Marketing analytics (Record no. 7389)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 04678nam a22002177a 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20241110191632.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 241110b |||||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| International Standard Book Number | 9789354242625 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 658.83 |
| Item number | GUP |
| 100 ## - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Gupta, Seema |
| 245 ## - TITLE STATEMENT | |
| Title | Marketing analytics |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) | |
| Name of publisher, distributor, etc. | Wiley India Pvt. Ltd. |
| Place of publication, distribution, etc. | New Delhi |
| Date of publication, distribution, etc. | 2021 |
| 300 ## - PHYSICAL DESCRIPTION | |
| Extent | xxiii, 374 p. |
| 365 ## - TRADE PRICE | |
| Price type code | INR |
| Price amount | 999.00 |
| 500 ## - GENERAL NOTE | |
| General note | Table of content:<br/>Chapter 1 Introduction<br/><br/>1.1 Marketing Analytics<br/><br/>1.2 Data for Marketing Analytics<br/><br/>1.3 What Are Business Intelligence, Analytics, and Data Science?<br/><br/>1.4 Analysis<br/><br/>1.5 Exploratory Data Analysis<br/><br/>1.6 Descriptive Analysis<br/><br/>1.7 Predictive Analytics<br/><br/>1.8 Prescriptive Analytics<br/><br/>1.9 Organization of the Book<br/><br/>Chapter 2 Segmentation<br/><br/>2.1 Introduction<br/><br/>2.2 Benefits of Customer Analytics<br/><br/>2.3 Factors Essential for Obtaining Benefits from Customer Analytics<br/><br/>2.4 Segmentation Analytics<br/><br/>2.5 Cluster Analysis<br/><br/>Chapter 3 Positioning<br/><br/>3.1 Introduction<br/><br/>3.2 Perceptual Mapping<br/><br/>3.3 White Spaces<br/><br/>3.4 Umbrella Brands<br/><br/>3.5 Multidimensional Scaling<br/><br/>Chapter 4 Product Analytics<br/><br/>4.1 Introduction<br/><br/>4.2 Analyzing Digital Products<br/><br/>4.3 Analyzing Non-Digital Products<br/><br/>Chapter 5 Pricing<br/><br/>5.1 Introduction<br/><br/>5.2 Goals of Pricing<br/><br/>5.3 Bundling<br/><br/>5.4 Skimming<br/><br/>5.5 Revenue Management<br/><br/>5.6 Promotions<br/><br/>5.7 Discounting<br/><br/>5.8 Price Elasticity of a Beverage Brand<br/><br/>Chapter 6 Marketing Mix<br/><br/>6.1 Introduction<br/><br/>6.2 Market Mix Modeling<br/><br/>6.3 Variables in Market Mix Modeling<br/><br/>6.4 Techniques of Market Mix Modeling<br/><br/>Chapter 7 Customer Journey<br/><br/>7.1 Introduction<br/><br/>7.2 Importance of Customer Journey<br/><br/>7.3 What is Customer Journey Mapping?<br/><br/>7.4 Customer Journey Mapping and Use of Analytics<br/><br/>7.5 How to Map a Customer’s Journey?<br/><br/>7.6 What Does Analytics with Customer Journeys Involve?<br/><br/>7.7 Customer Journey Use Case for a Beverage Brand<br/><br/>7.8 Journey of a Loyal Customer<br/><br/>7.9 Principal Component Analysis<br/><br/>7.10 Applying Principal Components to Brand<br/><br/>Chapter 8 Nurturing Customers<br/><br/>8.1 Introduction<br/><br/>8.2 Metrics for Tracking Customer Experience<br/><br/>8.3 Upgrading Customers: Use Case of Upselling<br/><br/>8.4 Logistic Regression Analysis<br/><br/>8.5 Use of Logistic Regression as a Classification Technique<br/><br/>Chapter 9 Customer Analytics<br/><br/>9.1 Introduction<br/><br/>9.2 Customer Lifetime Value<br/><br/>9.3 Churn Analytics<br/><br/>Chapter 10 Digital Analytics: Metrics and Measurement<br/><br/>10.1 Introduction<br/><br/>10.2 Important Web Metrics<br/><br/>10.3 Attribution Challenge and Shapley Regression<br/><br/>10.4 Test and Control or A/B Testing<br/><br/>10.5 Example Use Case: Webpage Design with A/B Testing<br/><br/>10.6 Search Engine Marketing<br/><br/>10.7 Search Engine Optimization<br/><br/>10.8 SEM or SEO: Which Is the Optimal Choice?<br/><br/>10.9 Social Media Analytics<br/><br/>10.10 App Marketing Metrics<br/><br/>Chapter 11 Artificial Intelligence and Machine Learning<br/><br/>11.1 Introduction<br/><br/>11.2 Importance of AI in Marketing<br/><br/>11.3 Key Applications of AI in Marketing<br/><br/>11.4 Common Terminologies – AI, ML, and DL<br/><br/>11.5 Important Concepts of ML<br/><br/>11.6 Random Forests<br/><br/>11.7 Model Evaluation Using ROC, AUC, and Confusion Matrix<br/><br/>11.8 Boosting Trees<br/><br/>11.9 Variable Importance<br/><br/>11.10 Simple Feed-Forward Network<br/><br/>11.11 Deep Neural Network<br/><br/>11.12 Image Recognition<br/><br/>11.13 Working with Textual Data<br/><br/>11.14 Recommendation Systems<br/><br/>11.15 Challenges Involved with AI<br/><br/>Chapter 12 Data Visualization<br/><br/>12.1 Introduction<br/><br/>12.2 Necessity of Data Visualization<br/><br/>12.3 Charts<br/><br/>12.4 Visualizations Useful with Common Data Science Techniques<br/><br/>12.5 Conclusion<br/><br/>Summary<br/><br/>Key Terms<br/><br/>Discussion Questions<br/><br/>Project<br/><br/>Appendix 1: Installing and Using R<br/><br/>Appendix 2: Installing Python<br/><br/>Endnotes<br/><br/>Index<br/>[https://www.wileyindia.com/marketing-analytics.html] |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc. | Marketing 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.<br/>(https://www.wileyindia.com/marketing-analytics.html) |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Marketing-Management |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical term or geographic name as entry element | Marketing-Statistical methods |
| 700 ## - ADDED ENTRY--PERSONAL NAME | |
| Personal name | Jathar, Avadhoot |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Book |
| Source of classification or shelving scheme | Dewey Decimal Classification |
| Withdrawn status | Lost status | Source of classification or shelving scheme | Damaged status | Not for loan | Collection code | Bill No | Bill Date | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price | Total Checkouts | Full call number | Accession Number | Date last seen | Copy number | Cost, replacement price | Price effective from | Koha item type |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| Dewey Decimal Classification | Marketing | TB2249 | 28-10-2024 | Indian Institute of Management LRC | Indian Institute of Management LRC | General Stacks | 11/10/2024 | Technical Bureau India Pvt. Ltd. | 694.30 | 658.83 GUP | 006381 | 11/10/2024 | 1 | 999.00 | 11/10/2024 | Book |