Natural Language Processing (NLP) Applications in Business

Natural Language Processing (NLP) is one of the most revolutionary fields of artificial intelligence (AI). NLP gives machines the ability to extract meaning from human languages and make decisions based on this data. In other words, NLP helps computers communicate with humans in their own language.

NLP technologies have dramatically evolved over the past decades and have become an essential part of our daily lives. I guess each of us has at least once used Google Translate, autocorrect or autocomplete. The spam filter on your email system also employs NLP to identify what emails you want to keep in your inbox and what are spam. These are just a few examples, and there are a lot of other incredible ways natural language processing is used today.

Natural Language Processing technology is especially valuable for businesses. A number of companies have already taken advantage of NLP services from Unicsoft to gain a competitive edge over their rivals. Firstly, this technology helps derive understanding from the multiple unstructured data available online and in call logs. Next, since businesses feel the constant need for enhancing the communication process with their customers, NLP tools are the best way to improve the quality of this interaction. Application of NLP can be found in a range of business contexts, including e-commerce, healthcare and advertising. Here are the top NLP use cases in business.

#1 Machine Translation

Being one of the most frequently used NPL applications, machine translation enables automatic translation with no need for human involvement. MT is super useful in business since it facilitates communication, enables companies to reach broader audiences, understand foreign regulatory documents and emails in a quick and cost-efficient way.

#2 Social Media Monitoring

Today, social media plays one of the key roles in developing relationships between businesses and consumers, providing an unrivalled opportunity to establish customer service by gathering input, answering questions and collecting feedback. To leverage their presence on social media, companies widely employ social media monitoring tools that are basically built using NLP technology. NLP helps you monitor social media channels for mentions of your brand, and notify you about it. The NLP technology is crucial when you need to prevent negative reviews from ruining your reputation and immediately react to any potential crises.

#3 Sentiment Analysis

Fair enough, understanding a human language is sometimes a tough job when it comes to opinions and emotions. But it’s not a problem for the cutting-edge sentiment analysis, or opinion mining. Sentiment Analysis is an NLP technique used to interpret and classify emotions in subjective data. In other words, it is able to detect positive or negative sentiment in text. You might want to use sentiment analysis to track mentions on social media and handle hostile comments before they go viral, examine customer reactions to your products, and get a thorough understanding of how consumers feel about your brand.

#4 Chatbots and Virtual Assistants

Another outstanding NLP use cases are chatbots and virtual assistants. These applications are utilized for automatic question answering. Chatbots and virtual assistants are designed to understand human language and produce appropriate responses. What is even more impressive, AI-powered chatbots and virtual assistants learn from each interaction and improve over time. It’s a no-brainer that these applications are super helpful for businesses. Available 24/7, they essentially accelerate response times, handling the greater part of the queries and leaving only the most difficult issues to human agents.

#5 Text analysis

By analysing texts and deriving various types of elements from them, like people, dates, locations etc., businesses can spot useful patterns and obtain valuable insights. This undoubtedly facilitates more efficient decision-making and developing strategies that respond to customer demands.

For example, online stores can use NLP-driven tools to perform text analysis of their product reviews to find out what their consumers like or dislike about their goods, and even more useful information.

#6 Speech Recognition

Speech recognition technology employs NLP to transform spoken language into a machine-readable format enabling applications and devices to respond to spoken commands. Speech recognition is an essential component of virtual assistants, like Siri or Alexa. This tech is disrupting businesses as well. To start with, it can enormously boost business productivity: it’s much easier to multitask using your voice instead of your keyboard, and convert your spoken words into text documents. In addition, NLP enables companies to automatically transcribe calls, send emails, and translate. And it’s not only about your office: for instance, if you’re a retailer, speech recognition can streamline shopping for your customers and add value to your business.

#7 Text Extraction

Text extraction, or information extraction, is an NLP-driven system that automatically locates specific data in a text. Also, it can extract keywords from a text, as well as specific features, for instance, product serial numbers.

Coupled with sentiment analysis, keyword extraction can give you understanding which words the consumers most frequently use in negative reviews, making it easier to detect them.

#8 Autocorrect, Spell Check and Even More

These NLP-driven functions are commonly found in word processors and text editing interfaces. Autocorrect identifies misspellings and automatically replaces them with the closest possible correct terms. Spell check works in a similar way, the difference is that the spell check relies on a dictionary while autocorrect depends on the pre-entered terms.

However, NLP technologies have gone even further than autocorrect and spell check. The cutting-edge NPL-driven writing tools are able to identify grammar mistakes and give you suggestions concerning the style of your writing. All in all, they allow for quick, clear and efficient communication, which is quite essential for businesses today.

To Wrap it Up

In a nutshell, businesses are using NLP to better understand customer intent through sentiment analysis, yield crucial insight from unstructured data, facilitate communication and improve the overall performance. The NLP technology can process language-based data faster than humans, without getting tired. Undoubtedly, we can expect that Natural Language Processing will become even more influential for business in the near future.

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