How NLP Helps Businesses Gain Traction and Harness Their Potential?

The data generated from conversations with customer service representatives and on social media sites is 80 percent of time unstructured. To gain most from such kind of data, organizations are turning to NLP (natural language processing). Notably, NLP gives machines the ability to read, understand and derive meaning from human languages. Such technology helps determine the uncertainty of human language.

Let's see how businesses are leveraging NLP for better efficiency.

Sentiment Analysis

This application is widely used for web and social media monitoring in order to enable businesses to gain a broad public opinion on the organization and its products and services. Today, organizations, worldwide, are adopting the ability to extract insights from the text and emoticons from social media. With the capacity to understand customer's attitudes and responses. The advent of digital media represents a great opportunity for businesses of any industry to acquire the needs, opinions, and intent that users share on the web and social media. Here, to understand the customer's expression, NLP is used to crack the sentiment behind it.

As emotions provide a lot of information that addresses customer's choices, companies always consider sentiments as the most significant value of the opinions users express through social media. Therefore, NLP for sentiment analysis focused on emotions discovers extremely favorable situations while helping companies understand their customers better to improve their experience, which will help the businesses change their market position.

Email Filters

One of the use cases of NLP is an email filter that analyses the text in the emails that flow across the servers. Through such analysis, email providers can stop spam based email contents from entering their mailbox.

Ad Replacement

As we know, emails, social media, e-commerce and browsing behaviors contain a lot of information about customer interest. Through the huge potential of such data, various companies today generate most of their revenue selling ads (Google and Facebook). NLP applications like keyword matching and sense disambiguation are deployed here for ad placements.

Voice Recognition

The NLP tools enable companies to create intelligent voice-driven interfaces for any system that can understand human language and queries. The platforms used by a company depends on a custom knowledge graph instead of trying to understand concepts based on normal human language usage patterns. Notably, such a graph is created for each application and performs a much better job identifying concepts that are relevant in the customer domain.

Extraction of Information

Today most of the business decisions in industries like Finance are driven by sentiments influenced by the news which is present in the form of text, infographics, and images. Here, NLP taking these text, analyze and extract the related information in a format that can be used in the decision-making process.

As it stands now, the arrival of advanced statistical NLP algorithms has enhanced the capabilities of using statistical inference to understand human conversation by predicting the probability of certain results. The program embedded with NLP features can constantly improve itself with more data it processes. Such technology is increasing the feasibility of attaining insights from the huge amount of unstructured data.