Interpreting Cluster Means/Centers for High Dimensionality Clustering Using Kmeans Clusting

I'm trying to perform Kmeans clustering on a data set with multiple variables (8 to be exact), but it's hard to visualize this clustering because of its dimensionality.

Would looking at its cluster means/center given in the output of the kmeans() function be helpful in visualizing it?

Thank you!