Marketing Analytics -

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Editeur : Apple Academic Press

Langue : Anglais

Parution : 01/02/2023

Format : Moyen, de 350g à 1kg

Nombre de pages : 368.0

Expédition : 690

Dimensions : 15.6 x 23.6 x 24.0

ISBN : 9781774910887

Résumé :

1. Introduction to Marketing Analytics 2. Statistics for Marketing 3. Evolution of Data Analytics 4. Segmentation and Targeting Analysis 5. Important Marketing Metrics: A Snapshot 6. Consumer Buying Behavior 7. Understanding Consumer Behavior Using Market Basket Analysis 8. Neuromarketing Techniques for Consumer Analytics 9. New Product Development 10. Natural Language Processing for Branding 11. Forecasting Sales and Price 12. Sales Prediction and Conversion 13. Role of Supply Chain Analytics in Marketing Analytics 14. Web and Social Media Analytics 15. Marketing Analytics and Its Applications

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Biographie:

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.

Sommaire:
A comprehensive overview of marketing analytics, incorporating machine learning methods of data analysis that automate analytical model building. It covers segmentation and targeting, statistics, marketing metrics, buying behavior, neuromarketing techniques, new product development, web and social media analytics, etc....