How to Build a Chatbot: Definition, Process, & Architecture
Artificial intelligence (AI) has had a significant impact on customer services in the past few years and chatbots are a notable technology that has changed the way businesses interact with customers.
Many of us are familiar with chatbots and have either interacted with them or have come across them when browsing the web. When you visit an online store, for instance, and a conversation box pops up with suggestions for questions you can ask about the various products, that feature uses chatbot technology.
What exactly is a chatbot? And what is the process and architecture of this technology?
Definition
“Chatbots use natural language recognition capabilities to discern the intent of what a user is saying, in order to respond to inquiries and requests,” is how IBM defines a chatbot. It is essentially a software developed to communicate with humans in a natural way. You may come across standalone chatbot apps as well as chatbots integrated with messaging applications.
Following a question-answer pattern, chatbots rely on artificial intelligence and machine learning to deliver appropriate answers for customer queries.
There are several benefits to using chatbots. They have significantly improved customer service as chatbots are available around the clock and customers need not wait until operating hours to contact customer support.
With chatbots, a business can also make the ordering and purchasing process simpler and more efficient. Customers will find a personalized service provided by the chatbot with recommendations based on products viewed previously.
Another key benefit of this technology is that businesses can now allocate fewer resources to customer service while still providing customers with efficient and effective support by investing in the services of a chatbot development company.
The Process
Chatbot technology has improved to an extent where customers may not even realise they are interacting with a machine. This is because AI and machine learning are at the core of chatbot technology. Chatbots use Natural Language Processing or NLP as well.
When a chatbot receives a user query, it processes the query through complex algorithms to recognize the request using specified preset instructions. The chatbot can then provide an appropriate response to the query.
The training period of the chatbot plays a vital role in its ability to respond to queries appropriately. This can make the development of chatbots expensive and time-consuming.
There are seven main steps a Chatbot development company will follow in the chatbot design process; Scope and requirement, input identification, understanding UI elements, crafting the first interaction, building conversation, and testing.
There are also two main types of chatbots. AI or intelligent chatbots use NLP and are not predefined. There is no limit to the access to customer services and the chatbot acts smart and responds to queries with the most appropriate answer. It can also decode messages quickly and respond accordingly.
A fixed or rule-based chatbot, on the other hand, does not use NLP and is predefined. Access to customer services is limited and the chatbot responds to queries using a predefined script. It also does not decode messages quickly.
Architecture
Chatbot architecture consists of key elements like pattern matching, Natural Language Understanding (NLU), NLP, a knowledge base, and data storage. The involvement of AI app developers and a machine learning consultancy is vital when building a chatbot for a business.
When building a chatbot, a business should begin by defining the goals of the chatbot by taking into consideration business requirements and customer demands. It is then important to decide on a communication channel, whether it is the company website or mobile app or messaging applications like Facebook Messenger.
The third step is where the developers come in as it is time to design conversational language and architecture. You need to consider all possible questions a customer may have about your business, products, and services.
The next step is to choose an app for integration, followed by data collection. You must then select a development platform or framework that is best suited for your needs. After dialogue flow implementation, you can carry out testing and deployment.
