When and Why to Use Marketing Math Models
Simulation Statistics
Duration: 60 minutes
Modality: asynchronous; in-class or remote learning
Author: Stephen J. Hoch, John Wesley Hutchinson, and Jagmohan S. Raju
Subject: Marketing
Learner Level: Undergraduate, Graduate
Team Size: Individual
Analytic Foundations for Marketing Decisions (AFMD) provides an interactive learning experience to help marketing students understand the key concepts behind commonly used marketing analyses. More than just an online problem set, the simple web application presents the definitions, formulae, and examples of quantitative analyses taught at Wharton.
Simulation Summary
Crafted alongside top Wharton faculty contributors Stephen J. Hoch, John Wesley Hutchinson, and Jagmohan S. Raju, Analytic Foundations for Marketing Decisions is a “Marketing Math” essential. Through this simple and publicly available learning tool, students will gain insight into marketing analysis by learning why and when to use common models – and how to interpret the results.
Although statistical analysis and modeling in marketing research can be quite sophisticated, much of the day-to-day number crunching for managers is simple arithmetic and algebra. The calculations themselves are not difficult; the challenge lies in knowing which analyses to employ and what to conclude from the results. This game teaches that real day-to-day problems are messy – they do not have “answers in the back of the book” like a homework assignment. In this regard, AFMD presents problems in a “real-life” format, enabling students to not only practice the calculations, but also to reason out which calculations are appropriate in each scenario. The analyses featured in AFMD are widely used in business and academics, but there is a seemingly endless set of variations in terminology, form, and function. The goal of this application is to create a solid foundation not only for Wharton courses, but also for the problems that students will encounter in the future.
AFMD contains both “easy” and “hard” problem sets for several hypothetical companies. Students learn when and how to calculate margin analysis, break-even analysis, chain model for segment value, customer lifetime value (CLV), and economic value to the customer (EVC). The application features extensive help notes, a glossary, and a window that allows students to display the answers to the problems once they have performed their calculations.
Interested in using AFMD? You can distribute the link to your students at any time! Click the button below to be taken to the publicly available learning tool.
About the Authors
Stephen J. Hoch is the Laura and John J. Pomerantz Professor Emeritus of Marketing. Professor Hoch is internationally known for research on retail merchandising, assortment, pricing, and promotion strategy. He consults extensively with leading consumer goods manufacturers and retailers around the world, assisting them in focusing retail strategies and improving pricing and merchandising tactics via point-of-sale data. Read more
Wes Hutchinson is Stephen J. Heyman Professor and Professor of Marketing at the Wharton School of the University of Pennsylvania. His research focuses on consumer and managerial decision making, particularly the interrelationships among attention, learning, confidence, decision making, and expertise in repeated choice environments. Read more.
Jagmohan S. Raju is the Joseph J. Aresty Professor and the Executive Director of the Wharton-Indian School of Business Program. Professor Raju served as the Chair of Wharton’s Marketing Department for six years, and the Vice Dean for Wharton Executive Education and Wharton Online; also for six years. Professor Raju is internationally known for his research on pricing strategies, retailing, managing private labels, short-term price discounts, category management, incentives, and sales force compensation. Read more.