About the Book

Often termed as the ‘new gold,’ the vast amount of social media data can be employed to identify which customer behavior and actions create more value. Nevertheless, many brands find it extremely hard to define what the value of social media is and how to capture and create value with social media data.
In Creating Value with Social Media Analytics, we draw on developments in social media analytics theories and tools to develop a comprehensive social media value creation framework that allows readers to define, align, capture, and sustain value through social media data. The book offers concepts, strategies, tools, tutorials, and case studies that brands need to align, extract, and analyze a variety of social media data, including text, actions, networks, multimedia, apps, hyperlinks, search engines, and location data. By the end of this book, the readers will have mastered the theories, concepts, strategies, techniques, and tools necessary to extract business value from big social media that help increase brand loyalty, generate leads, drive traffic, and ultimately make sound business decisions. Here is how the book is organized.

The book is non-technical in nature best suited for business (and information Systems) managers, owners, consultants, students, and professors, etc.

Here is how the book is structured.


Chapter 1: Creating Value with Social Media Analytics—this chapter lays down the foundation of the book by introducing a generic social media value creation model (VCM) which is explored in the rest of the chapters. The social media VCM is inspired by the well-known Michael Porter’s Value Chain (Porter, 1985). The model explains the process of value creation through a set of activities that firms need to undertake to create value with analytics. Throughout the chapter, we define and equally explore several tangible and intangible social media analytics values to firms and customers. We also provide a detailed discussion on social media return on investment and construct a variety of social media value metrics. A real-world case study is also part of the chapter which shows how Jack in the Box used social media analytics to create value.

Chapter 2: Understanding Social Media—social media is a big part of our lives today that it is almost impossible to imagine our lives without it. This chapter introduces social media and its underlying technologies including the Internet, Web 1.0, Web 2.0, Web 3.0, and Web 4.0. A discussion on the use of social media for business purposes is also part of the chapter. The chapter also identifies common social media issues.

Chapter 3: Understanding Social Media Analytics—this chapter introduces the eight layers of social media analytics framework which is explored in the subsequent chapters in detail. The chapter explores social media analytics concepts, tools, history, and industry. A detailed discussion is included on uses of social media analytics for business intelligence purposes. We also distinguish between social media analytics and business analytics with examples. We also discuss four types of social media analytics: descriptive analytics, diagnostic analytics, predictive analytics, and prescriptive analytics and common social media analytics limitations and issues.


Chapter 4: Analytics-Business Alignment—configuring and understanding social media tools alone are not enough; to get the most out of it, analytics should be aligned with business strategy. Chapter 4 discusses strategies and techniques to align social media analytics with business goals. A detailed discussion is provided on social media strategy formulation and its components, such as ownership plan, content strategy, account strategy, platform strategy, and implementation plan. The chapter also provides an analytics maturity models that organization use to assess their current state of analytics maturity and provide a structured path towards improving data analytics competence for an enterprise-wide business decision-making.


Chapter 5: Capturing Value with Text Analytics—chapter 5 is dedicated to text analytics, the first layer of social media analytics. A variety of textual elements of social media are discussed along with the steps needed to carry out text analytics, its purpose, and the tools of text analytics. The chapter also includes a case study on networks and a step-by-step guide on analyzing social media text (e.g., tweets and comments) using Semantria for Excel and IBM Watson Analytics for social media.

Chapter 6: Capturing Value with Network Analytics—Networks are the building blocks of social media and are formed as social media users make friends, follow brands, like and share content, review and rate products, and forge professional ties. Chapter 6 deals with network analytics and seeks to identify influential nodes (e.g., people and organizations) and their position in the network. Network level properties (such as clustering coefficient, density, diameter, and density) and node level properties (such as, degree, betweenness, and eigenvector centralities) are discussed in detail. Network structure driven strategies and types of social media networks, such as Facebook, Friendship Network, Twitter, and YouTube are also discussed. The chapter also includes a case study and a step-by-step tutorial on NodeXL for analyzing social media networks.

Chapter 7: Capturing Value with Actions Analytics— chapter 7 deconstructs the 3rd layer of social media analytics, that is, the actions analytics. The chapter explains extracting, analyzing, and interpreting the actions performed by social media users, such as likes, dislikes, shares, mentions, and endorsement. The chapter also includes a case study and a step-by-step tutorial on Hootsuite’s analytical tool.

 Chapter 8: Capturing Value with Search Engine Analytics—search engines are the gateways to social media and help users search for and find information. This chapter explains search engines analytics and search engine optimization (SEO) techniques and strategies. Search engines analytics focus on analyzing historical search data to gain valuable insight into trends analysis, keyword monitoring, and advertisement spending statistics. A detailed discussion on search engine types, black hate, and white SEO techniques, and offsite and onsite SEO techniques is also part of the chapter. Practical step-by-step guidelines are provided using Google Trends and Google Correlate to analyze search engine data.

Chapter 9: Capturing Value with Location Analytics— location matters. Chapter 9 deals with location analytics, which is also known as spatial analysis or geospatial analytics. The chapter outlines tools and techniques to mine and maps the location of social media users, contents, and data. A real-world case study on mining mobile phone data and a step-by-step guide on geo-mapping tabular business data using Google Fusion Table and ArcGIS Online are also provided.

Chapter 10: Capturing Value with Apps Analytics— mobile apps are the next frontier in the social business landscape. Chapter 10 deals with mobile analytics and marketing issues. A practical tutorial on analyzing and understanding in-app purchases, customer engagement, and demographics are included in the chapter. A practical tutorial on the Countly apps analytics tool and a real-world case study is also included.

Chapter 11: Capturing Value with Hyperlinks Analytics—social media traffic is carried out through the hyperlinks embedded within it, thus hyperlink (e.g., in-links and out-links) analysis can reveal, for example, Internet traffic patterns and sources of the incoming or outgoing traffic to and from a source. Hyperlink analytics is discussed in chapter 11. A real-world case study and step-by-step guidelines on hyperlink analytics using VOSON are also included.

Chapter 12: Capturing Value with Multimedia Analytics—the last but not the least layer of social media analytics is multimedia analytics. Social media multimedia analytics is the art and science of harnessing business value from video, images, audio, and animations, and interactive contents posted over social media outlets. This chapter introduces multimedia analytics tools, techniques, and strategies.


Chapter 13: Social Media Analytics Capabilities—having sound social media analytics capabilities can place a firm in a superior business position, which can generate a greater value for a firm and its shareholders. In order to harness value from the social media data, organizations need sophisticated social media analytics capabilities, particularly predictive and prescriptive analytics abilities. This chapter discusses the analytics capabilities that firms need to effectively leverage social media for competitive advantage.

Chapter 14: Social Media Security, Privacy, & Ethics— engaging through social media introduces new challenges related to privacy, security, data management, accessibility, governance, and other legal and information security issues such as hacking and cyber-warfare. Chapter 14 discuss these issues in detail alongside a discussion and framework on social media risk management. A case study on social media risks assessment is also part of the project.