What Are The Best Natural Language Processing Applications?


Businesses demand data, yet the vast majority of information is unorganized and unavailable (more than 80%). In this scenario, Natural Language Processing (NLP) has shown to be invaluable.

A computational linguistics and artificial intelligence application called Natural Language Processing (NLP) makes it possible for companies to provide apps for customers who seek accurate data analysis. NLP is a collection of approaches for changing people’s thoughts, feelings, and behaviors. It stands for Neuro-Linguistic Programming and is founded on the premise that how we use language and our neurological processes are linked to how we think, feels, and conduct.

This capability allows for efficient human-computer interaction as well as the analysis and structuring of vast amounts of previously unprocessed data. According to Statista, the Natural Language Processing (NLP) market will develop 14 times faster in 2025 than it did in 2017. This includes a boost in value from around $3 billion to $43 billion!

Here’s the rundown:

Market Intelligence

Marketers can utilize natural language processing to gain a deeper understanding of their clients and use those insights to develop more effective tactics. They can analyse subjects, keywords, and make effective use of unstructured data thanks to the power of NLP. It can also be utilized to determine your consumers’ pain points and maintain track of your competition.

Sentiment Analysis

During discussion, humans can be sarcastic and sardonic. You can monitor social media mentions and respond to them before they escalate with real-time sentiment analysis. This NLP application allows your business to detect customer pulses. It also enables you to assess the impact of your most recent digital marketing campaign on your customers. Companies can do sentiment research regularly to have a better understanding of their operations.

Hiring And Recruitment 

HR departments know that selecting the right employees is among their most important duties. However, in the current situation, HR has so much data that sifting resumes and shortlisting prospects becomes overwhelming.

This work can be made easier with the help of Natural Language Processing. HR experts can use techniques like information extraction and named entity recognition to extract information from candidates such as their names, talents, locations, and educational histories. This enables for unbiased resume filtering and the selection of the best candidate for the job.

Text Summarization 

This NLP application is used to extract the most important information from a text and summarize it. The main goal is to make sorting through huge amounts of data in news items, legal documents, and scientific studies faster. Two methods of text summarization are possible based on natural language processing: extraction-based summarization, which extracts the most important words from an article and provides a summary without adding any additional details, and abstraction-based summarization, which rewrites the content to create new words.

Survey Analysis 

Surveys are an important tool for companies to evaluate their performance. Whether it’s gathering feedback on a new product launch or determining how well a company’s customer service is performing, survey analysis plays a critical role in identifying flaws and assisting companies in improving their goods.

The issue emerges when a high number of clients complete these surveys, resulting in an unusually big amount of data. The human brain can’t comprehend all of it. A natural language processor is introduced at this point. Businesses can use these techniques to obtain reliable information about their customers and improve their performance.

Targeted Advertising 

Lead generation continues to be a priority for businesses. They aim to reach out to as many people as possible for this reason. Natural Language Processing (NLP) is a fantastic tool for getting the appropriate ad in the right place at the right time. Keyword research, internet surfing patterns, emails, and social media platforms are all used to do this. Text mining software is used to carry out these activities.


Natural language processing (NLP) is quickly evolving, and the number of deep learning Applications for NLP is increasing by the minute. With so much information at our fingertips, it’s critical to comprehend, monitor, and, in some situations, restrict it.

NLP will grow even more popular in the coming years as a result of ready-to-use pre-trained models and low-code, no-code technologies that are available to everyone. Businesses, in particular, will continue to gain from NLP, which will help them improve their operations, customer happiness, cut expenses, and make better decisions.

So, if you wish to know more about NLP in business, contact the ONPASSIVE team.

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