New challenges arise in line with changing customer expectations. How…
The time they need to search for relevant information is the time wasted. Do not let your customers wait and make sure your agents can act as quickly and as accurately as possible.
What will be the role of AI and technology in general in contact centres in the future?
The main goal for AI and automation will increase agent efficiency. Using AI and NLP, we can figure out the intention for a given support ticket and route it to the best agent. When the system understands the user’s intent, it can again leverage AI/NLP to identify the actions to be performed by the agent. As the training matures, AI will eventually either suggest resolutions to the agents or resolve the contact itself. What will happen ultimately is that AI and automation will solve most of the simple cases while assisting agents in more complex cases. This process will eventually reduce the workforce need for contact centres.
What are the advantages and disadvantages of self-service?
When customers are empowered to resolve their issues themselves via automation, the volume of support interactions which need agent interaction, and consequently support costs will be significantly reduced while preserving a high CSAT rate. However, not all self-services are created equal. Having poorly designed self-service flows in the system can be counter-productive and have zero effect on contact rate reduction. When customers have to go through more steps that do not solve their issues, it will potentially confuse and frustrate them and adds an undue cognitive burden on the user.
How to boost agent performance and productivity?
Showing them what they need to know and what they need to do as quickly and accurately as possible is the key. As soon as they have to hunt for information or standard operation procedures, handling time is already wasted. Furthermore, assigning the wrong contact to the wrong agent will also decrease their productivity. As such, by leveraging AI, we are able to accurately predict the right information, policy, and actions for our agents.
ZJ Loh, Staff Software Engineer at Uber is a system architect for Uber Customer Care. He has built the Uber customer support system from the ground-up. His biggest challenge is to sustain Uber-scaled growth while keeping the support cost in check. He is now focusing on evolving Uber customer care into the world of self-service, automation, and artificial intelligence. Before that, he worked for the workforce management area in Nice System Inc.