Part 4 case study
A BAV teaching file for reading brand perception, reducing 48 attributes into interpretable factors, and clustering similar fast-food and casual-dining brands.
The updated file contains 48 brand-attribute percentages. PCA shows how much of that high-dimensional perception space is captured by the first few components; the rotated factor map gives the two-axis view a more readable business interpretation.
Which brands are perceived as close competitors, which brands occupy premium or value territory, and how much Brand Asset can be reconstructed from the latent factors.