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8 natural language processing (NLP) examples you use every day

What is Natural Language Processing, or NLP in short? If you’re unsure, you’re not alone. Many people don’t know much about this fascinating technology, and yet we all use it daily. In fact, if you are reading this, you have used NLP today without realizing it.

What is NLP?

Natural Language Processing is what computers and smartphones use to understand our language, both spoken and written. Because we use language to interact with our devices, NLP became an integral part of our lives. NLP can be challenging to implement correctly, you can read more about that here, but when’s it’s successful it offers awesome benefits. 

Real-Life Examples of NLP

Here are eight examples of how NLP enhances your life, without you noticing it.

Faster Typing using NLP

Any time you type while composing a message or a search query, NLP helps you type faster.

1. Autocomplete suggests the rest of the word.

2. Predictive typing suggests the next word in the sentence.

what is natural language processing - autocomplete

Messengers, search engines and online forms use them simultaneously.

Accurate Writing using NLP

When you compose an email, a blog post, or any document in Word or Google Docs, NLP will help you to write more accurately:

3. Spell checkers remove misspellings, typos, or stylistically incorrect spellings (American/British).

4. Grammar checkers ensure you use punctuation correctly and alert if you use the wrong article or proposition.

A tool like Grammarly (I’m a fan!) uses both and explains why you need to make a correction:

Better Search using NLP

When you search on Google, many different NLP algorithms help you find things faster. Query and Document Understanding build the core of Google search. In layman’s terms, a Query is your search term and a Document is a web page. Because we write them using our language, NLP is essential in making search work. The beauty of NLP is that it all happens without your needing to know how it works.

5. Auto-correct finds the right search keywords if you misspelled something, or used a less common name.

6. Duplicate detection collates content re-published on multiple sites to display a variety of search results.

7. Spam detection removes pages that match search keywords but do not provide the actual search answers.

Here is an example of how Google News recognizes the misspelling “jon key”, and shows just one result on this topic from each news outlet. Note how “resigned” got matched to similar words “resignation” and “resigning”.

what is natural language processing - autocorrect

Productive Emailing using NLP

Email clients continuously defend you from spam. In fact, using NLP they differentiate between different types of emails that go beyond the classic spam filters:

8. Email classification is an essential feature of Gmail, which separates emails into Primary (your actual personal email), Social (notification from Facebook and the like) and Promotions (newsletters which we get subscribed to).

Natural Language Processing is Everywhere

As you can see, Natural Language Processing is ubiquitous, and it will only become more powerful and useful in the coming years. Virtual assistants like Microsoft’s Cortana and Amazon’s Alexa are becoming more popular. Businesses turn to chatbots for various user interactions. We will continue to generate more and more language, which will need analyzing.

Consumers are already benefiting from NLP, but businesses can too. For example, any company that collects customer feedback in free-form as complaints, social media posts or survey results like NPS, can use NLP to find actionable insights in this data. Although, it’s not as simple.

Here at Thematic, we use NLP to help customers identify recurring patterns in their client feedback data. We also score how positively or negatively customers feel, and surface ways to improve their overall experience.

Sky TV is using our software to understand their subscriber’s feedback and get actionable insights, especially relating to viewing experience and customer service satisfaction metrics. Applying our advanced Natural Language Processing algorithms to weekly survey data, Sky TV is able to understand how price increases impact customers and what they can do more of to increase customer retention — critical insights that have massive implications for product and overall business strategy.

If you’re currently collecting a lot of qualitative feedback, we’d love to help you glean actionable insights by applying NLP. Schedule a demo or start a free trial of Thematic.

Ready to scale customer insights from feedback?

Our experts will show you how Thematic works, what feedback data it analyzes and how to use feedback to make data-led decisions. To learn how you can make the most of Thematic, request a personal demo today.

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