Standard natural language processing (NLP) is a messy and difficult affair. It requires teaching a computer about English-specific word ambiguities as well as the hierarchical, sparse nature of words in sentences. At Stitch Fix, word vectors help computers learn from the raw text in customer notes. Our systems need to identify a medical professional when she writes that she 'used to wear scrubs to work', and distill 'taking a trip' into a Fix for vacation clothing. Applied appropriately, word vectors are dramatically more meaningful and more flexible than current techniques and let computers peer into text in a fundamentally new way. I'll try to convince you that word vectors give us a simple and flexible platform for understanding text while speaking about word2vec, LDA, and introduce our hybrid algorithm lda2vec.