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Voice of customer is typically captured through multiple connect points like surveys, warranty claims, social media, and so on. Customer verbatim is collected through these connect points to encourage free expression of opinion by customers. Such verbatim data is generally of high value and is typically analyzed using Natural Language Processing (NLP) techniques for translating into influencing actions in manufacturing, customer service, marketing, and product development departments. One of the challenges in analyzing unstructured verbatim data is to map that data onto appropriate concern codes (CCCs), which are typically used in automotive firms for tracking quality and satisfaction metrics. These concern codes map to a hierarchy of function areas in the organization aimed at improving product, service and hence the customer’s overall experience.