Abstract
This chapter proposes a conceptual model, the 121 e-Agent Framework, for Customer Relationship Management (CRM) in academic libraries. Linked data and Semantic Web are the core components of this model. The implementation of the Framework will enable the participating U.S. academic libraries to reach out to their user communities through systematic customer group identification, differentiation, and interaction. The main contributions of the chapter are 1) applying Semantic Web technologies for CRM in academic libraries using the 121 e-Agent Framework, 2) defining the relevance challenges of CRM for academic libraries, 3) adding trust management to the linked data layer with a touch of tagging, categorizing, query log analysis, and social ranking as part of the underlying structure for distributed customer data filtering on the Web in CRM applications, and 4) making the approach extensible to address the challenges of CRM in other fields.
TopIntroduction
Customer relationship management (CRM) is defined as “the business processes and supporting technologies that support the key activities of targeting, acquiring, retaining, understanding and collaborating with customers” (Band, 2013). CRM is also regarded as a business model that uses proven methodologies and e-business technologies to help companies identify, select, acquire, develop, and retain profitable customers, building the lasting relationships that are key to long-term financial success. Simply put, “It is a strategy used to learn more about customers' needs and behaviors in order to develop stronger relationships with them. Good customer relationships are at the heart of business success” (Wailgum, 2014). When applied to the library profession, it is about developing a strategy or model that uses a combination of methodologies, computer programs, and Internet capabilities to build good relationships with patrons.
In the past CRM has received little attention in the library community. While librarians are more focused on collection-related issues of the digital age, the business world is obsessed with customers and a new era called the age of the customer (Forrester Research, Inc., 2014). Eventually, “Libraries are slowly becoming interested in CRM, as they look for ways to market their services and attract ‘customers’” (Arnold, 2013). The benefits of CRM for academic libraries include the ease of sharing information, ability of raising funds, reaching new users via social media, and obtaining details on usage (Cambellini, 2012). Like business organizations, libraries also need customer loyalty and support.
The library CRM strategy involves identifying and retaining patrons, including supporters from a library learning community, knowing their backgrounds, best matching their research expertise, interests and needs with relevant resources and services, measuring user satisfaction, developing long-term friends of the library, and more. The adoption of best practice and deployment of appropriate technologies such as the 121 e-Agent Framework is the key component in successful CRM implementation. In the last decade, academic libraries began to view their patrons as customers (Wilson, 2008). Therefore, the terms “patrons” and “customers” are used interchangeably in this paper as they both refer to the library clientele.
Key Terms in this Chapter
Semantic Web: W3C’s vision for Web of linked data empowered by technologies such as RDF, SPARQL, OWL, and SKOS
Trust Management: It is also known as trustworthiness estimation, and high quality and reliable customer engagement management. It is about developing strategies for establishing trust through underlying information infrastructure for customer information filtering; and developing systems that can assist collection managers in i) assessing level of trust they should place on customer engagement, and ii) answering how-well like questions in collection management with degree of confidence.
121 E-Agent Framework: It is also known as One-to-one Customer Engagement Agent Framework. It’s a proposed conceptual model for customer relationship management. Specifically, it is a tracking system to manage library collections and customer information, predict customers’ wants and needs, match them to the collections automatically, recommend to customers and library collection managers as appropriate, and provide decision support for library collection managers in the collection management and customer engagement process.
Collection Managers: Librarians who build and manage library resources tailored to the intellectual needs of a given library community.
CRM: It is also known as customer relationship management. It is about developing a strategy or model that uses a combination of methodologies, computer programs, and Internet capabilities to build good relationships with library users.
Relevance Challenges: Challenges of remaining relevant to library users, particularly i) meeting the users’ information needs in the fabric of the user experience, for example, teaching and learning activities, scientific research, and scholarly communications; ii) promoting the most sophisticated intellectual inquiry, advanced thinking, the teaching and learning of the 21 st -century skills, knowledge advancement, research output, and decision making; and iii) linking of library resources, services, expertise, tools and infrastructure with research, teaching and learning objectives, processes, and outcome measures.
Academic Libraries: College and research libraries which are affiliated with institutions of higher education (e.g. colleges and universities); providing resources, services, expertise, tools, and infrastructure to engage, educate and empower library users; and supporting the teaching, learning and research mission of the institutions.