[D] What are the difference between these 2 algorithms?

So I am currently doing a customer segmentation project which I am trying to learn and visualise data using 3d scatter graphs based on basket analysis, a friend told me K-means algorithm was the most optimal algorithm for this task, but out of curiosity I produced results using a hierarchical algorithm but not sure what the results pertain? Comparing both results, I am struggling to understand what is actually happening? In the k means algorithm I can see the 3rd cluster show higher annual income but less spending which means alternative methods such as advertisements can help encourage this demographic to spend more, but the hierarchical algorithm just seems random, not sure what is happening here? The colour of the clusters just seem like they have changed positions (not sure if this matters or if I did something wrong) compared to k means and clusters look bigger however the clusters remain in the same position/pattern as that of k means but less accurate reads, not sure what is happening here?