Natural Language Processing (NLP) is one of the most potent advancements made by Artificial Intelligence (AI). NLP allows the AI to naturally process human language and make decisions based on the gathered data.
NLP technologies have evolved immensely over the years and are becoming part of our daily life routine. In some way, we are all using NLP, which is either Google Translate, autocorrect, or something else.
These were just some examples, but there’s more to find out. In this article, we will identify the NLP applications in business.
Let’s dive right in!
What are the NLP applications in business?
Social media monitoring
In today’s world, social media plays an important role in developing relationships between businesses and consumers by gathering feedback and input via customer service.
In order to leverage social media presence, most companies will use social media monitoring tools that use NLP technology. So, you may be wondering how does NLP work in the social media world?
NLP helps you better monitor social media channels and all the mentions for your brand and gives you continuous notifications about it. Overall, NLP technology is essential whenever you try to prevent any negative reviews that will ruin your business reputation and will immediately react to any crises.
Sentiment Analysis
Understanding natural language may be tricky for machines when considering opinions, claiming that humans will use irony and sarcasm. However, according to Phi Dang, sentiment analysis recognizes emotions and thoughts to determine how positive or negative they are.
Moreover, whenever you conduct real-time sentiment analysis, you can monitor all social media mentions, monitor customer reactions via your product launch or marketing campaign, and get an overall sense of how customers will feel about your brand.
Additionally, if you think it’s a better idea, you can try to perform sentiment analysis periodically and understand what customers prefer and don’t prefer about your business. Maybe, they are in love with your new features but unhappy about your customer service. Furthermore, these types of insights can allow you to make better business decisions and show you precisely what kind of things you would like to improve.
Social media sentiment analysis
Alternatively, you can also run social media sentiment analysis. NLP for social media is unique from the rest because it’s able to understand internet short language forms such as YOLO, LOL, YR, and more. Moreover, not only, but it also understands emojis, hashtags, emotions, and much more.
According to Henfield, no matter how your customers choose to speak with you, NLP allows you to extract information. For example, the social media sentiment analysis will give you a clear picture of whether your brand is receiving positive or negative reviews on social media. Thus, it gives you actionable insights into how you can perform on social media. Therefore, you can choose to reach out to influencers to help improve your marketing campaign, promote your product or service, increase your brand reputation, and much more.
Language translation
The web is full of information you can use, but one of the most common challenges individuals face is trying to understand another language. That’s why online translations have been a considerable advancement for researchers. Therefore, if translation weren’t possible, we wouldn’t be able to enjoy documentaries in another language, live streaming, or even general videos we would like to watch every day.
NLP technology has come a long way and provides speech-to-text translations faster than we expect. Every language is beautiful and unique, so being able to watch a video in another language and read subtitles to understand it is what makes everything attractive. Regarding language translation, NLP is continuously evolving in this case, so data scientists are constantly gathering new terms and phrases from actors to help improve NLP’s ability to better process language translations.
In NLP, we have Sentence Boundary Detection (SBD), which aims to understand the boundaries of all words. It’s an essential task in translation and is the primary reason you can translate texts into different languages. For example, we have Google Translate, one of the world’s most widely used platforms for translating into more than 100 languages. Besides that, you have many different platforms that can do the same.
However, let’s not forget that human languages are complex and still require machine translation to work much harder in understanding harder dialects. Above all, let’s not forget that many languages worldwide have many dialects and might have words that have other meanings. Hence, machine learning models need to gather more data regarding this.
Chatbots and virtual assistants
Another huge influencer regarding NLP is chatbots and virtual assistants. Chatbots and virtual assistants have the primary task: to answer questions that customers might ask whenever they visit your website or social media channel. Moreover, the best part about it is that chatbots are designed to understand human language and produce the type of responses they are looking for.
Even more interesting is that AI-powered bots and virtual assistants will learn more about you each time you interact. Undoubtedly, it’s not surprising that these businesses are helpful for most companies. Chatbots have a considerable advantage over humans because they can be at your service 24/7 without taking breaks. Above all, it’s best when we let them take care of the repetitive jobs because they never get tired of doing them, a huge weak point for humans!
Text extraction
In other words, information extraction detects certain information such as companies, places, names, and more. You can also call it entity recognition, where you can extract keywords within a text and pre-defined features such as product serial models and numbers.
Text extraction applications include surfing through support tickets to identify special information such as email addresses, order numbers, and more relevant information without opening up and reading every ticket.
Additionally, you can use text extraction for data entry purposes. Furthermore, you can pull out the type of information you need and automatically enter it into your database. However, keyword extraction can also give you an overview of text content and more. Keyword extraction can add extra insights by informing you of customers’ most common words to express negativity towards your product or service.
Automated trading
If you are in the finance industry, NLP applications can be used for automated trading purposes. Moreover, a person can define the program’s instructions such as price, time, and volume. Thus, when the share price is equivalent to the value specified, the program can execute directions and conduct the transaction.
Automated phone systems
Whenever you call a company and have to dial a number to reach someone through an automated phone system, it’s all thanks to NLP. Thanks to NLP, we also have computer-generated languages that sound similar to human voices. Nowadays, they say they are more robotic, but with the help of voice actors, this may change in the upcoming years. NLP can do this by using speech recognition and interactive voice response (IVR) whenever it interacts with you.
Above all, this is how it guides you through a transaction and gives you the option of choosing the languages you prefer. As a result, more companies choose to use NLP regarding customer interactions since it’s more cost-effective and predictable.
Autocorrect and spell checks
Have you ever used programs like Grammarly? Well, the way you can conduct auto-correct and undergo spellchecks is all thanks to NLP functions. Autocorrect is responsible for automatically correcting all of your mistakes and mis-spellings when you might make errors in a word or two.
Spell-check will inform you of the words you need to fix, depending on your pre-entered terms. Moreover, NLP technologies have entered a new level regarding spell check and autocorrect. The NPL-driven tools can identify grammatical errors and give suggestions whenever you need to identify any grammatical errors and need recommendations concerning your writing style. Above all, they give you a chance for effective communication and to improve your overall spelling while writing.
Wrapping everything up
That’s about it for this article. These are the top NLP applications within a business. NLP has brought innovations to our everyday lives and has changed how we function, write, and interact with our jobs. However, even though many may think AI has made it harder for people to find jobs, it has actually increased the level of assistance we are getting.
We have to be honest about one thing, and that is the fact that humans aren’t built for repetitive jobs and can’t work 24/7. Nevertheless, NLP has found mistakes we make in areas we might not have thought of.
