Clustering Pitfalls

Blindly applying k means clustering can lead to misleading results, primarily influenced by the scale of your data. It's crucial to normalize your variables to ensure that no single feature, like price, dominates the clustering outcome. Always maintain a healthy skepticism about your data and consider clustering as just one step in a larger analytical process.