What is NLP?

NLP represents Natural Language Processing(NLP) . It is a branch of artificial intelligence and computer science. This technology teaches computers to analyze and understand human language. It is the function of a machine to process human language in an automated way, analyze the questions and queries and respond just like a human.  

NLP has come as a breakthrough language that is developing every day and has come a long way. It is used in both large-scale and small-scale companies.  Companies use this to analyze unstructured data from human speech. It interprets human language and the author’s intent by evaluating everything from phone call recording to text messages from chatbots. It enables the company to reveal hidden operational data and trends, discover quicker product and service solutions, and facilitate maximize business performance.

How are NLP solutions applied in business?

• Automated translation

One of the most used applications of natural language processing is the automatic translation between two languages, for example, with Google Translate. The text provided by the translation is becoming more and more accurate and can even serve in court cases. Thus, machine translation is one of the first successful applications of deep learning in the field of NLP.

• Chatbots

Automated interactions with customers have significantly increased user experience and satisfaction. For example, 88% of customers have no issue paying more for an overall better customer experience on the website. A good example of chatbots that improve the customer experience is seen in Amtrak, an American rail company. The company hired Julie, an automated NIP chatbot that can help passengers find a convenient way to travel. As a result, it achieved an 800% return on investment, reduced customer service costs by around $ 1 million per year, and increased bookings by around 25% compared to earlier stats. 

• Speech recognition

The market for voice assistants is growing at full tilt; companies like Apple, Samsung, Google, and Amazon have developed voice assistants for mobile devices, home appliances, and televisions. The voice is becoming a new interface for computer-human interaction. The interface is designed to control machines in industries, especially when employees’ hands are busy. Speech recognition using NIP solutions is getting smarter day by day and giving users a better overall experience. As assistants learn more about the speaker’s intentions, they provide more precise answers to complex questions.

• Sentiment analysis

Sentiment analysis is widely used in online and social media monitoring because it allows companies to obtain a wide range of public opinions about the organization and its services. The ability to extract information from text and emoji on social media is a widely adopted practice by organizations worldwide. NLP shows a favorable side to emotion-focused sentiment analysis. With the help of NLP, companies can better understand their customers to improve their experience, which will help companies change their position in the market.

• Natural language generation

In addition to understanding text, machines are getting better at delivering new text. For example, in business, natural language generation gives more educated and humane answers to common questions. Therefore, it is ironic that compared to today’s trigger-based solutions, automating traditional communications will make them more personalized and user-friendly.

• Text analytics

NLP tools can analyze long and complex texts. The same applies to the studying of unstructured data owned by email or other companies. The case of text analysis is an automatic question answering function generated by Google. Its purpose is to provide search results for a specific query and provide a complete answer to the user’s needs, including a link to the quoted website and a description. 

NLP in Sales

NLP is a framework that explains how people unconsciously produce real-life results through thought, language, and feelings. NLP sales involve using specific phrases, strategies, and behaviors to play a role in the system and skillfully shape how potential customers feel about the product.

Techniques used in sales: 

• Being Mindful of Your Body Language
• Active Listening
• Expressing and Promoting Positivity
• Mirroring Your Prospect

NLP in Communication

One of the biggest problems professionals face when working with new clients or colleagues is overcoming different communication methods. NLP comes here as a savior. It helps to focus on your customer’s preferred representative system and communicate accordingly. For example, visual learners will find diagrams and tests attractive, while auditory learners will hear a strong argument speak with conviction. NIP will help you speak your client’s language. 

Benefits of NLP in business

• Reducing Bureaucracy, Administrative Work

Form filling, data entry, and other mundane management tasks require human resources, money, and time. Transferring these responsibilities to AI allows companies to save these costs and employees’ labor to do work that requires human attention.

• Cutting The Supply Curve, Improving Product Offerings

There is always some extent of mismanagement while dealing with large supply chains. Allocating materials to the most usable places and purchasing the most logical inventory is almost impossible because there are so many moving parts in the supply chain to follow.

Virtually impossible for a human. Knowing that things can be done better is often frustrating. But by giving an A.I. when the supply line dominates, the result will naturally be transformed into higher-quality goods at a lower cost so that the company has room to create more complex products for customers.

• Optimizing Internal Operations

Many organizations want to know whether they have made the best decisions in terms of sales, product development, customers, service, etc. 

However, as mentioned above, through NLP data analysis, these suspicions can ultimately be confirmed. The system will scan unstructured data and find the exact area that caused the operation failure.

• Offer immediate customer service.

Chatbots use NLP technology to help their customers get an answer to any question immediately, regardless of the time of the day or the day of the week. 

Suppose the query is focused on the same topic. In that case, the chatbot can use predefined responses to prevent customers from waiting for the response from the service desk because the chatbot plays the role of the customer service supervisor. They can even provide specific assistance such as sharing instructions links, booking services, or finding specific products. In fact, the possibilities are endless, and it all depends on the business needs of the relevant company. They will even convert potential customers into customers through very considerate services, or when visitors encounter problems, you will quickly find solutions to prevent them from turning to competitors.

• Moderate user-generated content

You can use this technology to apply spam filters and block spam content on websites and emails. In addition, NLP allows you to review user-generated content posted by readers, allowing you to maintain forum quality while avoiding disputes, unsolicited advertisements, or backlinks to malicious websites, and the role of such solutions is also to detect “prohibitions” “Vulgar words.” 

• Increase employee satisfaction

AI-based solutions are designed to handle everyday, mundane or time-consuming tasks like:

• Answer repetitive questions 
• Review comments 
• Act as customer support
• Monitor the references and products
• Scan keywords in documents and filter them
• Categorize emails
• Spell checker

This will not only make your employees happier. It will help them be more efficient, and it will give them time to focus on what they like. In turn, you will see a spike in employee satisfaction, increased employee engagement.

Potential of NLP technology

NLP technology provides numerous chances and opportunities for every company in multiple industries and market segments. In addition to the relatively intuitive methods that utilize NLP (like document processing and chatbots), many other applications are there, including real-time social platforms analysis and supporting investigation work or news. 

 NLP model can be used to improve and enhance existing solutions, from supporting and backing reinforcement learning models behind self-driving cars by providing more accurate signal recognition, expanding to study and evaluate headlines, and providing better event-based forecasts to enhance demand forecasting Tools. 

Since natural language technology is one of the best options for the transformation of information between machines and humans, the applications that NLP builds will only grow at a great rate in the near future, and business processes in the world will also grow quickly.

Challenges of Natural Learning Technology 

As a young technology, it still has many hurdles in its way. The biggest challenge with NLP is the difference between a machine that mimics text understanding and a machine that truly understands it. Context and intention are essential to analyze the text. The challenges faced by NLP in business have further increased due to the multiple cultural and social norms in communication. The best way to meet this challenge is to provide a multidimensional vector-based word mapping that provides complex information about the words they represent. The turning point of neural NLP in business appeared in 2013 when the famous word2vec model was introduced. However, one of the main problems that word2vec cannot solve is the homophone because the model failed to distinguish different meanings of the same word.