Many of a company’s business processes are based on language data, either in the context of communication like email or as documents like purchase orders, technical manuals or contracts. It doesn’t make a difference if these processes are customer related or happen company internal like a vacation request. During these processes a large amount of unstructured, textual data gets created and stored.


What is Natural Language Processing (NLP)?

Natural language processing (NLP) combines techniques from linguistics, computer science and artificial intelligence (AI) with the objective to computationally analyze, understand and process language data to create value and actionable insights from it.

Further subfields are natural language generation and the implementation of conversational interfaces. Recently, the application of AI techniques to NLP tasks has driven NLP research and use cases.

What does Natural Language Processing (NLP) transform and optimize?

With these methods valuable, so far inaccessible, information which was not accessible yet, can get extracted from textual data and be used to improve process quality and efficiency or provide whole new services.

  • Email requests can be automatically forwarded to the appropriate department. Response times are shortened and insufficient processing of customer inquiries is reduced.

  • Unsatisfied customers and product problems can be automatically identified by analyzing social media data. Corresponding countermeasures and alternatives can be taken and initiated at an early stage.

  • Customer support can be automated with chatbots. Customer service is optimized and a new customer experience is created.

NLP Trends

New NLP trends are the use of deep learning, word embedding and general purpose models such as BERT and GPT-2.

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NLP Tools

The number of available open source tools and libraries are growing steadily. Two of the most widely used tools are NLTK and spaCy.

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NLP Building Blocks

There exist many different application techniques like text classification or sentiment analysis which often get combined.

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NLP Application Areas

NLP applications can lever improvements in manifold application areas. Let’s have a closer look into some use cases.

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How does NLP work?

Methods from linguistics, big data techniques and AI enable the recognition and processing of natural language.

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