Although they were not the original audience, I expect that this software will mostly be adopted by software developers, data scientists, and digital artists.
What's in it for software developers?
There's a big direct benefit: it implements a lot of the standard NLP functionality; it's easy to get, easy to build, and easy to run; if you really want to calculate sentiment values for tweets you can be doing that in about ten minutes. But there are many indirect benefits to software developers as well: it is an excellent introduction to working with the lower levels of the standard NLP stack; if you are thinking of working with the Stanford CoreNLP libraries it is a very useful source of sample code and client examples; and if you want to extract new linguistic features the oopcorenlp framework will make that development process much faster and easier.
What's in it for data scientists?
There's a big direct benefit: it generates a lot of high quality numerical features out of data sets that many people care about and the numerical data it generates is easy to feed into statistical packages or machine learning algorithms. But there are many indirect benefits to data scientists as well: it is an excellent introduction to working with linguistic features; instead of endlessly browsing through Kaggle you could running your own supervised training algorithms against curated data sets within a few hours.
What's in it for digital artists?
I'm not sure that there is a direct benefit, but I am personally very excited about the possibilities. Do you want to turn text into music? It can do that. Do you want to turn text into images? It can do that. Do you want to mash up text, images, and music into a whole new multi media experience? It can do that.