Why should enterprises prefer conversational AI-based virtual assistants over basic chatbots?
Chatbot, conversational AI and virtual assistant are the concepts that are used interchangeably in the market. However, they are not referring to the same concepts and implementations. In this blog, we aim to propose a clear understanding of these concepts and the reasons why enterprises should prefer a conversational AI-based virtual assistant over a basic chatbot.
Basic chatbots vs. an AI-powered virtual assistants
In the simplest meaning, a chatbot is a computer program designed to allow interaction between humans and technology. In the initial phase of this technology, every conversational interaction with a machine was called a chatbot in the most general sense. However, as the technologies, use cases and benefits get more sophisticated, we tend to distinguish chatbots and virtual assistants. According to Gartner, chatbots and virtual assistants have important features that differentiate them.
A basic chatbot typically is a question-answer type interaction, in a limited domain and built through rule-based techniques. They have the ability to automate simple queries and still have value for some use cases. Chatbots use keywords and other language markers to trigger predefined responses.
Whereas, conversational AI-based virtual assistants can run complex dialogues and understand the free text human statement as they are based on conversational AI.
Source: Making Sense of the Chatbot and Conversational AI Platform Market
Basic chatbots can fulfil the needs of a small company in a limited use case, however, as enterprises need conversational interactions with their customers and employees, the best solution is conversational AI-based virtual assistants that have the ability to understand human language and provide transactional functionality.
Conversational AI is the synthetic brain power that makes virtual assistants capable of understanding, processing and responding to human language. It uses a large set of training data that enables deep learning algorithms to classify intents and better understand human language. It is the most advanced implementation and the power behind the virtual assistants.
Large organisations, like banks, marketplaces or government agencies, often have thousands of customer queries in a large scope and it is impossible for basic chatbots to function properly with an enhanced customer experience in such a need. Only conversational AI-based virtual assistants can fulfil the complicated needs of an enterprise by scaling its language understanding and capacity without any reduction in accuracy.
Why conversational AI-based virtual assistants better fit to the needs of enterprises rather than basic chatbots?
Conversational AI-based virtual assistants provide more sophisticated solutions that have the following features and capabilities that also explain the reason they are able to fulfil more complicated, enterprise grade requirements. Let’s have a look at these features and capabilities.
Conversational IVR
A conversational AI-based virtual assistant can interact with its users in a voice modality and can be integrated into the IVR to automate customer support by understanding and responding to customer queries by AI. Providing automation in voice interfaces as well as text interfaces creates an important efficiency opportunity for institutions.
Holistic customer experience
Conversational AI-based virtual assistants provide a holistic customer experience as they put the “customer” at the centre of everything. As customers’ needs cannot be limited to a specific department or field, this has to be a “total experience”. Multiple assistants managed by different departments, but orchestrated by a main bot maximises the customer experience.
AI-assisted live chat
AI does not only help customers, but it also helps the human agents by providing them the information they need when interacting with the customer. Connecting a virtual assistant to a knowledge base and allowing them to assist the human agents to reach the information easier and faster increases the efficiency and productivity.
Integrations
Conversational AI-based virtual assistants can be integrated into both the internal and external systems. This capability makes them behave in a larger scope with transactional capabilities in addition to the informational ones.
High accuracy & resolution rates
A conversational AI-based virtual assistant is able to understand natural human phrases so they have higher accuracy rates than basic chatbots. Understanding the customer better makes them provide higher resolution rates if the use case is related to customer support. Conversational AI-based virtual assistants understand a complex customer request and thake the actions in a flow. These crucial features make it possible for conversational AI-based virtual assistants to achieve high automation rates of up to 90%.
Scalable intent hierarchy
The number of topics is limited for a basic chatbot. However, when it comes to conversational AI-based virtual assistants, it is possible to manage hundreds and thousands of topics that an enterprise such as a bank, a telco company or a public institution needs. Conversational AI-based virtual assistants structure the topics in hierarchical trees, not in the same level and enrich the tree as the new topics are added, which provides an important flexibility for the enterprise.
Solution managed by the organisation itself
If the conversational AI-based virtual assistant is built on a no code / low code platform then the buyer organisation can have the ownership of the solution and manage it on the platform with no or limited dependency on the vendor, data scientists, developers.
Conversational analytics
An enterprise-level virtual assistant should give the enterprise team the opportunity to monitor and analyse the interactions and get actionable insights from this data. It is crucial to have this feature or tool to improve the existing experience.
Seamless human handover
In an experience offered by a conversational AI-based virtual assistant, the assistant can identify which topics are out of its scope and it is unable to understand. This is an important level of awareness. Because in this case it can handover it to a live agent to help the customer in a seamless way.
Omnichannel
Virtual assistants provide 24/7 personalised support, issue solving and shopping opportunities on the channels that the customers prefer. These can involve text based channels like website, WhatsApp or Facebook Messenger, or voice based channels like Google Assistant, mobile app of the company or its IVR system. Thus, enterprises can deploy and test new, fully-automated omnichannel experiences for sales and customer service.
Conclusion
As it is still an ummature market, concepts are used interchangeably and this unclear conceptual landscape makes it difficult for the IT and business managers to decide which solution fits their needs to solve certain issues around automation, customer support, sales and efficiency.
The first step is to define the concepts we use clearly. Then decide what is the exact solution for our needs. The last step is to define the vendors that fullfill the solution we are looking for and are aligned with our enterprise’s approach.
Therefore, this blog tried to clarify the two concepts, basic chatbots and conversational AI-based virtual assistants. It is up to the enterprises to decide which approach and solution best fits their needs.
CBOT is a conversational AI company, highly focused on customer service automation. CBOT Platform is a conversational AI-powered automation platform that CBOT offers to enterprises with the necessary tools and technologies to build scalable virtual assistants. The outcomes of CBOT Platform are sophisticated virtual assistants, with integrations, both into internal and external systems, omnichannel capabilities, operate in a large scope with both informational and transformational capabilities and human in the loop systems.
To see more details, please check out our success stories.