Top NLP Examples that Reshape Businesses with the Power of Automation

Considering natural language processing as modern technology could be wrong, especially when it constantly transforms lives at every turn. From predictive text to sentiment analysis, examples of NLP are significantly far-ranging.

NLP solutions can be a boon for companies, saving time on cumbersome tasks and cutting overhead expenses to a large extent. By leveraging NLP in business, you can considerably improve your operational efficiency, product performance, and, eventually, your profit margins.

This informational piece will walk you through natural language processing in depth, highlighting how businesses can utilize the potential of this technology. Besides, it will also discuss some of the notable NLP examples that optimize business processes.

What Are Some Popular NLP Examples to Consider?

The emerging role of AI in business has widened the scope for its subsets, as well. This is one of the reasons why examples of natural language processing have evolved drastically over time. Below are some of the prominent NLP examples that companies can integrate into their business processes for enhanced results and productive growth.

Language Translation

One of the first and widely used natural language programming examples is language translation. Today, digital translation companies provide language translation services that can easily interpret data without grammatical errors.

However, that wasn’t the case a few years back. For instance, Google Translate used to translate word-to-word in its early years of translation. Users can’t completely trust it to translate long, whole sentences.

But with natural language processing algorithms blended with deep learning capabilities, businesses can now make highly accurate and grammatically correct translations for most global languages.

Smart Assistants

Smart assistants such as Apple’s Siri, Amazon’s Alexa, or Google Assistant use voice recognition mechanisms to infer meanings and understand everyday queries. After understanding the context of queries, they leverage natural language generation, one of the subsets of NLP to answer them.

Source: Apple

As one of the prominent NLP examples, smart assistants are now being trained to help consumers with more tasks than just one-way answers. NLP-based smart assistants can:

• Create and edit shopping lists for users
• Order items and finalize purchases based on commands
• Recommend products to consumers as per their preferences

Customer Service Automation

Customer support and services can become expensive for businesses during the time they scale and expand. In such cases, the role of enterprise chatbots seems notable. However, chatbots are not the only way to handle this situation.

Certain types of NLP applications can be used to curb this issue. For instance, sentiment analysis can help identify the sender’s views, context, and main keywords in an email. With this process, an automated response can be shared with the concerned consumer. If not, the email can be shared with the relevant teams to resolve the issues promptly.

Enhanced Search Engine Results

Gone are the days when search engines preferred only keywords to provide users with specific search results. Today, even search engines analyze the user’s intent through natural language processing algorithms to share the information they desire. 

Search autocomplete can be considered one of the notable NLP examples in a search engine. This function analyzes past user behavior and entries and predicts what one might be searching for, so they can simply click on it and save themselves the hassle of typing it out. 

Smart search is also one of the popular NLP use cases that can be incorporated into e-commerce search functions. This tool focuses on customer intentions every time they interact and then provides them with related results.

Survey Analytics

When you create and initiate a survey, be it for your consumers, employees, or any other target groups, you need point-to-point, data-driven insights from the results. This can be a complex task when the datasets are enormous as they become difficult to analyze.

That’s when NLP examples come in handy. Its major techniques, such as feedback analysis and sentiment analysis can scan the data to derive the emotional context. 

Social Media Monitoring

Social media has become an active part of almost everyone’s lives. Businesses get to know a lot about their consumers through their social media activities. But again, keeping track of countless threads and pulling them together to form meaningful insights can be a daunting task.

The solution? Using social media monitoring powered by NLP solutions can easily filter the overwhelming number of user responses. These NLP tools can also utilize the potential of sentiment analysis to spot users’ feelings and notify businesses about specific trends and patterns.

Why Should Businesses Leverage Natural Language Processing?

The right interaction with the audience is the driving force behind the success of any business. In any business, be it a big brand or a brick-and-mortar store with inventory, both companies and customers communicate before, during, and after the sale. 

It brings numerous opportunities for natural language processing to improve how a company should operate. You can monitor, facilitate, and analyze thousands of customer interactions using NLP in business to improve products and customer services.

Statistically speaking, the global NLP market is moving at an unprecedented rate. It is expected that the market revenue growth will be 3.5 times larger in the next two years than it was in 2020.

In fact, as per IBM’s Global AI Adoption Index, over 52% of businesses are leveraging specific NLP examples to improve their customer experience.

What Are the Advantages of Natural Language Processing in Business?

From deriving business insights through sentiment analysis to quickly translating text from one language to another, there are numerous benefits of natural language processing for businesses.

Data Analysis

By leveraging NLP examples, businesses can easily analyze data, both structured and unstructured, such as text messages, voice notes, speech, or social media posts.

Enhanced Customer Experience

With sentiment analysis, businesses can extract and utilize actionable insights to improve customer experience and satisfaction levels.

Reduced Costs

NLP-powered AI assistants can be employed to perform certain customer service-related tasks. This saves both time and money.

Better Market Understanding

Using natural language processing algorithms, businesses can analyze and understand the target market, aiding them in preparing better marketing strategies.

How Can Businesses Make the Best Use of NLP Examples?

There are several ways in which businesses can use the popular examples of natural language processing. Some of them are:

To Automate Support

Chatbots have become one of the most imperative parts of any website or mobile app and incorporating NLP into them can significantly improve their useability. Companies often integrate chatbots powered with NLP for business transformation, lessening the need to enroll more staff for customer services. 

Auto Desk, Inc., an American multinational software and 3D computer-aided design company, extended its working hours to 24/7/365 without hiring additional staff for the same. All credit goes to NLP-powered chatbots that simulate human-like conversations across various communication channels.

To Improve User Experience

Businesses can use natural language processing to deliver a user-friendly experience. The NLP-integrated features such as autocomplete and autocorrect located in search bars can aid users in getting information in a few clicks.

Google’s search engine leverages NLP algorithms to comprehensively understand users’ search queries and offer relevant results to them. Such NLP examples make navigation easy and convenient for users, increasing user experience and satisfaction.

To Monitor and Analyze Reviews

Businesses often get reviews and feedback from social media channels, contact forms, and direct mailing. However, many of them still lack the skills to carefully monitor and analyze them for better insights.

Using NLP can help in gathering the information, making sense of each feedback, and then turning them into valuable insights. This will not just help users but also improve the services provided by the company.

How Can Appventurez Help You with Using NLP for Business Transformation?

The tech landscape is changing at a rapid pace and in order to keep up with the market trends, it’s important to harness the potential of AI development services.

However, as you embark on the transformative journey focused on more personalized services, it becomes imperative to adopt natural language processing for your business. All you need is a professional NLP services provider that helps you excel in the competitive technological landscape.

Appventurez is an experienced and highly proficient NLP development company that leverages widely used NLP examples and helps you establish a thriving business. With our cutting-edge AI tools and NLP techniques, we can aid you in staying ahead of the curve.