"This book provides an overview of the field of the Semantic Web, social Web and CRM by uniting various research studies from different subfields, exploring the opportunities and challenges confronting organizations using Web 2.0 and 3.0"--Provided by publisher.

"This book offers case studies, methodologies, frameworks and architectures, and generally the cutting edge in research within the field of customer relationship management"--Provided by publisher.

In today’s global economy, social media and technological advances have changed the way businesses interact with their clientele. With new forms of communication and IT practices, companies seek innovative practices for maintaining their consumer loyalty. Customer Relationship Management Strategies in the Digital Era blends the literature from the fields of marketing and information technology in an effort to examine the effect that technological advances have on the interaction between companies and their customers Through chapters and case studies, this publication discusses the importance of achieving competitive advantage through implementing relationship marketing practices and becoming consumer-centric. This publication is an essential reference source for researchers, professionals, managers, and upper level students interested in understanding customer loyalty in a technology-focused society.

Social media has received considerable attention, and many potential benefits, as well as concerns, are now being discussed. This book explores how social media can successfully support business processes in marketing, sales and service in the context of customer relationship management (CRM). It presents the fundamentals of Social CRM and shows how small and large companies alike have implemented it. In turn, the book presents analytic and operational software tools that offer features for enhancing and streamlining interactions with customers. The book concludes with an overview of essential design areas that businesses need to bear in mind when introducing social media into their CRM strategies. In this regard, it also points out key success factors, limitations, and data protection aspects.

"This book provides an analysis and introduction on the concept of combining the areas of semantic web and web mining, emphasizing semantics in technologies, reasoning, content searching and social media"--Provided by publisher.

The advent of Web 2.0 has led to a rebalancing of power between the customer and the company through the consumer's voice about the brand and referral behavior via electronic word of mouth. Customer opinions within the virtual brand communities can have a vast impact on a company’s sales and image. It is crucial for companies to promote and use customer contributions in order to enhance their brand image, retain customers, and develop their marketing strategy. Social Customer Relationship Management (Social-CRM) in the Era of Web 4.0 provides relevant theoretical frameworks and the latest results of empirical research on the strategic role of marketing 2.0, digital customer experience, and social customer relationship management on social networks. Covering a range of topics such as disruptive marketing, artificial intelligence, and customer behavior, this reference work is ideal for marketers, IT practitioners, CRM specialists, industry professionals, researchers, scholars, practitioners, academicians, instructors, and students.

With the purpose of building upon standard web technologies, open linked data serves as a useful way to connect previously unrelated data and to publish structured data on the web. The application of these elements leads to the creation of data commons called semantic web. Cases on Open-Linked Data and Semantic Web Applications brings together new theories, research findings and case studies which cover the recent developments and approaches towards applied open linked data and semantic web in the context of information systems. By enhancing the understanding of open linked data in business, science and information technologies, this reference source aims to be useful for academics, researchers, and practitioners.

"This book explores the potential of Web 2.0 and its synergies with the Semantic Web and provides state-of-the-art theoretical foundations and technological applications"--Provided by publisher.

The past ten years have seen a rapid growth in the numbers of people signing up to use Web-based social networks (hundreds of millions of new members are now joining the main services each year) with a large amount of content being shared on these networks (tens of billions of content items are shared each month). With this growth in usage and data being generated, there are many opportunities to discover the knowledge that is often inherent but somewhat hidden in these networks. Web mining techniques are being used to derive this hidden knowledge. In addition, the Semantic Web, including the Linked Data initiative to connect previously disconnected datasets, is making it possible to connect data from across various social spaces through common representations and agreed upon terms for people, content items, etc. In this book, we detail some current research being carried out to semantically represent the implicit and explicit structures on the Social Web, along with the techniques being used to elicit relevant knowledge from these structures, and we present the mechanisms that can be used to intelligently mesh these semantic representations with intelligent knowledge discovery processes. We begin this book with an overview of the origins of the Web, and then show how web intelligence can be derived from a combination of web and Social Web mining. We give an overview of the Social and Semantic Webs, followed by a description of the combined Social Semantic Web (along with some of the possibilities it affords), and the various semantic representation formats for the data created in social networks and on social media sites. Provenance and provenance mining is an important aspect here, especially when data is combined from multiple services. We will expand on the subject of provenance and especially its importance in relation to social data. We will describe extensions to social semantic vocabularies specifically designed for community mining purposes (SIOCM). In the last three chapters, we describe how the combination of web intelligence and social semantic data can be used to derive knowledge from the Social Web, starting at the community level (macro), and then moving through group mining (meso) to user profile mining (micro).

"This book focuses on the data mining and knowledge management implications that lie within online government"--Provided by publisher.