Data mining- Clustering techniques I have a project for comparison between clustering techniques using the data set of SSA for birth names from 1910-2013 years for the different states.

I have finished applying my clustering techniques on my data set and the output of the clusters were the clusters of the states for each year.

Now I can know from my results; which states are close to each other with the birth names and which were not. By looking 

I would like to have interesting results to make my project report interesting, Which states are similar in birth names are not enough to make the read be excited about my project. 

My questions:


any ideas of what can be learned from my project?
How can I show the comparison between the clustering techniques? anyway other than seeing how Homogeneous the clusters are?
It's common to perform clustering on certain features, and then use characteristics such as mean differences between other features (not used in clustering) to show how clusters differ.  It's not always meaningful to say that clusters differ merely by lower distances between cluster centers and objects assigned to them (as in k-means).

As an example, you might acquire other features (variables) for the states and then average each feature among objects assigned to each cluster.  Then show bar charts of averages for those variables among all the clusters to assist in explaining how the clusters differ.  You might also test for significantly different means of the supplemental features across clusters.