Businesses need data but unfortunately, the more substantial part of the data, which covers almost 80% of it, is unstructured and inaccessible. This is where Natural Language Processing (NLP) has come in as a situation saver.
Natural Language Processing is an application of artificial intelligence and offers the facility of offering applications to companies that need to analyze their data reliably. NLP is a set of techniques used to help people change their thoughts, feelings, and behaviors. It stands for Neuro-Linguistic Programming and is based on the idea that the way we think, feel and behave is linked to the way we use language and our neurological processes. This quality efficiently enables human-computer interaction and also allows for the analysis and formatting of large volumes of previously unused data. According to Statista, the Natural Language Processing (NLP) market is expected to grow 14 times in 2025 than it was in 2017. This means increasing from around 3 billion USD to 43 billion!
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In this article, we’ll talk about the top 11 Trending NLP Applications in 2024.
Here goes the list:
1. Market Intelligence – Marketers can use natural language processing to understand their customers in a better way and use those insights in creating effective strategies. The power of NLP equips them for analyzing topics, keywords, and making proper use of unstructured data. It can also be used to identify customers’ pain points and keep an eye on your competitors.
2. Sentiment Analysis – Humans have the gift of being sarcastic and ironic during conversations. With sentiment analysis in real time, you can monitor the mentions on social media and tackle them before they escalate. This application of NLP gives your company the power to sense the pulse of the customers. It also equips you to gauge the customer’s reaction to your latest digital marketing campaign. Sentiment analysis can be done by companies on a periodic basis to understand the deeper aspects of the business.
3. Hiring and Recruitment – We all will agree that the HR department performs one of the most crucial tasks for the company: by selecting the right employees. But in the present scenario, there is so much data available with HR, that filtering resumes and shortlisting the candidates becomes overwhelming.
With the help of Natural Language Processing, this task can be done more easily. HR professionals can use techniques like information extraction along with named entity recognition to extract information such as names, skills, locations, and educational backgrounds of the candidate, This also allows for unbiased filtering of resumes and selection of the right candidate for the desired role.
4. Text Summarization – This NLP application is used to summarize text by extracting the most important information. The main goal here is to reduce the process of going through vast amounts of data in news content, legal documentation, and scientific papers. There are 2 ways of using natural language processing for text summarization: extraction based, which extracts keyphrases and creates a summary without adding any extra information AND abstraction-based summarization, which paraphrases the original content to create new phrases.
5. Survey Analysis – Companies use surveys as an important means of evaluating their performance. Be it getting feedback on the latest product launch or getting to know about the performance of its customer service, survey analysis plays a huge role in understanding the loopholes and helping companies improve their products.
The problem arises when a lot of customers take these surveys leading to an exceptionally large data size. All of it cannot be comprehended by the human brain. That’s where natural language processing enters the canvas. These methods help the companies to get accurate information about customer’s opinions and improve their performance.
6. Targeted Advertising – Leads generation stays at the core of businesses. This is the main reason they want to reach out to the maximum number of audiences. Natural Language Processing is an amazing resource for placing the right advertisement, in the right place, at the right time. This is done through keyword analysis and browsing patterns of users over the internet, emails, or social media platforms. Text mining tools are leveraged to perform these tasks.
7. Neural Machine Translation – This is one of the oldest applications of NLP, which is relevant even in 2024. In this, a machine translation uses a neural network to translate low-impact content and speed up communication with its partners. A recurrent bidirectional network called an encoder processes a source sentence into vectors for another recurrent neural network called the decoder. This helps to predict words in the target language as we see in Google Translate.
8. Copywriting – The task that involves creativity and is done by keeping in mind the brand’s vision is now also possible, thanks to NLP. It is helping businesses grow by improving their content marketing strategy. This business world application of natural language processing makes use of the technology to write marketing content that aligns with the brand voice and also provides insights on particular messages that appealed to the target audience.
9. Email Filters – NLP makes use of a technique called text classification to filter emails. It refers to the process of classification of a piece of text into predefined categories. Examples of this include getting an incoming mail classified into primary, promotions, and social sections and also the classification of articles into different categories so that you can choose to read the material of your choice.
10. Grammar Check – Yes, this natural processing technique is here to stay. Tools like Grammarly provide tons of features in helping a person write better content. It is one of the most widely used applications of NLP that helps professionals in all job domains create better content. It is a boon for content writers, copywriters, and editors.
11. Voice Assistants – I am sure you’re all used to Siri, Alexa, or Google Assistant. All these voice assistants use speech recognition, natural language understanding, and processing to understand the verbal commands of the user and perform actions accordingly. From the time they were introduced to now, they have transformed into a very reliable gadget.
Check out the free course on nlp projects for beginners.
Endnote
These were the 11 Trending NLP Applications that we’re about to see grow. Looking at its growth trajectory, it will definitely be beneficial for you to understand NLP.
For this, you can pursue the Post Graduate Program in Artificial Intelligence: Business Applications, offered by the McCombs School of Business at The University of Texas at Austin and delivered by Great Learning. It is one of the best AI courses in the US that uniquely combines a wholesome curriculum and covers the most widely used tools and techniques in the industry.
The University of Texas at Austin is one of the top universities in the US for masters in artificial intelligence. An artificial intelligence masters in the US from this university adds more integrity to your CV. You can also download the free career guide that carries trends, global salary insights, and much more information about the AI industry. From introducing you to this field, sharing its applications, to the industry insights: this career guide is a short handy ebook to give you an idea about what it takes to be in the field of AI.
Hope you liked the article. Let us know about the applications you are most interested in the comments section.
