Marketing Analytics

For Strategic Decision-Making

Price: 550.00 INR

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ISBN:

9780190130862

Publication date:

25/03/2021

Paperback

480 pages

Price: 550.00 INR

We sell our titles through other companies
Disclaimer :You will be redirected to a third party website.The sole responsibility of supplies, condition of the product, availability of stock, date of delivery, mode of payment will be as promised by the said third party only. Prices and specifications may vary from the OUP India site.

ISBN:

9780190130862

Publication date:

25/03/2021

Paperback

480 pages

First Edition

Moutusy Maity & Pavankumar Gurazada

Analytics is taking up an increasingly larger role in a marketer’s everyday decision-making. With a change in the customers’ nature of buying behaviour, there is a need for marketers to understand and use technology-enhanced data collection and analysis methods. Marketing Analytics: For Strategic Decision-Making has been written from a marketing perspective to provide a comprehensive overview of the analytical methods that are pertinent and important for a marketer through illustrations that make use of appropriate data sets and apply software such as R, SPSS and Excel.

Rights:  World Rights

First Edition

Moutusy Maity & Pavankumar Gurazada

Description

Designed primarily for the students of MBA specializing in Marketing and written in a lucid manner, the book will also be useful for marketing professionals trying to improve their understanding of marketing analytics.

First Edition

Moutusy Maity & Pavankumar Gurazada

Table of contents

Section I: The Need for Marketing Analytics

  1. Marketing Analytics and Marketing Research
  2. Marketing Analytics: Data including Web Analytics
  3. Descriptive Analysis
  4. A Primer on Machine Learning for Marketing Analytics
Section II: Understanding the Consumer and Customer: Using Structured Data
  1. Correlation and Regression
  2. Experimental Design
  3. Advertising Analytics
  4. Consumer Perception, Consumer Preference and Customer Portfolio Management
  5. Customer Acquisition
  6. Customer Retention
Section III: Understanding the Consumer and Customer: Using Unstructured Data
  1. Collecting and Understanding Social Media Data
  2. Chapter 12: Visualizing Consumer Engagement
  3. Chapter 13: Simulating Social Media Data Generating Mechanisms
  4. Chapter 14: Analyzing Social Network Data
  5. Chapter 15: Mining Meaning from Text
  6. Chapter 16: Collecting Unstructured Data in Offline Marketing Research
Section IV: Putting it all together
  1. Chapter 17: Coda

First Edition

Moutusy Maity & Pavankumar Gurazada

Features

• Provides comprehensive coverage of marketing analytics and its applications in the real world • Includes a dedicated chapter on understanding machine learning for marketing analytics • Presents all exercises demonstrating analytical concepts in at least two of the following analytics software: R-language programming, SPSS or Excel • Includes ample number of examples for students to practise and learn the basics of marketing analytics Instructor resources (a) Powerpoint slides (b) Instructor Manual

First Edition

Moutusy Maity & Pavankumar Gurazada

First Edition

Moutusy Maity & Pavankumar Gurazada

Description

Designed primarily for the students of MBA specializing in Marketing and written in a lucid manner, the book will also be useful for marketing professionals trying to improve their understanding of marketing analytics.

Read More

Table of contents

Section I: The Need for Marketing Analytics

  1. Marketing Analytics and Marketing Research
  2. Marketing Analytics: Data including Web Analytics
  3. Descriptive Analysis
  4. A Primer on Machine Learning for Marketing Analytics
Section II: Understanding the Consumer and Customer: Using Structured Data
  1. Correlation and Regression
  2. Experimental Design
  3. Advertising Analytics
  4. Consumer Perception, Consumer Preference and Customer Portfolio Management
  5. Customer Acquisition
  6. Customer Retention
Section III: Understanding the Consumer and Customer: Using Unstructured Data
  1. Collecting and Understanding Social Media Data
  2. Chapter 12: Visualizing Consumer Engagement
  3. Chapter 13: Simulating Social Media Data Generating Mechanisms
  4. Chapter 14: Analyzing Social Network Data
  5. Chapter 15: Mining Meaning from Text
  6. Chapter 16: Collecting Unstructured Data in Offline Marketing Research
Section IV: Putting it all together
  1. Chapter 17: Coda

Read More