When building a K-means clustering model, you notice that the clusters did not segment on...

When building a K-means clustering model, it's important to ensure that the data is properly scaled, as K-means is sensitive to the scale of the variables. If the variables have different scales, the clustering may not segment as expected. Standardizing or normalizing the data can often improve the results.