Drive self-service and provide enterprise-grade, human-to-machine and customer care experiences with Conversational AI solutions. Scale your customer service operations and meet high volumes of customer service requests, whilst reducing operational costs.
Omnichannel Virtual Assistant | Conversational Biometric Authentication | Agent Augmentation Tools | Natural Language Processing
When we talk about Conversational AI, we’re referring to an array of technologies including chatbots, virtual assistants, and conversational IVR. These technologies use large volumes of data, machine learning and natural language processing to deliver human-like conversational experiences. In simple terms, it’s technology with the ability to understand text and speech in the same way human beings can.
By using Natural Language Processing, the AI can understand the context behind words in a sentence and respond much more effectively. This means the AI can alter a conversation based on factors like a person’s historic relationship, sentiment, and context – just like a human agent.
Conversational AI is extremely useful when it comes to customer service: you have these virtual agents that can interpret intentions and respond in the same way a human would – only they do it faster, more accurately, and for a much lower cost per interaction.
Conversational AI uses Natural Language Processing to understand user utterance – either through a chat application or a voice channel. When setting up a Conversational AI, organisations will need to model their business processes to ensure the Conversational AI behaves the way they want it to in any given customer facing situation. This process modelling is why adopting a holistic approach to Conversational AI tools is so important.
Natural Language Processing strives to build machines that understand and respond to text or voice data—and respond with text or speech of their own—in much the same way humans do. This means that it can comb through a customer’s user utterance to find the meaningful terms and phrases that it will use to respond.
Using Conversational AI, you can provide automated self-service options for customers on web, mobile and voice channels. This means you can manage high volumes of interactions consistently, provide 24/7 cover far more cheaply than by rotating live agents, and boost CSAT by improving AHT.
With Conversational AI you can:
83% of IT leaders say AI and Machine learning is transforming customer engagement. Why are organisations increasingly looking to implement AI and automation in their service strategy?
There are several drivers behind the adoption of Conversational AI software in the contact centre:
What is the difference between Conversational AI and a Chatbot?
The main difference lies in the ability to recognise and respond to intent. Conversational AI can detect intent behind a user utterance, whilst chatbots are much more transactional. Conversational AI can triage requests, track, and remain aware of the context behind queries – so it’s much better when it comes to providing a human-like experience.
Chatbots might be able to handle customer issues, but likely won’t be equipped to handle multi-part requests as they aren’t able to triage and decipher the context behind the requests. They’re much more linear, and often rely on specific scripts. Any deviation, and they’ll need to transfer to a human agent.
Conversational AI can handle dialogue variations. For example, if a customer realises half way through an interaction that they’ve been referring to the wrong credit card, Conversational AI can simply revisit the point in the conversation at which it confirmed which card was being discussed, redo that interaction, and continue the process without losing any of the information it retrieved previously.
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