The ability of a computer software program to comprehend spoken or written human language is known as natural language processing or NLP. It has been used for over 50 years, is based on deep learning, and allows computers to comprehend user inputs. It is an application of artificial intelligence that effectively processes enormous amounts of natural language by computers.
How does NLP work?
NLP gathers user input and uses AI to translate it into terms the machine can comprehend. Human language is broken up into smaller pieces to understand and analyze the grammatical structure and meaning of words.
Texts are converted using text vectorization into a machine-understandable format. After transforming the text, the input and output associations are created using machine learning methods.
Two main phases of NLP
Natural language processing is divided into two primary stages, which are
Data pre-processing: For the computer to comprehend the grammar and meaning of the words, human language is fragmented and segregated into smaller chunks. Data processing involves several tasks, including:
- Texts are tokenized by being divided up into smaller semantic clauses.
- Identifying words as nouns, adjectives, adverbs, and other parts of speech.
- Lemmatization and stemming: Getting words back to their basic structure.
- Stop words are words that contribute little to no information and are removed.
Development of the algorithm: After the data has been analyzed, we must create and train the algorithm to comprehend plain language and carry out the necessary duties. The two most popular NLP algorithms are the following:
- The rule-based technique, which depends on manually written grammatical rules and requires the assistance of linguistic experts and knowledge engineers, was the first approach to NLP algorithms.
- Algorithms for machine learning The training data is used to train machine learning models, which depend solely on statistics. The primary benefit of employing machine learning algorithms is their capacity for self-learning. The algorithm leverages previous data to create predictions, allowing for greater flexibility because no manual rules need to be defined.
Advantages of NLP(Natural Language Processing) Chatbots
- They are highly accurate and hence reduce the false positivity rate.
- Offers solutions by resolving conflicts and identifies failures in the input through statistical modeling.
- Uses comprehensive communication when dealing with customer responses.
- Can learn faster and address the issues observed while developing a solution.
- It can achieve natural language understanding and capability through lesser training data inputs.
- Re-use training data for future purposes.
- False positives are corrected through straightforward corrective measures.
What are NLP chatbots?
The concept of deep learning is the foundation of NLP, or natural language processing, which enables bots to extract meaning from the input. The NLP chatbot uses feedback to analyze the customer's genuine question and determine how best to provide more helpful individualized assistance.
The main benefit of using the NLP chatbot is that you can ask queries in various ways rather than just using the provided keywords. Businesses can educate their chatbot powered by AI to comprehend a variety of inquiries. These are customer-submitted inquiries, giving a system a wider base to access the queries efficiently.
Some NLP(Natural Language Processing) based Chatbots.
- BotPenguin: It is an AI-powered NLP chatbot platform that helps you build incredible chatbots to communicate and engage with your customers. It is one of the best NLP chatbots in the market, providing excellent solutions to your customer management problems. It offers a lead generation chatbot, customer service, assistant chatbot, and order booking chatbot. Bot penguin can cater to small as well as large businesses.
- Chatfuel: It is a great NLP chatbot because of how easy it is to get started and because it offers some rudimentary NLP you can leverage with a bot. It is most suitable for small to medium companies just starting.
- DialogFlow: It has a voice-enabled Google Home product line. It is relatively easy to use, and most of its interface is point-and-click. Although it is not as intuitive as Bot penguin or Chatfuel, it is a great option for those with zero coding abilities. Most suitable for organizations looking to use the Google Home ecosystem.
Need for NLP(Natural Language Processing) Chatbots
Natural conversation across languages
There are infinite variations in which Y can express a specific statement in many different languages. There are so many different ways to express an emotion. NLP enables us to make a connection between incoming information and the response that the system generates.
NLP can understand language semantics, speech phrases, and text structures. Therefore, it enables us to analyze a large amount of data. NLP also allows the chatbot to interpret and understand various emotions through sentiment analysis.
Focus on mission-critical tasks
NLP-based chatbots help reduce human efforts in manual tasks such as invoice processing or customer service, reducing the required resources and increasing employee efficiency. It helps the employees to focus on the important tasks in a far more creative manner.
Reduced Cost
NLP chatbots can help businesses cut down costs associated with manpower significantly while increasing customer retention and improving efficiency, and streamlining workflows.
Higher Customer Satisfaction
NLP chatbots understand, analyze and prioritize the questions according to their complexity and enable bots to respond faster than a human response. Faster responses help in building customer trust and loyalty. The chatbot can solve almost 60-90% of all chat issues without involving any human agent.
Chatbots can answer over 100 questions, while a human service advisor can only answer one.
Market Research and Analysis
You can generate a lot of versatile and unstructured content from social media. NLP helps structure this data and makes it easy to understand the idea behind the customer reviews, comments, inputs, or queries.
Automatically Analyze Customer Feedback
Customer feedback is essential to know what your customers think about your product. However, this data is hard to process. NLP helps you leverage the data collected from the chatbot survey and help you get the required insights to improve the business.
Future of NLP(Natural Language Processing) Chatbots
Conversational AI
Conversational AI is on the rise. The global market has a compounded annual growth rate of 22% from 2020 through 2025. It is expected to be higher in the 2030s. Conversational AI will expand the capabilities of NLP chatbots and make sophisticated conversational versions more affordable.
New Applications
NLP chatbots are well known for their use in the customer service industry. With the advancements in AI, they are expected to become more and more popular in human resource departments. They may also become popular in employee training, IT help, and administrative assistance departments.
Growth through social media
Social media plays an important role in increasing consumer awareness of NLP chatbots. It featured over 100,000 bots in Facebook's Messenger app in 2017. Some NLP chatbots focus on customer service, but many are developed for simple, free-to-use varieties people talk to for fun.
Better Security
Cybersecurity in today's times is of extreme importance. Numerous cyber attacks are launched every day. These chatbots are not exempt from the threats of these attacks. NLP chatbots often collect personal information, and protecting this data is a priority. Consumers need to know that these devices are safe and do not have the risk of sensitive information leaking.
Greater Transparency
Consumers need to know that they can trust these NLP chatbots. They might be worried about their information leaking. Luckily, advancements in AI and NLP resolve the issue with transparency.
Are NLP chatbots worth it?
NLP chatbots provide an excellent tool for your business, and it helps you to reduce the human resources required, reducing the monetary requirements. The NLP chatbots can learn from previous interactions and cater to your customers better as they are available 24/7. Users today are focused on instant replies and immediate problem-solving. NLP chatbots help provide your customers with the exact needs and help create a happy customer experience. NLP chatbots are worth it and are a must to grow your business.
