What is a Chatbot?
What is it? How do they work and why are they something that helps to grow my business?
Can I build my own chatbot?
These are the Frequently Asked Questions (FAQ) when you think about using a chatbot to expand your business. According to research done by Forbes, the market for chatbots is reaching $1.25 billion by 2025.
Nowadays, a customer, who wants to buy from you, believes that the importance of the experience your company has and provides is equal to its products or services. That’s where AI chatbots come into play. It’s no lie to say that bots are a very important piece of the puzzle to Customer Service Automation (CSA).
We, at Shinebot, will comprehensively discuss all of the FAQs and how chatbots are necessary for today’s digital marketing strategy of your company.
Chatbot… What is it?
If you are interested in the story of how chatbots came to live, you can click on the quote above.
In short, the definition of a chatbot is an AI (Artificial intelligence) based computer program that is built to simulate human conversations. They are also known as digital assistants that understand human capabilities. Bots interpret and process the user requests and give prompt relevant answers.
Across websites, applications, and messaging channels (e.g. Messenger, Twitter, WhatsApp,…), bots can be deployed through voice as well as text.
How do they work?
A chatbot works by identifying the user’s request. It’s analyzing the intent of the question to extract entities, who are relevant. This is the most important task of a chatbot. Once the analysis is done, the most appropriate response is delivered to the user. It works by using three classification methods.
Artificial Intelligence Markup Language (AIML) is a standard structured model of this pattern. Bots use this pattern to group the text and produce the appropriate response to the client. It’s able to get the right answer in the related pattern. The bot reacts to anything related to the matching pattern.
Natural language understanding (NLU)
NLU gives the chatbot the ability to understand a human. Natural Language Understanding converts text into structured data, so the machine is able to understand it. It follows three specific concepts: expectations, entities, and context.
- Expectations – When the customer makes a request, the bot must be able to fulfill his expectation.
- Entities – This creates an idea for the chatbot. For example, it may be a refund system or the customer is searching for a specific product.
- Context – If the chatbot isn’t using a natural language understanding algorithm that identifies the request and can’t lean on a historical backdrop of conversation, it will not be able to recall the request to give the response.
Natural language processing (NLP)
To convert the text or speech input of the user into structured data, the bot is designed to use Natural Language Processing (NLP). This collected data is used to choose an answer which is relevant to the needs of the customer.
Natural Language Processing (NLP) is a process that follows the steps below:
- Tokenization – A set of words is filtered bij the NLP in the form of tokens.
- Sentiment Analysis – The bot is able to interpret the user responses to get an idea of his emotions.
- Normalization – It checks for typing errors that can change the meaning of what a customer is asking or looking for.
- Entity Recognition – In this process the bot is looking for the necessary information in different categories.
- Dependency Parsing – The chatbot is always looking for questions or sentences that the customer frequently uses. That way it can interact faster in the future.
If you are interested in knowing more about chatbots, follow this blog.
Next week I will be posting more about types of chatbots, why they are important for your business, and how to build your first chatbot…