Big Data A Road Map for Successful Digital Marketing 1st Edition by Amandeep Singh, Rohit Bansal, Sandhir Sharma ISBN 9783110733785 3110733781

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ISBN 10: 3110733781
ISBN 13: 9783110733785
Author: Amandeep Singh, Rohit Bansal, Sandhir Sharma

Big Data A Road Map for Successful Digital Marketing 1st Edition Table of contents:

1. Bui Huy Khoi Chapter 1 AIC Algorithm for Employee Motivation
2. Introduction
3. Methodology
4. Sample Approach
5. Blinding
6. Results
7. Akaike Information Criterion Selection
8. Variance Inflation Factor
9. Autocorrelation
10. Model Evaluation
11. Solutions
12. Conclusion
13. Further Research
14. Reena Malik, Sonal Trivedi Chapter 2 Big Data Analytics in Predicting Consumer Behavior
15. Introduction
16. Review of Literature
17. Tools of Predictive Analytics in Marketing
18. RFM Modeling
19. Black-Box Model
20. Personal Variable Model
21. Statistical Analysis and Market Research Tools
22. Gaining Insights from Big Data Analytics
23. Big Data and Consumer Purchase Decision
24. Analytics – The Road Ahead
25. Conclusion
26. Seprianti Eka Putri Chapter 3 Using Big Data on Customer Behavioral Analysis in Indonesia
27. Introduction
28. Overview of C2C E-Commerce
29. Defining Big Data
30. Define Consumers in Big Data
31. Volume
32. Velocity
33. Variety
34. Consumer Behavior is Affected by Big Data
35. Scanning Information on Needs Recognition
36. Scanning Information Against Information Seeking
37. Scanning on Alternative Evaluations
38. Informed Scanning of Purchasing Decisions
39. Information Scanning of Post-Purchase Behavior
40. Credibility Impact and Security System on Consumer Behavior
41. The Buying Decision’s Credibility
42. Post-Purchase Behavior’s Credibility
43. Consumer Behavior and the Impact of Security Systems
44. Information Retrieval on the Security System
45. The Assessment Alternatives’ Safety System
46. The Security System on Purchasing Decisions
47. Conclusion and Recommendation on Customer Buying Behavior
48. Get to know Customers Better
49. Build a more Effective Marketing Strategy
50. Building Relationships and Consumer Trust in the Business
51. Improve the Consumer Shopping Experience
52. Increase e-Commerce Innovation
53. Recommendation System About Needs
54. Recommendation System of Information Search
55. Recommendation Framework for the Evaluation of Alternatives
56. Recommendation System on Post-Purchase Behavior
57. B. J. D. Kalyani Chapter 4 Customer Vision with Big Data Analytics
58. Introduction
59. Influence of Big Data on Digital Marketing
60. Personalized Learning Management
61. Improved Customer Behavior Analysis
62. Enriched Employee Retention Processes
63. Rise in Revenue
64. Present Data Content with Statistics
65. Methodology
66. Learn
67. Decide
68. Buy
69. Use
70. Reengage
71. Case Study
72. Data Flow Diagram
73. Implementation
74. Results and Discussions
75. Conclusion
76. Fazla Rabby, Ranga Chimhundu, Rumman Hassan Chapter 5 Digital Transformation in Real Estate Marketing: A Review
77. Introduction
78. Background and Rationale
79. Methodology
80. Literature Review
81. The Role of the Influencer
82. The Future of Marketing
83. Big Data Analytics
84. Virtual Reality in Marketing
85. Digital Marketing in Real Estate
86. Innovative Technologies
87. Disruptive Innovation
88. Blockchain and the Internet of Things
89. Artificial Intelligence
90. Drones and Wearable Technologies
91. Augmented and Virtual Reality; 3D Scanning
92. A System Dynamic Model for Technology Adoption
93. Findings and Conceptual Model
94. Conclusion
95. Namrata Sandhu, Sandhir Sharma, Dilpreet Singh Chapter 6 Drivers of Bank Penetration: A Bankers’ Perspective
96. Introduction
97. Operational Definition and Previous Research
98. Methodology
99. Sample
100. Respondent Demographics
101. Data Analysis
102. Data Reduction
103. Model Development
104. Model Test
105. Factor 1 – Supply Side Innovations
106. Factor 2 – Growth and Profit Objective
107. Factor 3 – Competition
108. Factor 4 – Demographic Dividend
109. Factor 5 – Regulatory Mandates
110. Factor 6 – Cost Effective Solutions
111. Discussion
112. R. Dhaya, R. Kanthavel Chapter 7 Elaborative Perceptions on Big Data and Social Media Analytics
113. Introduction
114. Literature Survey
115. Need for Big Data in Social Media Analytics
116. Social Media Analytics Tools
117. Social Media Analytics Software for Internal Use
118. Social Media Analytics Tools for External Use
119. Structured and Unstructured Data Management in Social Media
120. Impacts on Social Media Analytics
121. How Might Big Data Help Social Media Advertisers and Entrepreneurs?
122. The Challenges of Working with Big Data
123. Benefits of Leveraging Big Data for Social Media
124. Conclusion
125. Harmanpreet Kaur Chapter 8 Impacts of Big Data on Mobile Marketing (Big Data and Mobile Marketing)
126. Introduction
127. Key Areas of Mobile Marketing with Big Data
128. A Summary of Big Data’s Position in Sales and Marketing
129. Mobility and Big Data: A Connection
130. Get the Edge of Big Data in Real Time Analysis
131. Critical Elements of a Good Marketing Campaign based on Data
132. Customized Mobile Marketing with Big Data
133. Coming up with the Best Price
134. Better Customer Analysis
135. More Customized Selling and Marketing
136. Better Overall Product
137. Social Media and Big Data
138. Tools and Metrics
139. Website Ranking
140. Analytics of Online Traffic
141. Social Media Mentoring
142. Engagement of Customer Via Mobile Marketing by using Big Data
143. Improved Customer Engagement
144. Customer Records must be Maintained and Often Updated
145. Use the Desired Contact form of a Client
146. Using Omnichannel
147. Emphasize the Importance of Security
148. Issues and Challenges faced during Mobile Marketing by using Big Data Customized Decisions
149. Issues of Big Data in Mobile Marketing
150. Opportunities of Big Data in Mobile Marketing
151. Impacts of Big Data on Mobile Marketing
152. Conclusion
153. Komal Kapoor Chapter 9 Implications of Big Data in Execution of Social CRM Techniques: Cases from Developed and Emerging Economies
154. Introduction
155. Big Data
156. Social CRM
157. Big Data in Social CRM
158. Cases and Implications
159. Conclusion and Future Areas of Research
160. S. Balamurugan, M. Selvalakshmi, M. Palanivelrajan Chapter 10 Leveraging Big Data for Digital Marketing
161. Introduction
162. Digital Marketing Objectives
163. Importance of Big Data
164. Big Data Analytics Application
165. Conclusion
166. Ram Krishan Chapter 11 Performance Analysis of Algorithms Used for Workflow Scheduling in Cloud Environment
167. Introduction
168. Task Scheduling in Cloud
169. Workflow Scheduling
170. Performance Parameters
171. Review and Analysis of Scheduling Algorithms
172. Conclusion
173. Manish Mohan Baral, Subhodeep Mukherjee, Chittipaka Venkataiah, Sudhir Rana, Bhaswati Jana Chapter 12 Role and Impact of Big Data Analytics Determinants in Improving Supply Chain Agility
174. Introduction
175. Background of the Study
176. Dynamic Capabilities View (DCV)
177. Theoretical Framework and Development of Hypotheses
178. Competitive Advantage (CA)
179. Organizational Flexibility (OF)
180. Knowledge Management (KM)
181. BDA and SCA
182. Research Methodology
183. Results
184. Demographics of Firms Surveyed
185. Reliability and Validity
186. Exploratory Factor Analysis
187. Structural Model and Testing of Hypothesis
188. Discussion
189. Conclusion
190. Kriti Aggarwal, Gulshan Goyal Chapter 13 Role of Big Data in Growth of Digital Marketing
191. Introduction to Digital Marketing
192. Growth of Digital Marketing and Popular Options
193. Big Data Evolution and Parameters for Data Evaluation
194. Role of Big Data in Digital Marketing
195. Application of Big Data in Digital Marketing
196. Big Data Techniques used in Digital Marketing
197. Conclusion
198. Oliver Moisés Cervantes Flores, Valeria Meléndez Cervantes, Claudia Malcón Cervera, José Gerardo De la Vega Meneses Chapter 14 Text Mining Applied as Business Intelligence in the Tourism Industry
199. Introduction
200. General Objective
201. Specific Objectives
202. Theoretical Framework
203. What do Hotels do with Guest Reviews when the Room is delivered, and how has that Review been Measured?
204. Text Analysis Applications and Effectiveness in Results
205. Methodology
206. Transformations and Assumptions Carried out to Develop the Text Analysis in the Hotel Chain
207. Methodological Development
208. Los Angeles
209. Seattle
210. San Francisco
211. Conclusions and General Recommendations to Improve the Measurement of Customer Opinion Through Text Analysis
212. Alock Gupta, Tanvi Kaushik, Vipin Mittal Chapter 15 Big Data: Impact on Digital Era of Twenty-First Century
213. Introduction
214. What is Data?
215. Classification of Data
216. Traditional Data
217. Big Data
218. Characteristics of Big Data
219. How Big Data came into Existence
220. Why is Big Data Important?
221. From where does it come? Or Sources of Big Data
222. Pros of Big Data
223. Cons of Big Data
224. Applications of Big Data
225. Big Data Analytics
226. What does this Imply?
227. What is the Aim of Big Data Analytics?
228. Types of Analytics
229. Tools for Analyzing the Data
230. HADOOP: What exactly is HADOOP?
231. What is Hadoop’s Evolution?
232. What is the Significance of this for Big Data Analytics?
233. Core HADOOP Modules
234. Benefits of using HADOOP
235. Challenges in HADOOP
236. Conclusion
237. Tareq Rasul, Rhodora Abadia, Ashfaq Ahmad Chapter 16 Enhanced Customer Experience through Reasoned Big Data Analytics Strategies
238. Introduction
239. Brief Theoretical Background
240. Customer Experience (CX)
241. Effective BDA Strategies for Enhanced CX
242. Overcoming the Challenges of BDA For Enhanced Cx
243. Future Research Directions
244. Conclusion
245. Rohit Malhotra Chapter 17 Asymmetries in Concepts of Digital Asset Pricing Sustainability Literature
246. Introduction and Conceptual Overview
247. Theoretical Constructs
248. DA Pricing and Static Versus Dynamic Pricing Framework
249. The Methodology used in this Study
250. The Terminologies used in the Study
251. Asymmetric Literature Review
252. Pricing Strategies for DA – A Literature Survey
253. Sustainable Pricing Strategies for Digital Assets (Spsda) Matrix for Improving the Digital Assets
254. Explanation of the SPSDA Matrix
255. Conclusion and Future Scope
256. List of Contributors
257. About the Editors
258. Index

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