The Concept of NLP

Natural Language Processing (NLP) is a branch of artificial intelligence that enable machines such as computers to understand, manipulate, and interpret human language. The main idea behind NLP is to enable computers to understand human communication (Chowdhary, 2020). For instance, in a text, a computer can be used to draw insights within the text. A perfect example is the amazon comprehend that uses a computer to identify the language used in a text, key phrases, places mentioned, people, events, or brands associated with the text. As some writers/speakers may be biased towards what they are writing about, NLP identifies how positive or negative the text is.

NLP uses two main techniques; syntax and semantic. Syntax refers to how the speaker arranges words that make grammatical sense (Techtarget, 2019). Examples are; word segmentation, sentence breaking, stemming, among others. NLP uses these syntax techniques to derive meaning based on grammatical rules. Semantic is the meaning of words. NLP applies algorithms to derive meaning from semantic words and sentence structure. Currently, NLP is based on deep learning in which a type of AI examines and uses data to improve computer understanding.

Use of NLP in a Business Situation

Organizations can employ NLP in different situations. One of them is reducing customer complaints. Nearly, every successful organization provides platforms for customers to air their views. Some of these platforms may be social media, emails, surveys, and call center conversations. To extract essential trends from customers’ feedback, a company can use NLP to analyze data from the platforms and identify why the customers are dissatisfied. As a result, it can improve where applicable. An example of a company that uses NLP to reduce complaints is Royal Bank of Scotland. Sas.com (n.p) cites that the company uses a technique of NLP called text analytics.

Secondly, businesses can use NLP to make marketing decisions. Since the main benefit of NLP is to extract a wide range of information from a text, marketing also involves the use of information. For a business to make the right choices of marketing, it needs lots of interpreted data both internally and externally. Some of these data may be the kind of audiences, the product brand position, among other considerations of marketing. NLP program is capable of analyzing such information, and this helps a business identify marketing needs. After the marketing of products, the business can still use NLP techniques such as measuring metrics to assess how the marketing campaign was viewed and what impact it had on the targeted audiences.

From an article published by BBC (2011), NLP can be used to spot connection, avoid information overload, and improve understanding. BBC is a big media house that produces a large amount of news and other material in different languages. This can be a significantly great challenge for journalists and staffs at the BBC. To help in how the news material connects to each other, and avoid information overload, it uses NLP techniques to get the semantic data, classify content, and analyze sentiments. This saves the company a lot of time, money, and effort and also reduces the number of workforces. Furthermore, the company can disseminate timely news.

How Communication Industry can use NLP

I have selected a communication industry specializing in providing services such as phone calls, messaging, and internet. Virtually, an organization increases when the customer’s loyalty increases (Lee & Cunningham, 2001). Many organizations in different industries strive to increase customer’s loyalty because that will lead to gaining competitive advantage. The communication industry is flooded with many companies, and for a particular company to gain a competitive advantage, it must identify ways of how to be loyal to customers and fulfil their needs. The perfect way to achieve this is by using NLP techniques.

 NLP can increase the customer’s satisfaction in many ways. One, analyzing customers’ feedback. What customers say is directly connected to how the company is positioned in the market. The feedback; complaints, and compliments can be assessed and interpreted by NLP techniques like text analytics. It allows a company to improve where necessary, thereby increasing loyalty. Secondly, to gain a competitive advantage through customers’ loyalty, a company has to ensure high-quality services. As in the case of the communication industry, customers will need speed in the network service, availability of services, and accessibility. The company can achieve this by using NLP to manage data within these services. For instance, to provide internet or phone calls services, programming will be needed, a company can employ NLP in such cases.

Also, a communications company can use NLP to avoid information overload, and thus serve customers better. All these uses of NLP can help a communications company serve its customers well, retain them, and thus gain competitive advantage. This is because to gain a competitive advantage; an organization has to ensure customers’ loyalty. Besides gaining a competitive advantage, by using NLP, an organization will be able to overcome obstacles, thereby improving its business. 

References

BBC. (2011). Natural language processing. Retrieved from https://www.bbc.co.uk/rd/projects/natural-language-processing

Chowdhary KR (2020) Natural Language Processing. In: Fundamentals of Artificial Intelligence. Springer, New Delhi. https://doi.org/10.1007/978-81-322-3972-7_19

Lee, M. and Cunningham, L.F. (2001), “A cost/benefit approach to understanding service loyalty”, Journal of Services Marketing, Vol. 15 No. 2, pp. 113-130. https://doi.org/10.1108/08876040110387917

Sas.com. (n.d.). What is natural language processing? Retrieved from https://www.sas.com/en_us/insights/analytics/what-is-natural-language-processing-nlp.html

Techtarget. (2019, May 20). What is natural language processing? – Definition from WhatIs.com. Retrieved from https://searchbusinessanalytics.techtarget.com/definition/natural-language-processing-NLP