Does (customer data) size matter? Generating valuable customer insights with less customer relationship risk

Abstract

Customer surveillance is a pervasive marketing practice that involves the collection, usage, and storage of customers' data from transactions, loyalty programs, and social media. Customer data are valuable to firms in gaining or maintaining an edge over competitors by developing superior customer insights that may assist product or service innovations. However, customer surveillance practices also risk customer relationships by potentially activating privacy and data security concerns. This article explores customer insight strategies that focus customer surveillance by assessing the insight value of data sources to avoid unnecessary data collection and capture. Three prediction experiments show that three distinct data source attributes, namely data quantity, data detail, and data content, are diagnostic of the prediction accuracy of customer psychographic characteristics and behavioral intentions. By demonstrating that customer insights are more (or less) valuable when derived from different data sources, this article shows that “more” data is not necessarily better. We advocate a smarter approach to customer surveillance practices that are selective in choosing to capture customer data that can yield more accurate customer insights while reducing the risk of jeopardizing customer relationships.