Marketing

This course will introduce students to AI and machine learning tools to draw managerial insights from data. Through this course, students will learn about methods such as classification trees and neural networks, and apply these methods across business applications settings such as marketing, finance, healthcare and other business areas.

Customer Lifetime Value (CLV) is a metric of burgeoning interest for firms, venture capitalists, financial analysts, and marketers. In this course, students learn how to build powerful and predictive data-driven CLV models. Topics covered include valuing firm equity using customer data, using RFM segmentation for direct marketing, customer acquisition and retention, and measuring the impact of a loyalty program.

This course is designed to offer you an overview of the major principles of persuasion. The emphasis will be on developing a marketing communications approach that will fit into a firms’ marketing program. The course will cover how to set effective communication objectives, decide what to communicate and how to develop a message execution approach.

Study of the paradigm that success of a product lies not only in its acceptance by the end consumer but also in how it is priced and how it reaches the intended consumer, with emphasis on understanding and analyzing the issues, problems, and opportunities characteristic of the channel relationship and of the various faces of pricing.

Introduction to Brand Strategy is designed to introduce students to core branding concepts through case analysis (done out of class) and branding exercises completed in class within brand teams including: brand audit, brand positioning, brand platform. Brand strategy elements to be introduced include: choice between branded house vs house of brands; sponsored and endorsed brands; brand architecture and brand portfolio; brand equity.

Students will learn the most common methods managers use to gain insight about customers and markets as well as the objectives/advantages/disadvantages associated with different research designs such as qualitative methods, surveys and experiments. Students will not learn specific analytic methods but rather how to design studies to yield valid results.

Marketing is evolving from an art to a science as data is now the key source of decision making. This course will teach you how to use analytics and data to address decisions by marketing managers, with emphasis on pricing and promotion decisions. A key part of the class is understanding how different types of data can—or can’t—be used to answer managerial questions, as well as how better planning can both simplify the analytics and increase your confidence in the findings. The course is organized around a hierarchy of topics. We begin with understanding pricing and promoting to an individual customer. This analysis provides the foundation as we move to more aggregate decisions, such as setting regular and promoted prices at the product level, managing category pricing, and store analytics. This class is designed to be very practical and hands-on. Most of the data we analyze is from real-world managerial problems, through collaborations with leading retailers and consulting firms who have brought problem-driven challenges to the classroom. Working knowledge of statistics (e.g., t-test and regression analysis) is required. You will learn and use R for data analysis, and no prior experience with R is necessary. The goal is not to train students to become experts in statistics or computer science; rather, students will learn to become a bridge between data scientists and managers.

Drawing on established theoretical frameworks of cognitive and social psychology, this course examines three aspects of consumer behavior: (1) individual, social and cultural influences on consumers, (2) psychological mechanisms of pre- and post-consumption processes such as decision-making and attitude formation and change, and (3) methodological issues in consumer analysis. Implications for strategy as well as marketing program design, measurement and execution are discussed. These topics will be studied through discussion of academic articles, cases and projects.

The course is designed to teach the concepts of customer-focused strategy in a healthcare context. The course should be useful to middle/upper-level administrators, physicians, and other professionals in the healthcare sector and includes: (1) Marketing strategy and implementation in healthcare and (2) Understanding client needs and monitoring metrics.

Introduction of new products to the market is a task of marketing executives whether in a startup or a large company, selling products or services, and for both B2C and B2B. Notably, 90% of new products fail. With this in mind, students learn the process, methodologies, and techniques of successful new product management. We focus on the product management process: (1) opportunity identification, (2) idea generation, (3) design, (4) test, (5) launch and analyze. The approach to each step is based on state-of-the-art frameworks, concepts, and tools that have been validated by innovative companies. Through lectures, case analysis, class discussions, in-class exercises, and a project, we address the challenge of bringing to market elegant and efficient solutions to meet strong customer needs.

The course teaches the building blocks of intercultural marketing, introducing frameworks for understanding the impact of cultural conditioning on international marketing strategy. It aims to help the students deepen their understanding of cultural influence, improve their intercultural marketing competencies, and increase their ability to deal with unpredictable and often ambiguous marketing contexts resulting from globalization.

Students focus on conjoint analysis, a state-of-the-art method for discovering consumer preferences. This framework enables a quantitative approach to new product design that encompasses analysis of market share, segmentation, targeting, and positioning. In this project-based course, student teams design a set of new product concepts using conjoint analysis, analyze related survey data, and present a data-driven strategic marketing plan for their chosen concept.

Introduction to key data-driven marketing concepts and both qualitative and quantitative tools that underly marketing strategy and tactics - including product, price, promotions, and place (4P's).

This course will introduce students to AI and machine learning tools to draw managerial insights from data. Through this course, students will learn about methods such as classification trees and neural networks, and apply these methods across business applications settings such as marketing, finance, healthcare and other business areas.

Course provides an introduction to digital marketing and examines ways it should be implemented. In addition to learning fundamental constructs and principles, students will focus on tools and skills needed for setting goals, implementing campaigns, and measuring success. Guest speakers and in-class exercises are used to provide insights and relevancy to this swiftly expanding area of marketing.

This course will teach students principles of survey design to prepare them to conduct surveys during and after business school. The course will cover articulating clear research objectives, defining the appropriate audiences to survey, determining the best methodology, and writing an actionable survey.