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How can a text corpus stored in a customer relationship management (CRM)database be used for data mining and segmentation? In order to answer thisquestion we inherited the state of the art methods commonly used in naturallanguage processing (NLP) literature, such as word embeddings, and deeplearning literature, such as recurrent neural networks (RNN). We used the textnotes from a CRM system which are taken by customer representatives of aninternet ads consultancy agency between years 2009 and 2020. We trained wordembeddings by using the corresponding text corpus and showed that these wordembeddings can not only be used directly for data mining but also be used inRNN architectures, which are deep learning frameworks built with long shortterm memory (LSTM) units, for more comprehensive segmentation objectives. Theresults prove that structured text data in a CRM can be used to mine out veryvaluable information and any CRM can be equipped with useful NLP features oncethe problem definitions are properly built and the solution methods areconveniently implemented.

Case Studies on using Natural Language Processing Techniques in Customer Relationship Management Software