One big feedback I got from user testings was that the legends were unclear, and there were a lot of data. To remedy that, I added legends and selected only a few coffee beans to reduce clutter and information overload.
I also realized the acidity score in coffee cupping score does not necessarily indicate higher/lower acidity, but rather, how the acidic taste makes the coffee unique. I can't really use this data to tell beginners what coffee to choose because it is too compliacted. With the time I had, I decided to analyze balance instead of acidity and trying to give out the same information as before.
I want my audience to be people that drink coffee often enough, and are interested in expanding their knowledge on different coffee beans.
One of the person I user tested was more of a beginner coffee drinker that doesn't know much about coffee at all. Because of that, they were confused by all the terminologies, and also the recommendations on coffee beans. I decided I want to focus on coffee drinkers that are actively interested in trying out more coffee, and made my project more tailored to that concept.
I have cited references on the bottom of the Shorthand page.
I had a lot of trouble finding good data for my purposes, and eventually I decided to just give up on finding data, and trying to make my limited analysis as good as they could be. In the future, perhaps I should find interesting dataset first before commiting to an idea.
Also, I had a really rough Wednesday and Thursday because of some personal issue. My presentation was way below satisfactory. That is on me :c