Natural language processing analysis of chats, call transcripts and e-mails

Chats and phone calls are an excellent channel for quick communication to the client and a powerful source of customer data. Machine learning methods and natural language processing techniques provide plenty of information from text chat data.

Business case

Machine learning and natural language processing techniques can extract plenty of useful information from chats and phone calls data. These channels are excellent and widely used for quick communication with the clients and provide plenty of data to analyse. Early detection of frequently discussed topics or problems in chats, such as products, bugs, or weak spots on the website is the key to preventing customer unhappiness. That means you can stop the current customers from churning, and potential ones from losing their interest in your products.


Our solution uses natural language processing methods to analyse text and audio data to find keywords and important points in the discussed topics. The most problematic issues are determined by estimating the sentiment of the conversations, using day-to-day, week-to-week, or month-to-month comparisons.


  • Quick processing, analysing, and sorting your data, plus detecting most important issues, helps you fix problems quickly and keep customers interested.
  • Using the topics and insights from chats and phone calls gives you the knowledge you need for running a successful retention campaign.

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Key contacts

David Vopelka - DataSentics

David Vopelka

FS&I Lead & AI Personalization Expert