Rotated Factor Matrix

The factor transformation matrix describes the specific rotation applied to your factor solution. This matrix is used to compute the rotated factor matrix from the original (unrotated) factor matrix. Smaller off-diagonal elements correspond to smaller rotations. Larger off-diagonal elements correspond to larger rotations.

Rotated factor matrix with variables in the rows and factor in the columns — Figure 2. Rotated factor matrix

The third factor is largely unaffected by the rotation, but the first two are now easier to interpret. The first rotated factor is most highly correlated with Toll free last month, Caller ID, Call waiting, Call forwarding, and 3-way calling. These variables are not particularly correlated with the other two factors.

The second factor is most highly correlated with Equipment last month, Internet, and Electronic billing.

Thus, there are three major groupings of services, as defined by the services that are most highly correlated with the three factors. Given these groupings, you can make the following observations about the remaining services:

Because of their moderately large correlations with both the first and second factors, Wireless last month, Voice mail, and Paging service bridge the "Extras" and "Tech" groups.
Calling card last month is moderately correlated with the first and third factors, thus it bridges the "Extras" and "Long Distance" groups.
Multiple lines is moderately correlated with the second and third factors, thus it bridges the "Tech" and "Long Distance" groups.

This suggests avenues for cross-selling. For example, customers who subscribe to extra services may be more predisposed to accepting special offers on wireless services than Internet services.

3-D scatterplot of factor loadings — Figure 3. Factor loadings plot

The factor loadings plot is a visual representation of the rotated factor matrix. If the relationships in the matrix are complex, this plot may be easier to interpret.