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AI-powered Virtual Assistant is no ordinary chatbot

Nowadays, it is common for businesses to set up chatbots on their webpages to engage with customers. When combined with AI and machine learning, chatbots can be transformed to virtual assistants and there is a significant difference between the two. Chatbots are relied upon to help with customer inquiries, while virtual assistants are responsible for daily business operations in addition to customer engagement.

Virtual assistants can perform customer facing functions with a higher understanding of users’ intent. They can also act as your personal assistant to simplify internal work processes, they improve repetitive day-to-day business operations, freeing up time for employees to turn their attention toward more important activities that cannot be performed through automation.

Understanding of human emotions

Traditionally, chatbots are designed to execute rule-based programs, they are built on a decision tree which allows interactions through buttons and reply with a set of pre-defined answers. A virtual assistant is trained by learning from actual sets of data, as thanks to Natural Language Processing (NLP), they can interpret the user's intent over time to provide information contextually based on their behavior and preferences. The platform provides advanced Natural Language Understanding (NLU) features to test utterances, configure stop words, sentiment, and flow matching thresholds. In short, virtual assistants interact with users much more human-like, offering higher efficiency and accuracy.

Learns as it goes

Chatbots rely on developers’ effort to enhance the rule-based system, while virtual assistant is combined with Machine Learning (ML) and Artificial Intelligence (AI), so continuously learn, offer accurate responses, and retain context to personalise conversations.

Capturing data regarding most asked questions, intents that were not recognised and duration of users’ interaction with a virtual assistant are just a few examples of data that can be recorded to enhance the conversation quality. Storing and presenting this data on a dashboard allows continuous rational decision making based on actual data. Taking the lessons learnt and reapplying them into the engine to enhance conversation flows leverages full advantage of the ability for the AI platform to learn more about your customers.

Multi-channel connection

A traditional chatbot is a single channel tool, it can be used on website, social media or an app. A virtual assistant is omnichannel, therefore in addition to what a chatbot can perform, it can be integrated with a number of social channels including FB Messenger, Whatsapp, Slack, Skype etc. Virtual Assistant can also send personalised automated follow-up emails which are especially useful to engage the customer with the business.

More comprehensive conversation flow

Chatbots lose the content of a conversation if you break the interaction in the middle, they are often unable to retain context over the course of a conversation, or between two different conversations with the same user. Virtual assistants are not bound by a rigid conversational flow, they can extract contextual data from a customer’s conversation. By identifying the context and the intentions behind the questions, the user will get an answer no matter how the question is asked. In addition, virtual assistants will be able to guide the customers if they are not sure about the information they need. Moreover, they can retain content between two different conversations from different channels with the same user. It offers a seamless experience to the customer across multiple engagements with the brand, while also maintaining high levels of automation and accuracy.

Seamless integration with Live Chat

A virtual assistant can be used to identify key phrases or terms that require specialist human intervention, such as complaints, anti-social behaviour issues or emergencies such as gas leaks or lost keys. Such circumstances can immediately invoke a connection to a Live Chat agent, who is presented with the conversation history of the chat at the point the chat was transferred. The live agent can then pick up the chat and either conclude it or hand back to the virtual assistant to finalise the enquiry.

Similarly, a virtual assistant can undertake user authentication and an understanding of an enquiry, prior to handing over to a Live Agent. A great example of this is an IT Service Desk solution, where the virtual assistant captures user details and the nature of their enquiry, then generates a service ticket prior to placing the chat in a queue. When the chat is opened by an agent, the ticket details are available to the agent. When the chat is concluded, the virtual assistant picks up the chat again to copy & paste the chat history into the ticket, and capture user feedback on their experience.

Multi-task personal assistant

The core functionality of chatbots is to assist customers such as responding to FAQs or form-filing. Virtual assistants can perform a much wider range of tasks.

Externally, they can understand a customers’ requirements and assist them with product discovery. It can make recommendations based on customers’ stated requirements or past behaviours, or help the customer compare multiple products. It can provide customers with information or advice about a brand’s products or services.

Internally, they can act as your personal assistant, as not all positions are equipped with a secretary, so it can be viable to have a virtual assistant that help you handle daily tasks. They can help you to schedule meetings, set priority on different tasks, delegate tasks to subordinates etc, it set staff free from handling administrative tasks and focus on higher-value engagements.

With more companies embracing virtual assistants, it is becoming an integral part of our lives both as an employer, employee or a consumer. Conversational AI can be applied to a number of industries including healthcare, banking, insurance, retail etc. Exploring and deploying the best AI-powered solution is a critical step in accelerating the AI transition, and the time to act is right now.

See our use case on IT Service Desk Live Chat here.


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