Understanding customer behavior and driving customer satisfaction are necessary for any business to succeed in the competing market. Companies need to be aware of the prevailing customer perceptions to make more accurate and effective plans for product development and marketing. Customer feedback is available through multiple channels. Specifically, we are interested in the unstructured data available as text that would be available through social media, comments from a survey, voice recordings of customer interactions, and chat transcripts. Analyzing such data correctly is critical, as it reveals everything from buying trends to product flaws and provides a significant business advantage. It would further strengthen business opportunity to uncover customer interests, product improvements, and marketing insights. In this paper, we explore different technologies of Deep Learning and Natural Language Processing (NLP) that would help analyze better the contextual information to capture customer feedback.
Ramaswamy, S., & DeClerck, N. (2018). Customer perception analysis using deep learning and NLP. In Procedia Computer Science (Vol. 140, pp. 170–178). Elsevier B.V. https://doi.org/10.1016/j.procs.2018.10.326