Who's #1: INSEAD, Harvard, Wharton, LBS? (A): Designing Research to Measure the Strength of Business Schools Brands (Japanese)
Niessing Joerg; Chandon Pierre
Product #:IN-2397
Supplier:INSEAD
Discipline:Marketing
Setting:Global
Subjects:
Industries:
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Learning Objectives
1) The case can be used to teach the fundamentals of branding. It illustrates how consumers perceive, evaluate and respond to brands. The case also discusses a step by step approach to building a strong brand.
2) It can also be used to discuss in more detail how different branding concepts like brand identity, brand positioning, brand equity, brand perception as well as brand metrics and brand value work together in a coherent branding strategy.
3) The case could also be used to focus on brand metrics only. Instructors could discuss in more detail how the equity and the value of a brand can be measured in comparison to the competition.
2. Customer intelligence (market research & marketing analytics)
1) Instructors can use the case to discuss how to set up a strategic marketing research project in general and how to manage it accordingly. Within this process questions related to problem definition, research design, data collection, proper survey writing and sampling can be addressed.
2) The case can also be used to discuss in detail the pros and cons of different research designs and research approaches and how these can be linked to the objectives of the research. Instructors could explain when to use exploratory approaches (like observations, focus groups, play-studios, ethnographies, in-depth-interviews), quantitative approaches (from survey research to social media listening) or causal research.
3) The case can also easily fill a 90-min class related to data analytics only. The focus could be on methodologies to better understand what customers care about when making decisions. Several techniques have been used in this project and instructors could for example discuss the pros and cons of stated importance, derived importance (regression modelling), maximum difference scaling and/or more complex discrete choice modelling techniques.