Customer Analytics Course - MBA Program at ESMT Berlin Business School - Capstone Case: Grosse Pointe Associates and the "Microvan"
This repository contains the case study on Grosse Pointe Associates' investigation into the potential market for "microvans." The case explores the project's objectives, methodology, and data analysis techniques. It serves as a capstone case that combines various multivariate techniques in a decision-oriented setting.
The repository includes the following files:
- Detailed description and analysis of the case Case PDF (Click to open)
- Dataset CSV used for the analysis.
- PowerPoint Presentation summarizing insights and findings (Click to open).
- Jupyter Notebook containing all the codes (Click to open).
The case revolves around the U.S. auto industry's constant search for the next big trend in automotive design. Grosse Pointe Associates (GPA), a boutique consulting firm specializing in auto industry trends, identified a potential market niche for smaller, luxury-oriented minivans. The case discusses the factors driving this trend and the attributes desired by potential buyers.
The objectives of this case study are as follows:
- To provide experience in customer segmentation within a market.
- To determine which customer segment(s) would be suitable for targeting based on data analysis.
- To establish a connection between the identified segments and relevant demographic variables for effective targeting.
The survey data required for the analysis is provided as a separate file. It includes responses from GPA's in-house panel, which consists of a large cross-section of the general U.S. adult population. The dataset comprises 400 respondents, along with demographic and behavior-based information.
You can access the dataset file here. It is also available in the repository.
The case study employs various multivariate techniques, such as regression, factor analysis, and cluster analysis, to analyze the data. The goal is to reduce the dataset while retaining crucial information and insights. The case study explores the process of data reduction and its implications for understanding and communicating the survey results effectively.
Feel free to explore the files and use the information provided in your analysis.