Start-to-end customer service experience with Xaleon
Customer has problem
Behavioural Rules detect customer problem
Chatbot is triggered
A specified chatbot is triggered to engage the customer and offer help.
Chatbot engages, customer explains problem
The Chatbot covers standard questions to gather context, asking the customer to describe their issue or what they are trying to achieve.
Xaleon finds the available agent best suited to solve the customer’s problem. Based on the customer’s explanation of their issue, Xaleon uses a combination of sentiment analysis and other parameters (e.g. current page of the user).
Agent enters conversation
The agent seamlessly takes over the conversation previously led by the Chatbot, and can view the existing conversation history.
Upgrade to Co-Browsing
To solve a more complex problem and achieve visual context, the agent can offer to Co-Browse with the customer.
Upgrade to Web Chat or Video Chat
For more a personal, and potentially more efficient conversation, the agent can transition the interaction to a Web Chat or Video Chat.
With context from Co-Browsing and Web Chat, the agent can guide the customer to a solution in record time. The customer will now be prepared to handle similar situations independently.
After the support interaction, the customer can provide feedback on the service experience, measured according to the net promoter score.
Xaleon’s Engagement Platform provides us with an end-to-end solution, the value of which I cannot overstate; everything from first sales contact, customer on-boarding, problem-resolution and of course, gathering real-time insight into our customer’s barriers and problems has significantly improved our entire Customer Experience function.
Director of Sales
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