer perspective, the implementation of the majority of measures is obligatory as those measures are considered as basic needs of must-be quality. However, delighting measures of attractive quality do exist and have the potential to create a competitive advantage. In this, we find some variation across different industries suggesting that corporations aiming to improve customer satisfaction by superior privacy protection should elicit the demands of their specific target customers.
机译:客户数据的目标分析对于数据驱动的业务模型变得越来越重要。同时,必须正确解决客户对数据隐私的担忧。现有研究大多将数据隐私描述为合规性和风险管理的必要弊端,并且未提出解决客户关注问题的特定数据隐私措施。因此,我们旨在揭示数据隐私的优势。在本文中,我们根据学术文献,立法文本,公司隐私声明和专家访谈得出了解决客户数据隐私问题的具体措施。接下来,我们利用Kano模型和两次基于互联网的调查数据来分析客户对这些措施的评估。从客户的角度来看,大多数措施是强制性的,因为这些措施被视为必不可少的质量的基本需求。但是,确实存在具有吸引力质量的令人愉悦的措施,并且有可能创造竞争优势。在这方面,我们发现不同行业之间存在一些差异,这表明旨在通过出色的隐私保护来提高客户满意度的公司应该引起其特定目标客户的需求。

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