A chatbot is known to be an AI-based program simulating human conversations. They act as digital assistants that are well versed with human capabilities, understands the user intent, promptly answer their questions and give solution to their issues. With the invention of chatbots, the interaction between customers and brands has completely changed. Having conversations with customers and providing them instant responses has made chatbots beneficial for businesses.
Button or Menu-based Chatbots
In today’s market, button or menu-based chatbots are considered the most basic and slowest chatbots to get the customers to their desired result. However, they need users to make numerous selections to get the ultimate answer.
Menu-based chatbots are well programmed to answer FAQs in nearly 80% of support queries; however, they fall short in advance scenarios where they need too much knowledge to answer customers’ queries.
Rule-based Chatbots
If you can predict what type of questions your consumers may ask, a rule-based chatbot is suitable for your business. Unfortunately, rule-based chatbots are usually slow to develop and use if/then logic to create the conversational flow. In rule-based chatbots, businesses need to define the language condition of the chatbots—conditions ( asses the order of the words, synonyms, and many more). Then, if a customer makes any query that matches the condition defined by the chatbot, the customer can receive the required answer in no time.
Machine Learning Chatbots
Have you ever thought about what a contextual chatbot is? This type of chatbot uses Artificial Intelligence (AI) and Machine Learning (ML) to remember conversations that occurred with a specific user. ML chatbots have contextual awareness and are competent to self-improve depending upon what customers are querying about and how they are querying it.
Keyword Recognition-based Chatbots
Keyword recognition-based chatbots are proficient in listening to what users are typing and responding accordingly. These chatbots use customizable keywords and Natural Learning Processing (NLP) to provide an appropriate answer to the customer. However, they usually fall short while responding to many similar questions. NLP chatbots start slipping when keyword redundancy is there between numerous related questions.
The Hybrid Model
Usually, businesses like the sophistication of AI-chatbots but often don’t have the talent or large volumes of data to support them. Thus, they go for the hybrid model as it offers the best of both – the simplicity of the rules-based chatbots besides the complexity of AI chatbots.
Voicebots
A voice-based chatbot provides a frictionless experience to the customers. These days, businesses are initiating voice-based chatbots to make the conversational interface more vernacular due to its convenience. For a customer, it is quite easy to speak instead of typing.
