Conversational AI helps customers get the answers they need faster and more efficiently
AI assistants give agents the tools to excel at their jobs: data, responses, entities and intents
Increase operational performance and collections with fewer agents while curbing costs, 24/7
So what is conversational AI? Conversational AI uses large or custom language models, natural language understanding (NLU) and machine learning to provide personalised and human-like customer interactions. Basically, conversational AI uses chatbots or AI agents to simulate conversations with human users.
In contact centers, conversational AI can be used to:
- Answer common questions
- Resolve simple customer queries
- Collect customer information
- Route customers to the appropriate agent
- AI assistants for agents
- Self-service guidance
AI agents can handle routine enquiries thus reducing the workload on contact centre agents. AI can automate entire interactions (call containment) or specific tasks within interactions, e.g., identifying a customer’s name, policy number, and reason for calling.
Another compelling feature is out of hours accessibility. From 9%-16% of customer conversations can be handled by AI agents after the human agents have knocked-off for the day. Many customers cannot contact businesses during work hours so after hours convenience is warmly welcomed.
Whether it's answering common questions, setting up payment plans, or processing transactions, conversational AI can manage these tasks around the clock without needing a break.
This significantly reduces waiting times (no more waiting on hold and then abandoning the call!) and improves customer satisfaction.
Conversational AI works perfectly across all digital messaging channels - in those very channels that customers feel at home communicating in. The likes of WhatsApp, SMS, Viber, web chat and Messenger are becoming the preferred option for customers to connect with businesses.
Not only are many people phone-adverse, digital channels are immediate and always on, and customers can reply at their own convenience.
"An AI assistant on your shoulder"
Analyse customer messages to help agents understand their emotional state which in turn guides their responses. The AI can add tags such as 'Positive' or 'Negative' to a conversation.
Entities are useful pieces of information that the AI recognises and extracts from unstructured text. For example, 'date of birth', 'amount' and 'payment date'.
Intents are what the customer is wanting to do or say. By understanding customer intent, the system can direct them down the best conversation route to resolve their query, e.g. to make a payment.
Propensity is understanding within a few utterances the most likely outcome of a conversation and set the conversation journey accordingly.
Additionally, AI can gather insights from customer interactions and use API to gather customer data to make the conversation useful and personalised.
AI acts as a co-pilot for agents, providing real-time insights and lifting the stress load by handling the tedious tasks while helping agents find the information they need, quickly and accurately. This leads to a more skilled and effective agent resource.
According to Gartner, conversational AI is projected to reduce agent labour costs by $80 billion in contact centers by 2026.
Contact centre managers will all agree that labour expenses are one of their biggest headaches, which can account for up to 95% of contact center costs (Gartner). On the other hand, conversational AI makes agents more efficient and effective.
By automating repetitive tasks, conversational AI and automation can free up agents to focus on more interesting queries. Furthermore, AI co-pilots make an agent's job easier with suggested responses and more information at their fingertips which eases the stress burden of dealing with anxious or angry customers.
If you need to improve your customer engagement, talk to us and we'll show you how AI and automation via digital messaging channels work.
You will love the Webio experience.
We promise.