Recently updated on October 25th, 2022 at 11:00 am
The machine is learning, and NLP is proof. A few years back, the machine would have asked for full sentences or phrases that made sense. Anything that didn’t come in a phrase form was considered gibberish. But not anymore! The machine understands your language, and AI gives a significant part of the credit.
Natural Language Processing, a subset of AI, is doing wonders in making linguistics core to machine intelligence. The revenue generated from the NLP market is estimated to reach $43 billion approximately in 2025. This technology replicates the intelligence, problem-solving capability, and understanding of the human mind.
Being a leading mobile app development company, we have performed an in-depth analysis of the NLP concept and how it makes mobile apps smarter. Let’s walk you through the meaning of Natural Language Processing.
What is Natural Language Processing?
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Natural Language Processing is the machine’s ability to decode language as it is spoken or written by humans. It is often referred to as the machine’s ability to interpret natural language.
For this purpose, AI uses real-world language as input and analyzes it to help the machines create patterns and sets around it. They use computer audio and programs to understand human language.
For example, Alexa and Siri have been studying the human language, and are able to hold conversations with people using voice commands.
Many businesses are considering NLP for their mobile app, as it can interact with customers naturally and convert faster. Here, we will take you through how NLP makes mobile apps intelligent.
How NLP Makes Mobile Apps Smarter?
Here are all the use cases that showcase how NLP can make mobile apps smarter.
1. Offers Accurate Information in Milliseconds
Imagine asking Alexa about a specific case study from the past while trying to write a paper for your next assignment. You are conversing with Alexa, and she is answering your questions more accurately.
That’s how voice assistants can help in offering information in real-time to help meet your immediate needs. This kind of information engine can help healthcare specialists, bankers, and even legal assistants gain knowledge that can help them with the current case.
This will help them make a guided decision, which will eventually help them with success.
2. Log or Record the Details
A lot of users tend to move out of an application owing to the trouble that occurs when you start entering the data onto a small screen.
For example, the healthcare industry is battling staffing issues globally. Many people struggle to accomplish the admin tasks while ensuring proper treatment. With NLP in your mobile app, it can become an assistant to the healthcare provider.
Eventually, the provider can log the details without spending much time on them. They can dictate the details, and the app with NLP will get it filled in the right places.
This is also helpful during surgery. The surgeon is supposed to log the findings and make sure they have mentioned everything about the surgery in the log. However, it can become tedious, which is why assistants can be helpful in healthcare.
The surgeons can dictate the findings and results in real-time, while the machine records the same. This is just an example of how it is used in the healthcare industry.
You can replicate this in other industries as well. You can use this in your application to help fill out the details when needed. It will ensure quicker checkouts, faster processing, and better experiences.
3. Filter out Spam
Whether it is your messaging app or your email, the spam filtering capability of NLP allows you to differentiate between spam and other regular messages. This will ensure that you don’t have to go through messages that hold no meaning for you.
You can even use this to block out spam messages through your social media feed.
4. Helps to Know Your Customers Better
As a business owner, your primary concern is your customers’ sentiment toward your brand. However, despite social listening, you cannot judge what they feel. That’s where NLP helps.
You can use it to analyze the user’s sentiment, thoughts, and perceptions. You can use this to build your strategies and improve acquisitions. This will help you plan the user experience design, and interface to meet the user’s needs and sentiments.
Conclusion
With NLP at the fore, you can research the market better and analyze it to know what your customers think about your brand. It helps deep dive into content and information to find the best fit for your requirement.
For marketers, it is a gateway to creating great content. With NLP, you can add features, promote in-app capabilities and enhance usability that will encourage engagement. It’s time to plan NLP in your next mobile app.
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