When viewing this, how do we know to find the optimal number of clusters? I used K-means and found the "elbow" on the graph that showed the optimal point but I am having trouble figuring this out from just the dendrogram.
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The interpretation varies depending on your metric and linkage used.
But in general, you want to keep branches that have "many" observations and with a “large" distance above (for the next merge).

Has QUIT--Anony-Mousse
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So the ideal way to go would be to find the groupings that have the largest distance between each of the clusters? We use Euclidian distance as our metric. – rmahesh Nov 05 '17 at 21:52