In the movie Big Hero 6, the inflatable Baymax robot is a healthcare companion who can diagnose and suggest treatment based on the 10 000 medical procedures he has learnt, all within a two-second body scan. So, how far off are we from using such technology for customer service?
By Michelle Osmond
We are in fact already using artificial intelligence (AI) and machine learning on a daily basis when we use the Uber app to call for a taxi, or when Netflix suggests a series we may enjoy based on our viewing habits.
In the contact centre environment, this technology is being used to automate certain functions to enhance the customer experience, giving rise to the use of customer-facing chatbots and digital assistants that provide an initial layer of support that is accessible 24/7. The customer speaks to a machine and not a human agent.
Instead of going through long menus that force users to choose inadequate options and repeat their queries at every step, the chatbot uses automatic speech recognition (transcription) and text-to-speech (automated responses), to handle the initial contact and deal with basic interactions.
A chatbot must be able to correctly identify the intentions of the customer, and will have hundreds of possible scenarios available to it. It knows the entities involved, and what kind of immediate help can be provided.
Ongoing training of the chatbot enables it to expand the range of interactions it can manage. It must also be able to detect the emotional state of the customer, and based on the interaction, transfer the call to a human representative if necessary.
For instance, a chatbot can handle a basic interaction such as an airport shuttle booking, but it will transfer the call to a human agent if there is a query it cannot handle, such as whether or not the shuttle will be able to accommodate a bicycle.
All the information and context from the contact is passed on to the human agent in order to swiftly answer the query and finalise the booking, and the chatbot will stay on the call to learn the correct response for future reference. This is machine learning being used to expand the chatbot’s knowledge.
Social media integration
When the power of AI and machine learning is combined with the integration of the contact centre function with social media, a powerful customer engagement is possible.
When a customer’s luggage does not arrive and they are frustrated, they may turn to the travel company’s Facebook Messenger to complain. A messenger bot will be able to respond with a view of the full history of the customer journey. The chatbot will be able to detect the tone and urgency of this interaction and will transfer it to a human agent if they are unable to resolve the query effectively.
These technologies combine and enable us to link all the data we have for customers and make it available to both virtual and human agents. By creating this dialogue between the customer, the human agent, and the chatbot, agents have the ability to access useful data previously inaccessible in real-time, bringing augmented reality to the heart of the contact centre.
The contact centre agent of the future
This shift to integration of all channels and the use of chatbots will not make agents redundant, but rather allow them to focus on developing their communication skills and manage the more nuanced interactions that chatbots are not able to cope with. Contact centre agents will become super agents, with sophisticated social interaction and people management skills.
This will make for a better customer experience with swifter responses on whichever channel suits that particular customer best.