eigenvectors were the only tough part of the linear algebra course i took, i think that's b/c it's quite a bit to learn before you start seeing the point of it. methods like PCA are rely heavily on eigendecompositon and allow you to reduce the dimensions of data...this is useful in all sorts of ways like compression for instance (e.g. getting rid of the dimensions that aren't very meaningful).