Location:   Research Institutes > Customer Information Management

Customer Information Management

Today, marketing managers have realized that firms' assets are their customers and their marketing focus has been shifted from being "marketer-centric" to "customer-centric."  The traditional process of mass marketing is being challenged by the new approach of interactive marketing, otherwise known as one-to-one marketing. Recognizing the increasing importance of customer information for moving towards a more customer-centric orientation, companies from all types of industries, ranging from manufacturing to information, are exploring customer information management and decision support systems as promising means of differentiation, competition, and revenue growth opportunities. Empowered by software and internet technology, firms have developed innovative tools and methods to uncover heterogeneity in customer preferences (e.g.  taste, cost to serve, and sensitivity to firm's decision variables) and adopt customized interventions (e.g. promotion, advertising, and product design) that are relevant to the status and preference of each individual customer.

For example, Amazon.com adopted learning tools to predict consumer demand and (automated) recommendation systems to improve customer shopping experience and cross-sell additional products. Many credit card companies use real-time data mining to screen credit applicants, customize their offers in credit terms, and predict credit fraud. Recently, an increasing number of similar technologies under the name of customer relationship management (CRM) software has made significant inroads at commercial firms which grant these companies the ability to dig out detailed information about each individual customer from vast databases, enabling more customized and proactive decisions for the purpose of acquiring, nurturing, and retaining customers and while maximizing customer lifetime contribution to the company profit.

The core idea behind customer-centric marketing implies the following two basic steps: (1) the firm learns customer preferences from past interactions with the customer; (2) firm marketing decisions are adapted according to the most up-to-date knowledge. Customer-centric (as opposed to promotional and product-focused) communications increase customer experience, which results in better marketing effectiveness and lower marketing efficiency. Companies are actively looking for new data mining tools which will allow them to learn about each individual customer and seek analytical marketing solutions; these tools enable highly customized intervention decisions. 

Mission

Customer- and technology-driven e-commerce initiatives are likely to dominate business strategies in the future. Rapid growth in the demand and supply of sophisticated data-mining and analytical decision tools requires research to understand the value of learning, as well as the manner in which learning interacts with firms' day-to-day marketing strategies. The goal of this center is to

  • encourage multidisciplinary research that explores the interface among marketing, operations management, and information systems,
  • investigate how companies can better use customer information to learn about customer preferences in a real-time fashion, enabling optimal interaction decisions to maximize the long-term profit of each customer,
  • provide a forum for faculty, Ph.D. students, visiting scholars, consulting associates, practitioners, and supporters to make important contributions on a wide range of topics related to this new trend of customer information management.

Research Fellows

Chen Yuxin,
Polk Bros. Professor of Retailing
Professor of Marketing
Kellogg School of Management, Northwestern University
Visiting Professor of Marketing
Cheung Kong Graduate School of Business

Professor Guo Liang,
Visiting Associate Professor of Marketing
Cheung Kong Graduate School of Business
Associate Professor of Marketing
Hong Kong University of Science and Technology

Professor Jing Bing,
Assistant Professor of Marketing
Cheung Kong Graduate School of Business

Professor Zhao Hao,
Associate Professor of Marketing
Cheung Kong Graduate School of Business

Research

In response to the increasing demand from industry for sophisticated data mining and decision support systems, we seek to develop research methods that dig out meaningful customer information from massive databases, supporting everyday marketing decision making. We investigate how optimization tools can be applied to customer information management and support marketing decisions, allowing companies to more effectively serve customers, increase the efficiency of marketing communications, and translate better customer relationships into long-term profitability.

By bringing together researchers from disciplines such as marketing, operations research, information systems, economics, and psychology, the center seeks to advance a holistic understanding of this trend and its evolution. Research issues of interest to the center will include:

  • Firm learning and analytical decision making
  • Customer-centric marketing
  • Proactive marketing and customer lifetime value analysis
  • One-on-one interactive and dynamic marketing intervention
  • Customer relationship management
  • Customer information management
  • Online customer tracking and web analytics

Working Paper Series

  • "Technology Innovation and Implications on Customer Relationship Management," (invited commentary paper), Baohong Sun, 2006, Marketing Science, 25, 594-598.
  • "Dynamic Structural Consumer Models and Current Marketing Issues," (invited commentary paper), Baohong Sun, 2006, Marketing Science, 25, 625-629.
  •  "'Adaptive' Learning and 'Proactive' Customer Relationship Management," Baohong Sun, Shibo Li, and Catherine Zhou, 2006, Journal of Interactive Marketing, 82-96.
  • Sun, Baohong and Shibo Li, "Learning and Acting Upon Customer Information - With an Empirical Application to the Service Allocations with Off-Shore Centers" (TSB working paper 2006-E48) 
  • Henry Cao and Baohong Sun, "Value of Learning and Acting Upon Customer Information."
  • Shibo Li, Baohong Sun, and Alan Montgomery, "Introducing What Financial Product to Which Customer at What Time -An Empirical Analysis of Customized and Dynamic Cross-selling Campaigns." (TSB working paper 2006-E66).
  • Yacheng Sun, Baohong Sun, and Shibo Li, "When is the Juice Worth the Squeeze? – An Empirical Study of Optimal Structuring of Win-back Strategy in the Presence of Consumer Dynamics."

Activities

June 29-30, 2009 Cheung Kong GSB Marketing Research Forum
MBA course: Optimization in Interactive Marketing

We designed this course to meet the increasing demands from the industry and recruiters for the application of quantitative and analytical skills to support sophisticated marketing decision making. Students learn how to construct state-of-the-art marketing strategies and what analytical techniques can be used to support these decisions. This course complements the courses on statistics, data mining, and optimization by demonstrating the applications of these analytical tools.

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