When I should use PCA?
If you can, go for some non-linear dimensionality reduction technique. The most powerful are Autoencoders, but you can also use t-SNE or other manifold techniques.

The problem of PCA is that it can extract only latent factors that are linearly associated with your variables. Using non-linear techniques, less variables can let you capture more of the original variance.