What is Natural Language Processing?
You probably already use a form of Natural Language Processing, or NLP, and may not even realize it. If you use a voice assistant, auto correct, or a search engine, you use NLP. At its most basic level, Natural Language Processing enables the processing and interpretation of human language.
NLP is an integral piece to the puzzle of easy-to-use and smart chatbots. An NLP based chatbot allows users to have an actual conversation with a chatbot. This stops from limiting users to a set of pre-defined options.
Based on machine learning, NLP assesses the intent of the user to create a response that is based on context. This makes responses more natural and humanlike. For example, when a user reaches out for technical support through your chatbot, the questions and descriptions can be confusing. Customers may not know or use the right terms. With a simple chatbot that utilizes canned responses based on keywords, the user will experience a level of frustration. A chatbot would not understand the intent. Meaning they would possibly respond with information and answers that are not relevant to the user’s problem.
Alternatively, a Natural Language Processing based chatbot can be trained. Developers and techs can use NLP so that multiple examples of the same situation can be assessed and interpreted. Training the bots uses Machine Language, which naturally leads to continuous learning for NLP and natural language generation (NLG). Because of deep learning, an NLP based chatbot will get better at analyzing intent with every interaction.
Why Your Chatbot Needs Natural Language Processing
While chatbots are used for a variety of reasons, like frequently asked questions (FAQ), inside sales qualification, virtual assistants, and many more. Those chatbots without Natural Language Processing solely rely on predetermined responses and information or human intervention. Without NLP, intent, emotion, and sentiment are often missed.
So, why does your chatbot need NLP?
- Research and Analysis
- Higher Customer Satisfaction
- Free Your Team to Do More
- Reduce Overall Costs
How does NLP help with research and analysis?
Natural Language Processing can analyze a large and versatile amount of content from a variety of sources. Once analyzed, you can get a feel for how your audience perceives your service or product. Ultimately, you get a deeper understanding of the meaning or intent behind content like reviews, comments, and questions.
Higher Customer Satisfaction Because of Natural Language Processing
Your audience demands instant results – thank you same-day delivery. Unfortunately, humans can’t always give an instant solution. This is where NLP empowers chatbots to analyze, assess, and respond to questions and comments faster than any human being. This speed creates a happier user. Did you know that the average American will spend 43 days on hold over their lifetime? At that rate, customer service has gotten a bad reputation. The longer the user waits, the more frustrated they will be.
Conversely, deploying a Natural Language Processing based chatbot helps increase customer satisfaction and customer retention rates. NLP allows for quicker response times. When your users and customers feel good about their helpful and timely support, the likelihood of them becoming loyal to your organization increases with every interaction.
Free Your Team to Do More with NLP Based Chatbots
It may become the unsung hero of your organization, but an NLP based chatbot can significantly reduce human efforts and intervention for repetitive tasks like billing, customer service, and sales qualification. Handing the mundane tasks to a bot effectively frees up your team to do more. With a Natural Language Processing chatbot, your staff can focus on their specific expertise and more mission critical tasks.
Reduce Overall Costs
With streamlined processes, like customer service and invoicing, you can experience reduced costs. This is because of reduced manpower and resources that are often needed for these repetitive tasks. Moreover, with increased brand loyalty comes higher customer retention rates, you can count on your existing customers to stick around longer. This helps by reducing turnover and reducing overall costs associated with turnover and new sales.
As a bonus reason, Natural Language Processing is smart enough to decipher more complex language variations like slang and abbreviations. NLP gets to the root of the meaning and sentiment, helping understand the emotion and intent behind the comment or query.
What is an NLP Engine and what can it do?
A Natural Language Processing Engine is the core component that is the force behind interpreting what users say and then converts that language into structured data that the system can then process. Using Machine Learning, NLP engines break down content and focuses on necessary pieces to understand user intent. In order to process a user’s input, NLP engines rely on a few elements:
- Intent recognition is the process of breaking down and compiling user intent through a few words. As an example, if a user inputs “search for plumbers in Scranton,” NLP analyses the complete sentence. It gets to the meaning of the words, positioning, plurality, and many more factors. Then breaks it down to something simpler like, “search for plumbers” to start with.
- Identifying entities is when NLP identifies such data as date, time, location, description, items, people, or objects. Then matches the entities to the user’s intent.
- Context analysis helps the chatbot see a bigger picture. It reveals the user’s circumstances and experiences over the course of the session.
- Other than the above capabilities, NLP engines possess a few more notable skills, such as document analysis and machine translations.
At the core of Natural Language Processing is the ability to understand input and then translate it into a language that can be understood between computers. Ultimately, an NLP engine’s job is to turn intent and context into structured data and signal APIs to get the query complete.
The use cases for such processing are only limited to your imagination. That being said, one powerful use case – that has been brought up over and over throughout this article – is chatbots.
Natural Language Processing: Why Your Chatbot Needs It
When you use Natural Language Processing within a chatbot, you can free up employees, reduce costs, and streamline customer service. This helps you ultimately achieve greater success. NLP isn’t determined to replace any real humans, however, it can imitate the same level of understanding and analysis. NLP ensures a chatbot’s success in delivering a stellar user experience.
At In-App Chat, our intelligent chat powers ground-breaking, never done before, as well as everyday necessary functionality. We go above and beyond to help you not only build better peer-to-peer connections, but to unleash endless possibilities when it comes to communications. When utilized with Natural Language Processing and the IoT, there’s no limit to what your chat can do.