000			04678nam a22002177a 4500
005			20241110191632.0
008			241110b |||||||| |||| 00| 0 eng d
020			_a9789354242625
082			_a658.83 _bGUP
100			_aGupta, Seema _95037
245			_aMarketing analytics
260			_bWiley India Pvt. Ltd. _aNew Delhi _c2021
300			_axxiii, 374 p.
365			_aINR _b999.00
500			_aTable of content: Chapter 1 Introduction 1.1 Marketing Analytics 1.2 Data for Marketing Analytics 1.3 What Are Business Intelligence, Analytics, and Data Science? 1.4 Analysis 1.5 Exploratory Data Analysis 1.6 Descriptive Analysis 1.7 Predictive Analytics 1.8 Prescriptive Analytics 1.9 Organization of the Book Chapter 2 Segmentation 2.1 Introduction 2.2 Benefits of Customer Analytics 2.3 Factors Essential for Obtaining Benefits from Customer Analytics 2.4 Segmentation Analytics 2.5 Cluster Analysis Chapter 3 Positioning 3.1 Introduction 3.2 Perceptual Mapping 3.3 White Spaces 3.4 Umbrella Brands 3.5 Multidimensional Scaling Chapter 4 Product Analytics 4.1 Introduction 4.2 Analyzing Digital Products 4.3 Analyzing Non-Digital Products Chapter 5 Pricing 5.1 Introduction 5.2 Goals of Pricing 5.3 Bundling 5.4 Skimming 5.5 Revenue Management 5.6 Promotions 5.7 Discounting 5.8 Price Elasticity of a Beverage Brand Chapter 6 Marketing Mix 6.1 Introduction 6.2 Market Mix Modeling 6.3 Variables in Market Mix Modeling 6.4 Techniques of Market Mix Modeling Chapter 7 Customer Journey 7.1 Introduction 7.2 Importance of Customer Journey 7.3 What is Customer Journey Mapping? 7.4 Customer Journey Mapping and Use of Analytics 7.5 How to Map a Customer’s Journey? 7.6 What Does Analytics with Customer Journeys Involve? 7.7 Customer Journey Use Case for a Beverage Brand 7.8 Journey of a Loyal Customer 7.9 Principal Component Analysis 7.10 Applying Principal Components to Brand Chapter 8 Nurturing Customers 8.1 Introduction 8.2 Metrics for Tracking Customer Experience 8.3 Upgrading Customers: Use Case of Upselling 8.4 Logistic Regression Analysis 8.5 Use of Logistic Regression as a Classification Technique Chapter 9 Customer Analytics 9.1 Introduction 9.2 Customer Lifetime Value 9.3 Churn Analytics Chapter 10 Digital Analytics: Metrics and Measurement 10.1 Introduction 10.2 Important Web Metrics 10.3 Attribution Challenge and Shapley Regression 10.4 Test and Control or A/B Testing 10.5 Example Use Case: Webpage Design with A/B Testing 10.6 Search Engine Marketing 10.7 Search Engine Optimization 10.8 SEM or SEO: Which Is the Optimal Choice? 10.9 Social Media Analytics 10.10 App Marketing Metrics Chapter 11 Artificial Intelligence and Machine Learning 11.1 Introduction 11.2 Importance of AI in Marketing 11.3 Key Applications of AI in Marketing 11.4 Common Terminologies – AI, ML, and DL 11.5 Important Concepts of ML 11.6 Random Forests 11.7 Model Evaluation Using ROC, AUC, and Confusion Matrix 11.8 Boosting Trees 11.9 Variable Importance 11.10 Simple Feed-Forward Network 11.11 Deep Neural Network 11.12 Image Recognition 11.13 Working with Textual Data 11.14 Recommendation Systems 11.15 Challenges Involved with AI Chapter 12 Data Visualization 12.1 Introduction 12.2 Necessity of Data Visualization 12.3 Charts 12.4 Visualizations Useful with Common Data Science Techniques 12.5 Conclusion Summary Key Terms Discussion Questions Project Appendix 1: Installing and Using R Appendix 2: Installing Python Endnotes Index [https://www.wileyindia.com/marketing-analytics.html]
520			_aMarketing Analytics offers marketing students, teachers, and professionals a practical guide to marketing decision models and marketing metrics. The book offers unified reference for various marketing analytics use cases across industries and diverse businesses, such as consumer packaged goods marketers, restaurants and hospitality, e-commerce, entertainment, etc. It provides nuances and trade-offs in using statistical/machine learning methods for various marketing decisions. It explains key marketing metrics and their use with an analytics technique. It offers common best practices of the industry with choice of methods for various decision problems. (https://www.wileyindia.com/marketing-analytics.html)
650			_aMarketing-Management
650			_aMarketing-Statistical methods
700			_aJathar, Avadhoot _918623
942			_cBK _2ddc
999			_c7389 _d7389