Big Data Customer Knowledge Management

ABSTRACT Knowledge management (KM) and customer relationship management (CRM) are dominant strategies for value creation for businesses in the new economy. Customer knowledge management (CKM) results in the merging of KM and CRM, where the knowledge management process is applied to customer knowledge, and customer knowledge is applied to customer relationship management operations. With the emergence of big data as the latest phase in the evolution of technology in business, CKM strategies need to be adjusted to meet the new challenges, changing from an internal organizational focus to new external channels such as social media and machine communications. This paper explores the concept of big data customer knowledge management. It presents an architecture that integrates CRM operations and KM processes with big data technologies that include NoSQL databases, Hadoop Distributed File System, MapReduce, and platforms for social media and machine-to-machine communications. Keywords: big data, knowledge management, customer relationship management, customer knowledge management, social media, M2M. INTRODUCTION Customer relationship management (CRM) and knowledge management (KM) are value creation strategies that exploit the relationship and knowledge assets in order to maximize opportunities and achieve business goals. CRM helps companies to acquire new customers, retain existing customers, and increase profitability and market share. KM concerns with the creation, sharing, maintaining, and utilization of knowledge within an organization. It has evolved from the internal focus of product and operational excellence to an external focus of enhancing business processes across the extended enterprise. The merging of the two disciplines of KM and CRM has become an area of interest in business and academia. Gibbert, Leibold, and Probst (2002) described customer knowledge management (CKM) as the management of knowledge from customers, empowering customers as knowledge partners. Customer knowledge management also refers to KM models in which customer knowledge is applied to support CRM processes (Bueren, Schierholz, Kolbe, & Brenner, 2004; Gebert , Geib, Kolbe, & Riempp, 2002; Gebert, Geib, Kolbe, & Brenner, 2003). In this paper, the extension of the CKM model in the era of big data is explored. Minelli Chambers, and Dhiraj (2013) described the emergence of the big data era as resulting from three dominant trends: the exponential growth of processing power, the accessibility of data with high volume, velocity and variety, and the convergence of traditional data management technologies, open-sourced technologies and commodity hardware. Big data are datasets whose requirements for storage, processing and analytics are beyond the prevalent technology capacity of the time. Contributing to the characteristics of big data are high volume, high velocity and high variety. With the proliferation of the Internet, social media and mobile computing, the impact of big data is felt in many sectors and industries. The capability of business to exploit big data to gain actionable insights is becoming a critical strategy to create competitive advantages. Customer knowledge management takes on new dimensions in the era of big data. Customer knowledge is acquired from sources beyond traditional CRM transactions to include big data sources such as call centers, Web logs, emails, surveys, social media and machine-to-machine communications. Knowledge creation, dissemination and sharing within an organization are extended to include other external communication media. New strategies in CRM emerge to leverage big data channels. They include listening and engaging through social media, interactions via machine-to-machine communications, in addition to high volume and high variety transactions through call centers and the Web. This paper combines the perspectives of knowledge management and customer relationship management in the era of big data. …