Business Applications of Natural Language Processing in the Digital World

In most modern call centers, all customer conversations are recorded and analysed using Natural Language Processing (NLP) algorithms. The purpose of recording and analysing the calls is essential to generate business insights and customer understanding. The reason why companies are relying on NLP is the ability to extract valuable information from unstructured data sources such as voice calls. Mihup is a prominent name in voice technology solutions and our NLP-based analytics tools are being used by a number of clients in diverse areas and applications.

Let’s go ahead and look at some of the ways in which businesses can apply NLP technology to meet their needs.

· Sentiment Analysis — Human expressions such as sarcasm, happiness or annoyance are crucial components to understand how a customer felt in a conversation. Sentiment analysis is the process of using NLP to identify nuances indicating emotions.

· Text Classification — In text analysis, machines use NLP to automatically understand, process and segregate raw text data obtained from emails, chats and social media sources.

· Chatbots and Voice Assistants — These are used in home automation systems, and as personal assistants on smartphones and even in vehicles for automatically answering our voice commands. NLP is used to make these tools understand and respond to spoken commands in appropriate manner and accent on real-time basis.

· Speech Recognition — Using speech recognition tools, businesses can leverage NLP to convert spoken words into text format for machines to read and understand.

· Text Extraction — Contact centers use NLP for text extraction applications such as sorting the support tickets raised by customers and identifying specific information such as order numbers or phone numbers from the large volumes of raw data automatically.

· Machine Translation — This is among the very first uses of NLP for machines. The technology is rapidly evolving and today leading translation platforms have become highly efficient with the power of NLP.

· Automatic Summaries — It is the NLP-based ability of machines to summarize text by highlighting the key points of text data presented and it helps users to source desired information quickly by sifting through knowledge resources such as articles, news pieces, whitepapers and electronic documents.

· Auto-Correct and Text Suggestions — We have all seen how MS-word and language check tools such as Grammarly or even the predictive text feature on smartphones auto-corrects spelling errors and offers text suggestions as we type the words. These are examples of NLP based analytics at work.

· Intent identification–NLP powered solutions can help businesses understand the intent of a customer through analysis of text or voice data.

· Urgency Identification — Advanced NLP solutions can detect words that convey urgency, restlessness or seriousness of the matter and help the systems classify the conversation as ‘urgent’ to help in faster resolution.

AI based SaaS NLP tools such as the solutions offered by Mihup are rapidly transforming digital world through the most fundamental process of communication i.e., ‘Language.’