1st Edition

Marketing Analytics A Machine Learning Approach

Edited By A. Mansurali, P. Mary Jeyanthi Copyright 2023
    366 Pages 12 Color & 174 B/W Illustrations
    by Apple Academic Press

    366 Pages 12 Color & 174 B/W Illustrations
    by Apple Academic Press

    With businesses becoming ever more competitive, marketing strategies need to be more precise and performance oriented. Companies are investing considerably in analytical infrastructure for marketing. This new volume, Marketing Analytics: A Machine Learning Approach, enlightens readers on the application of analytics in marketing and the process of analytics, providing a foundation on the concepts and algorithms of machine learning and statistics. The book simplifies analytics for businesses and explains its uses in different aspects of marketing in a way that even marketers with no prior analytics experience will find it easy to follow, giving them to tools to make better business decisions.

    This volume gives a comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automates analytical model building. The volume covers the important aspects of marketing analytics, including segmentation and targeting analysis, statistics for marketing, marketing metrics, consumer buying behavior, neuromarketing techniques for consumer analytics, new product development, forecasting sales and price, web and social media analytics, and much more.

    This well-organized and straight-forward volume will be valuable for marketers, managers, decision makers, and research scholars, and faculty in business marketing and information technology and would also be suitable for classroom use.

    1. Introduction to Marketing Analytics

    A. Mansurali and P. Mary Jeyanthi

    2. Statistics for Marketing

    P. V. Chandrika, Sandeep Kelkar, and Archana Arjun Ghatule

    3. Evolution of Data Analytics

    S. Radha Rammohan

    4. Segmentation and Targeting Analysis

    S. Radha Rammohan

    5. Important Marketing Metrics: A Snapshot

    K. Nagarajan

    6. Consumer Buying Behavior

    Ishpreet Kaur Saini

    7. Understanding Consumer Behavior Using Market Basket Analysis

    B. Uma Maheswari and R. Sujatha

    8. Neuromarketing Techniques for Consumer Analytics

    Siddique Kadavathe Peedikayil

    9. New Product Development

    Lokesh Balasundaram

    10. Natural Language Processing for Branding

    V. D. Krishnaveni

    11. Forecasting Sales and Price

    P. V. Chandrika and Dr. Hema Doreswamy

    12. Sales Prediction and Conversion

    R. Sujatha and B. Uma Maheswari

    13. Role of Supply Chain Analytics in Marketing Analytics

    R Vanathi, R. Swamynathan, and S. Thilagavathi

    14. Web and Social Media Analytics

    M. Mallika Sankar, Fezeena Khadir, and P. Senthilmurugan

    15. Marketing Analytics and Its Applications

    V. Harish


    Dr. A. Mansurali is an avid researcher and a well-rounded academician in the field of business management, with special focus on marketing, analytics, and applied research. With innovative and engaging pedagogy, he engages and trains students to understand the current developments in the field and has several academic contributions in the form of publications to his credit. He is proficient in R, Python, Tableau, Power BI, and machine learning algorithms. He is also a certified trainer for R and machine learning from STAR certification. His competence in analytics and research has earned him key roles in sponsored research projects. He has spent over 10 years of teaching management graduates marketing and analytics-related courses and researching the same. He has also received funding from the University Grants Commission to conduct research in microfinance. Prior to academics, Dr. Mansurali served at Janalakshmi Financial Services as Area Head, Sales, in the role of serving financially excluded people and was involved in the activities of customer acquisition for financial services and handling payment cycles. Dr. Mansurali has completed his undergraduate BCA from the PSG College of Arts and Science and MBA from the PSG College of Technology, India, and doctoral degree from Anna University, Chennai, India. He has also completed PGDCA, MSc (Applied Psychology), and MA degrees from Bharathiar University School of Distance Education. He also holds a PGP "Business Analytics and Business Intelligence degree jointly offered by Great Lakes School for Executive Learning McCombs School of Business, The University of Texas at Austin, USA. And he is a lifetime learner having certification in the areas of digital marketing, business intelligence, and analytics. He also engages academic fraternity and industry and trains them in the areas of business intelligence, analytics, and research though MDP and FDPs.

    Dr. P. Mary Jeyanthi is Associate Professor at the Jaipuria Institute of Management, Jaipur, Rajasthan, India. She has a decade of industry experience as an information technology professional in the banking sector at HDFC Bank Ltd, Business Intelligence Unit, Chennai, Tamil Nadu, India, as well as expertise in business intelligence and forecasting analytics. Dr. Jeyanthi has published many research papers in various national and international reputed journals and has conducted several workshops on research methodology and business intelligence. She has been invited as a speaker at intercollege symposiums and summits across India. She also acts as a resource person for many colleges for soft skills training and workshops related to research paper writing. Dr. Jeyanthi has contributed many articles in magazines related to building human capital and business analytics. She has expertise in the novelty approach of writing and managing analytics with real-time scenarios. Her research interests are in business intelligence and analytics, artificial intelligence, big data analytics, management information systems, data analysis, and business models. Dr. Jeyanthi has done research on A New Implementation of Mathematical Models with Metaheuristic Algorithms for Business Intelligence and has worked on business intelligence and analytics initiatives on high net worth (HNW) portfolios, for which she is responsible for the creation and execution of strategies.

    “An interesting and novel book that deals with marketing analytics in modern organizations. It presents in accessible form complex information and theoretical perspectives that are often difficult to grasp for the non-marketing expert. The book is particularly significant due to its breadth of coverage. It touches on all essential aspects of machine learning and marketing analytics. If you are a marketing professional, researcher, or student interested in marketing analytics and machine learning, then this book is for you. I have read a number of books in the field, but this book draws my attention because it is comprehensive and well-constructed.”
    —Prof. Dieu Hack-Polay, Professor of Management, Crandall University, Canada; Associate Professor of Organizational Studies, University of Lincoln, UK