Last Updated on March 28, 2024 12:50 AM IST
In the tech world, machine learning, artificial intelligence (AI) and Natural language processing (NLP) play a key role. However, the benefits of Natural Processing Language (NLP) are limitless. In simple terms, it is like a superpower to Artificial Intelligence (AI)
Many people believe that only engineers can use NLP. But we believe it is just a misconception.
Yes. Today, every one of us uses the internet and while using it you might use an NLP application. Popular search engines such as Google and Bing use NLP to result from the search requests.
Not only in search engines today, NLP technologies such as natural language understanding (NLU) and natural language generation (NLG) are also used in devices such as Siri and Alexa that use voice commands to function. And chatbots rely on NLP to deliver accurate responses to the end user’s queries. Let’s uncover the awesome benefits NLP brings to us!
Benefits of Natural Language Processing (NLP)
Natural Language Processing is a popular subset of artificial intelligence. Its linguistics is focused on making human communications such as text and speech more understandable to computers.
NLP is a process language that can be used in our everyday products and services. Some of the most common applications of NLP are Google Assistant and Apple’s Siri on smartphones, email-scanning programs and translation apps.
Today, even popular AI models such as ChatGPT and Gemini use Natural language processing to facilitate communication in real time.
However, advanced NLP techniques perform machine complex tasks without human intervention. It can generate text formats such as creative poems or code and even smartly answer your questions, just like having a conversation with a machine in human language.
This results in new solutions such as real-time dialogue systems, developing advanced-level chatbots and analysing emotions within the text data.
Perform Extensive Analysis
Natural Learning Processing allows you to perform extensive text analysis on a large scale. It can help you to analyze all types of documents, news articles, emails, social media data, online reviews and much more.
It will process significant amounts of data within a few seconds or minutes whereas doing it manually would have taken days or weeks.
Today, Accenture is using natural language processing for performing legal analytics. They have a project known as Accenture Legal Intelligent Contract Exploration (ALICE) which helps their legal team to search and understand millions of contracts.
ALICE can look at typical contract clauses by analyzing texts in the contracts. ALICE uses a technique called “word embedding” which helps in understanding the meanings and comparing them based on their similarities.
ALICE will go through the contract documents and search for keywords that indicate a certain contract clause. For example, it will search words like “flood”, and “earthquake”.
Improve Your Customer Experience
For any company, the customer plays a key role and improving the customer experience is crucial.
If not responding promptly to customer queries can lead to the company’s downfall. To avoid this, it is important to understand what and why customers are saying about your product and services.
Today, many NLP tools such as Simplify360 available that can help you respond quickly to customers.
Virtual assistants and chatbots are popular examples that help businesses to answer their customers automatically.
They can seamlessly respond to their customer queries and speed up their responsive time which will enhance the customer experience.
Streamlining Daily Process
Customer reviews on your services or products regularly help you to improve your business.
However, it is a challenging task for your employees to perform manual data analysis. And, the results aren’t as effective as compared to NLP tools results.
When you add NLP tools to your company data then you can quickly understand what your customers think about your products or services.
Hilton one of the renowned hotel chains reported a 20% increase in positive guest reviews after implementing NLP-powered feedback analysis.
This solution allowed them to solve the real time guest issues effectively and enhance their overall guest experience.
This helps your employees save time which will allow them to focus on enhancing their productivity.
Extracting Actionable Insights
While analysing surveys, social media conversations or online reviews you need to pay attention to the details because that’s where you will find the most valuable information.
But, going through intensive data can be challenging and time-consuming to get actionable insights from all the unstructured text (raw data).
But, AI-powered tools like Polymer can help you automate this process and help you to sort through the data.
This will help you identify the important details which will provide you with actionable insights quickly.
Gain More Objective and Accurate Analysis
Natural language processing can provide you with more objective and accurate analysis as compared to humans.
Humans can make mistakes while performing repetitive tasks such as reading, and analyzing surveys along with other text data.
But NLP tools can be customized especially depending upon your business needs and criteria that make them and their results better than humans.
And, you can also update and improve these tools and models as your business grows.
Better Market Understanding
Natural language processing has a huge impact on marketing. By, using NLP you can understand how your customers talk and you will have a better understanding of the market.
This will allow you to divide your market into groups and target customers directly.
Multilingual Support and Accurate Translation
Natural language processing helps businesses to perform language translation and helps to communicate in multiple languages effectively.
It uses several algorithms to analyze and understand different languages that ensure accurate translations.
This capability saves time and resources lets businesses reach the global market effectively and improves communication across diverse audiences.
Saves Time and Money
Natural language processing helps businesses save time and money. According to Chatbots Magzine using chatbots can lower customer service costs by up to 30%. This will reduce the stress on employees and allow them to focus on important tasks.
Over time and data, these large language models can be improved and get better at answering questions and handling complex situations. This will save operational costs which will be beneficial for businesses.
Top 3 Use Cases of Natural Language Processing
Natural language processing helps business operations across various industries. Here, are the top 3 use cases of NLP in various sectors.
Banking and Finance
Banking and financial institutions use sentiment analysis to analyse market data. One of the popular examples is the Credgenics sentiment analysis tool. It uses speech recognition and analysis over bots to generate insights about borrowers.
They can use their insight to minimize risks and make precise decisions. NLP can help these institutions to stop fraudulent activities such as money laundering and much more.
Marketing and Advertising
Natural language processing can help collect and analyse social media posts. This will help them to categorize the sentiments such as positive, negative or neutral.
This analysis helps marketers to understand the brand sentiments, monitor campaigns and make better decisions for better customer engagement and satisfaction.
Human Resources
NLP in human resources can help streamline the recruitment process. Its deep learning algorithms can automatically analyze resumes, and screen and match candidates based on qualifications, skills and experience.
This saves HR professionals time and identifies top-notch candidates effectively for the organizations. Thus, it improves the overall recruitment experience.
It can also help to perform employee feedback analysis, performance evaluations and personalised learning experiences within the organizations. This leads to better employee engagement and retention.
Summing Up
Natural Language Processing is emerging as a valuable asset for businesses, providing time and cost savings, process optimisation, and informed decision-making.
Being user-friendly NLP’s are no longer limited to engineers and computer science; anyone from any field can take advantage of its capabilities.
Businesses can use it to automate tasks, gain actionable insights from data, improve customer support, and expand their reach in global markets.
The ease of implementation and transformative impact of NLP systems improve efficiency, productivity, and competitiveness in today’s dynamic business environment.
In conclusion, Natural Language Processing (NLP) provides numerous benefits that can significantly improve business operations in 2024 and beyond.
FAQs related to natural language processing (NLP)
What is NLP in prompt engineering?
Prompt engineering is a technique used in natural language processing. It is a branch of artificial intelligence where users’ text describes what AI should do. After taking the input, the AI will generate an output on the screen.
Click here to learn and download our prompt engineering cheat sheet
Are there any privacy concerns with NLP?
Privacy is a major concern in Natural Language Processing (NLP). It is because these language models gather sensitive personal, financial and health data. Thus, any security breach can harm people. Therefore it is important to use data encryption, secure storage and access controls that protect data from unauthorized users or misuse.
Francesca Rossi, the President of the Association for the Advancement of Artificial Intelligence (AAAI) Advancement of Artificial Intelligence states: “The responsible development and deployment of NLP is crucial. We need to ensure fairness, transparency, and accountability in these systems to avoid bias and unintended consequences”.
Are there any rules for using NLP in businesses?
Yes. There are several sets of rules and guidelines for using Natural language processing in businesses. For example, in the EU General Data Protection Regulation (GDPR) regulates how personal data is processed by NLP and how it should be handled and protected. Following these rules ensures that businesses use NLP ethically and legally.
