دانلود رایگان مقاله ایجاد توازن بین حفظ حریم خصوصی مشتریان، اسرار، و نظارت

Abstract

As surveillance technology advances and becomes more data rich and less intrusive and costly, brands collect vast quantities of customer data in order to gain customer insights to remain competitive. Brands conduct customer surveillance often without considering the consequences on customer relationships. Because of customer surveillance activities, customers may also experience privacy intrusions and turn to customer secrecy strategies that hide or disguise their data. To reduce this reaction, we propose a set of surveillance prompts to structure market intelligence databases to increase the efficiency of, and thus reduce the quantity of, customer surveillance activities while increasing data integrity and the potential value of customer insights. By discussing the need for brands to collect business and market intelligence, as well as detailing five types of customer data resources, we lay the groundwork for selecting potential customer data resources that best fit a brand’s customer insight needs. We conclude with a discussion of two important considerations of a brand’s customer surveillance strategy.

6.2. Reduce customer secrecy strategies to improve market intelligence integrity

To reduce customer secrecy strategies, customers need to feel secure in disclosing personal data and realize the positive consequences of data sharing with certain brands. Thus, brands might switch from furtive customer surveillance to voluntary customer disclosure by demonstrating the value customers can gain from divulging certain data. This does not mean that brands should forego the collection of high-integrity data resulting from transactions with customers. Customers understand that this is a necessary element of business, and many appreciate databases that tally and report patronage points. It is the unobtrusive but perceptively intrusive surveillance that probably concerns most customers (e.g., using facial recognition to identify and track a shopper unknowingly). Furthermore, such technology is not 100% accurate and thus can lower the quality of business analytics. When customers willingly disclose in anticipation of tangible benefits (e.g., advanced information, discounts, improved convenience), data integrity is likely to be higher and the customer relationship maintained, if not enhanced.