10 NLP examples you use every day without realizing

Introduction

We use technology every day, and because it has become part of our routine, we don’t always realize how fascinating it really is. If Siri or Alexa has ever helped you, then you should know that the technology behind them is called NLP – Natural Language Processing. This is the technology that allows machines to understand and interact using human language. 

In this article, we will discuss 10 examples of NLP in our everyday lives that can be extremely useful not just in your personal life but also in your professional one. Let’s dig in!

• Smart assistants on everyday basis

Everyone has used a virtual assistant at least once: Siri, Alexa, Cortana, or Google Assistant. For them to understand your voice commands and help you with what you ask, they need to: 

– process your natural language

– extract essential information from what you communicate

– then perform the action you’ve requested.

All of this is possible with the help of NLP technology, which allows virtual assistants to understand the context and continuously learn based on previous conversations with you, thus providing personalized interactions.  

• Email filter applications

Email filters are among the first online NLP applications.  If you use Gmail, for example, you already know that your emails may end up in different inboxes, depending on the category they belong to: Social (social networks), Promotions (newsletters from the sites you subscribed to), or the main inbox (Primary), where you get the most important emails.

Spam filters also identify suspicious words or phrases that signal unwanted messages. Thanks to these algorithms, your inbox stays organized, and it’s easier for you to find important messages.

• Search engine results

Search engines like Google use advanced NLP technologies such as BERT and MUM to better understand your queries. So when you search for something on Google, NLP helps the search engine to: 

• understand the context
• understand the intention 
• deliver personalized results based on your search history.

Find out more about BERT and MUM below:

• Language translation applications

Most of us have used Google Translate or DeepL at least once. These applications use NLP to translate text from one language into another, analyzing grammatical structure and responding in a way that provides natural, human-like translations.

• Enhanced digital phone calls

You know when you call a customer service center and get redirected to the department responsible for solving your issue? NLP is used for exactly this purpose: to analyze your voice and identify certain words that tell the system which department to redirect you to. 

NLP can also provide agents with information about your needs. This considerably reduces time and therefore increases customer satisfaction.

For example, the Mayo Clinic has integrated NLP into voice assistants and chatbots to help patients access accurate medical information and respond to common symptoms with guided instructions.

• Product recommendations for e-commerce platforms

Have you ever browsed an online shop and been recommended products that matched your needs? This often happens because e-commerce platforms use NLP to analyze the product reviews offered, as well as your interaction with chatbots or search bars, helping them suggest more relevant products.

• Grammar and Spell Check

If you know you’re about to write an important article or a PhD thesis, you’ve probably turned on autocorrect or use Grammarly. NLP is behind these tools, and its role is to identify and correct errors in your texts, helping with:

– spell checking

– analyzing sentence structure

– analyzing punctuation

– identifying repetitions or topical errors

They can also suggest ways to improve your text, making it clearer and easier to understand, while continuously adapting to your writing style.

• Social Media Monitoring 

If you run a business that has multiple social media accounts, you already know how difficult it is to keep up with every comment or reaction to posts. That’s why platforms like HubSpot or SimilarWeb use NLP to monitor brands’ mentions across social media. These tools identify and categorize comments as positive or negative, extracting important insights about brand reputation. Thus, through these tools, you will be able to better understand your audience and respond more effectively to customer feedback.

• Customer relationship handling

Here we refer to CRM systems that integrate NLP in order to analyze customer interactions. These algorithms scan emails, identify the subject, and generate automatic responses to frequently asked questions. 

• Medical data analysis 

In the medical field, NLP analyzes patient data alongside scientific literature. This allows algorithms to extract relevant information from medical records, identify symptoms, and support clinical research.

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