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Book Review: “Business Analytics – Applications to Consumer Marketing”

Book Review: “Business Analytics – Applications to Consumer Marketing”


book reviewThe recent book by Dr. Sandhya Kuruganti and Hindol Basu is a must read and an essential reference for anyone who wants to understand business analytics and enable profitable growth by leveraging data to deepen the understanding on customers. A lot of organizations talk about customer centricity and the importance of Data in achieving this objective and this book discerningly and magnificently guides the reader to the path of customer centricity using the data available at our hands in a simple, lucid, and a palatable manner.

The salient feature of this book is that it will help individuals with varied levels of analytic proficiency; be it a less-mathematically-trained person who aspires to learn and adopt analytics for on organization more effectively compared to current practices, or someone migrating from academia to the corporate world and is transitioning from table top knowledge to real life applications, or even the seasoned veterans who will appreciate the nuances or advanced techniques in the book to help them with difficult and challenging situations in a complex business setting.



One of the challenges in creating an analytical organization is to enmesh theory and practice. The authors’ rich and collective experience as industry practitioners is reflected strongly through the real life applications in the book. A liberal dose of application oriented examples to explain concepts and its usage elegantly bridges the gap between theory and practice that makes it perspicuous even for people without prior background in mathematics or statistics. .

The book starts and ends with the most critical aspect of any attempt at customer centricity, which is the creation, availability and usage of data in the manner it can be leveraged to know more about our customers and how we can then cater to their needs and aspirations. Chapters in the book relating to Usage, Cross Sell, Retention, Pricing and Credit Bureau effectively encapsulates and outlines this concept on how to grow, nurture, enhance, and maximize customer engagement and value through a data driven approach. In fact, it is a relevant read for almost all customer facing organizations with valuable and insightful information on a wide array of business problems across sectors such as Group buying and Hotel pricing; Telecom Churn, Life Insurance Persistency and Mortgage Prepayments; Airline Rewards,   Sales Promotions and Credit Card Usage Strategies; Supply Chain Operations Reference (SCOR) models; and Price setting for Ecommerce & Auctions.

Needless to say Quantitative Methods, the core medium for accurate customer assessment and relevant and precise targeting is an essential component of the book; once again illustrated comprehensively with appropriate business applications; Cluster Analysis to Decision Trees, Discrete Choice Regression models, Survival analysis for example to name a few

Finally and equally important, the book also addresses the core need of any organization on how to create an Analytical ecosystem driven preferably by the top brass through change management, multi-disciplinary teams, institutionalized processes, nimble technology, and the quintessential data ecosystem as the analytics backbone to deliver the best results for the organization.

Personally, while the entire book with its extensive and elaborate exposition on business analytics is a brilliant read, I would like to pick up a couple of topics that I have always been passionate about; first being Cross sell and the other, Analytics Ecosystem.

While Cross Sell is part of most CRM presentations; executing an effective Cross Sell strategy has never been easy. The book lays out rather lucidly the types of cross- sell, the challenges associated with adopting these approaches, the various techniques available including Event Based Triggers, Multi Bundling Analysis (MBA), Decision Analysis and Recommender systems used most often in the Ecommerce domain. The examples of MBA includes shopping cart data utilization from Ecommerce sites, and good examples of Amazon & Netflix are given on the Recommender models, while Personal Loan to Credit cards X-Sell is used to explain Decision Trees and Logistic Regression.

The other topic extremely close to my heart is the Analytics Ecosystem, which in my view is the most critical aspect to create a successful analytics driven business. The book clearly explains the two ways to create a Data Warehouse, the Extract Transform Load (ETL) requirements, the criticality of the Data Quality and the steps to be taken to identify Data Quality issues, and the overall systems & process requirements to create an overall CRM platform. The book makes a very pertinent point that while CRM gained relevance in the individual customer facing service industry, it is becoming equally if not more relevant in the B2B environment.

Given that the Ecommerce world is taking us by storm and the success of any ecommerce venture would ultimately be determined by the success of their analytics backend, the book by Sandhya and Hindol would have gained even more prominence had this been covered in more depth including the creation, relevance, and usage of Big Data in Ecommerce scenarios. However, this does not dilute in anyway the relevance of their book as a practical guide and reference point for Business Managers, Analytics Practitioners, Business Intelligence Practitioners and especially those students who are planning to grow their careers in the corporate world across most industries & sectors of our economy including Financial Services, Telecom, and Retail.

Happy reading !

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BOOK DETAILS:

Title: “Business Analytics: Applications to Consumer Marketing”

Authors: Sandhya Kuruganti and Hindol Basu

Publisher: McGraw-Hill Education India

See Also
Sathyajith Bhat Adobe

Publication Date: March 2015

Available at Flipkart and Amazon India/UK/US/CA

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Author Profiles: Sandhya Kuruganti is a senior analytics leader with more than 18 years of experience in the financial services domain. As a management consultant, she currently advises companies in India in adopting data driven analytical strategies across various business functions. A postgraduate from Delhi School of Economics, India and a doctorate in Economics from Rutgers University, US, Sandhya has been one of the pioneers of the usage of decision sciences within the Indian banking industry. As Senior Vice President, she was also at the forefront of Citibank’s strategic drive of implementing advanced analytics across markets in Asia Pacific and Europe.

Hindol Basu heads the analytics practice for Tata iQ, and is responsible for conceptualization, development and implementation of data & analytics solution across the Tata Group. He is part of the Group initiative for evangelizing analytics and data driven decision making. With more than 14 years of experience in the area of risk and marketing analytics, Hindol possesses deep analytical expertise in the areas of price management, development of risk and marketing models, machine learning and credit bureau analytics spanning both US and Asia Pacific regions. Hindol holds a bachelor’s degree in Engineering from Indian Institute of Technology, Kharagpur and an MBA from Indian Institute of Management, Bangalore.


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