Natural Language Processing or NLP, as it commonly called, is gaining a lot of momentum these days. Organizations are using this piece of technology in various manners depending upon the nature of their business. While researching, I found that organizations were struggling to leverage the benefits data can offer them. They were having a hard time in achieving their targeted goals mainly because they kept on utilizing their time and energy in extracting actionable insights from the data collected from multiple platforms.
However, with the implementation of NLP solutions, organizations were able to extract, categorize, analyze, and utilize the analytics derived from the information gathered from social media and other platforms. This, in turn, helped these businesses to strategize the promotion campaigns and marketing policies, in a way that they can be optimally used to achieve a better revenue.
It made me curious as to how these companies were entangled in managing their resources to smoothen their business processes rather than focusing on the goal with what they started their business in the first place. My research led to some of the smart applications of NLP solutions that made it possible for these companies to utilize their energy and resources in generating a better profit quotient than managing the daunting task of restructuring, categorization, and classification of the data that they gathered.
As a technology consultant, I would like to share what I researched and what the revelations were that I discovered while walking down the aisle in the quest of finding the answers. Now, Before I begin this article, allow me to introduce the Natural Language Processing solutions, so that we can be on the same page when we come across the use-cases later in the article.
In a layman’s language, an NLP is a way that allows a machine or a computer system to understand, analyze, and manipulate the instructions given to them in a human language. This technology is governed by some Artificial Intelligence driven components, that allows the companies to inculcate the tech into their business. These components are;
Information Extraction: Extract the structured information from unstructured data.
Sentiment Analysis: Understand the mood of the comment, review, or post related to your business.
Answering Questions: Provide automated, real-time responses to simple customer-service problems and questions.
Semantic Search: Allows to provide information requested by a user rather than making him go through all the related keyword results.
Further, when tried to dig a bit deeper, I came across some use-cases that made me understand that how actually, NLP solutions helped the businesses. I’ve tried to list down some of them that stood out the most based on the criticality of the challenges they overcame, efficiency they offered to the business, and conveniently they were adopted by the businesses, respectively.
Siri
Have you ever thought that how do Apple’s smartphones respond to you when you instruct them? They present you with the accurate solutions to the requests that you made. It can unlock the phone just listening to your voice commands, and opens an app, does an internet search for you. This is because of the classification and speech-recognization algorithms -yet another component of an NLP solution, that allows Siri to understand and act as a virtual human being.
Amazon Comprehend
This is a Natural Language Processing service initiated by the e-commerce giant. It uses machine learning to extract insights and relationships that are encapsulated in the text. The service classifies the language of the text; abstracts key phrases, places, people, brands, or events. It also understands tonality and the context of the situation under which the text was written and analyze it using tokenization and part of speech and finally automatically organizes the collection of the text files. These APIs allows you to utilize the analyzed information into a wide range of application supporting your decision-making processes.
Google NLP API
This is an API that uses NLP’s Sentiment analysis to distinguish the document, comment, post or any review into categories of positive and negative. The text, speech, or any other graphics that carry the sentiments of sadness, anger, or hatred are labeled as ‘negetive’. While a file that has happy, enthusiastic, and good emotions are labeled as ‘positive’. This allows the business to plan, develop, and promote the strategies specifically for that genre of customers to achieve a better output from their business.
Brainvire’s Sentiment Analysis Tool
Me and my team of NLP experts came across an opportunity to implement one such component of NLP solution for one of our US-based client. What we did for the client was, we developed and implemented a sentiment analysis enabled tool that allowed the client to eliminate profanity from the content and verify it in fewer steps, under budget, and lesser time.
These are some of the use-cases and applications that are been successfully developed and implemented various components of NLP solutions into various processes of their business. Looking at these use-cases of NLP solutions it made me wonder, what future holds for this emerging yet powerful technology. So, let’s wait and keep a keen eye on the development this technology goes through.
I hope this article was helpful enough for you to understand the usefulness of the technology and you can understand why it is playing such a crucial role in restructuring the face of the business sector.
I have just begun my research about the NLP solutions and found it to be quite helpful for various business. If you want to know how you can leverage its astonishing features for your business, you can get in touch with me or my team, and we would like to help you out with your queries related to NLP solutions.
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