Thought chatbots were trendy? Make way for interactive virtual assistants (IVAs). But can chatbots change the customer experience? Can IVAs like Amelia go beyond the limitations of chatbots? There is plenty to consider.
In 50 years, chatbots have evolved first to engage users in dialogues for customer service in many fields and now to conversations on personal medication information. With the advent of cognitive intelligence, chatbots were given a facelift.
Conversational artificial intelligence (AI) has come a long way since ELIZA, which was intended by its creator in 1964 to be a parody of the responses of a psychotherapist to his patient, as a demonstration that communication between a human and a machine could only be superficial.
Conversational AI is the set of technologies behind automated messaging and voice-enabled applications that enable human-like interactions between computers and humans. Applied conversational AI requires science and art to develop successful applications incorporating context, personalisation and relevance in human-computer exchange.
The fundamental aspect of conversational AI applications is designing processes that sound natural, and the result is indistinguishable from what a human could have delivered. This is the highest quality conversational AI.
It uses various technologies, such as automatic speech recognition, natural language processing (NLP), advanced dialogue management and machine learning, to understand, respond to and learn from every interaction. Human language is full of grammar exceptions, dialects and other eccentricities too complicated for AI to understand. Words can have different meanings in different contexts. NLP enables an IVA to understand a customer's language, recognise their intention and produce a response.
The fundamental aspect of conversational AI applications is designing processes that sound natural, and the result is indistinguishable from what a human could have delivered.
Still, chatbots incorporating AI today are challenged to successfully process technical commands, understand human intent, exhibit conversational intelligence and understand different languages, accents and dialects. Today, the ability to understand the subtle nuances of human tonalities and speech patterns and mimic human empathy in texts and voices makes a chatbot truly successful across industries and verticals.
Natural Language Processing allows a computer algorithm to understand and interpret a user's request. Using a bidirectional transformer will enable us to truly understand the context of different words. For example, let's look at two simple phrases: ‘book me a ship’ versus ‘ship me a book’. If you utilise a keyword approach, or do not keep the context of how words co-relate, you may not do what the user really wants.
Imagine for a moment conversational AI in healthcare. Users report symptoms of their illness to the app, which checks them against a database of diseases, then offers an appropriate course of action. We have seen the deployment begin, using the chatbot to dispense medical advice, AI triage model and more.
Other start-ups have tried the health companion app to help assess the user's health based on the indicated symptoms using its vast AI-based database. These will become a standard diagnostic tool for doctors; monitoring health data over the long-term to enable predictive and proactive care is definitely the futurist view. A voice interface allows users to trial through existing voice applications like Siri and Alexa.
Trends in conversational AI chatbots continue to raise the bar:
Greater personalisation. Conversation bots can remember conversation context, past dialogues and user preferences. They can also understand sentiment and mood, and respond accordingly, especially to users' cross-sell and up-sell products and services.
Augmented reality is making its way into chatbots, such as to show how a coffee table might look in your living room, or how some new clothes would fit you. Interactive virtual assistants are making the runway this season.
Business users in chatbot development. No longer the exclusive domain of developers and linguists, chatbot creation now includes business users closer to understanding customer needs to make the chatbot more engaging. This includes scriptwriters who guide the flow of conversation through brand value to open-ended questions.
The customer experience is constantly evolving. It's not just about finding your customers where they are; it's also about anticipating where they are going, what they need, and how your brand can best support them. Perseverance is a must!
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