How do AI-based Virtual Assistants Augment Customer Agents?
AI-based virtual assistants create a significant efficiency impact in customer service by answering up to 80% of incoming calls without transferring them to a human. However, a welcoming virtual assistant is not the only way to create efficiency with AI in customer service. In addition to customer facing virtual assistants, it is possible to create greater efficiency by empowering customer agents with virtual assistants. In this blog, we discuss how customer agents are empowered by using AI technologies.
In Gartner report, it is estimated that there are approximately 17 million call center agents in the world by 2022. The efficient operation of such a high number of workforce is very important for the overall profitability of companies.
We know that AI-based virtual assistants increase efficiency and provide a better customer experience for companies where the number of customer interactions is high and the experience is more focused on digital. The model generally used to keep customer satisfaction at the highest level is to use human and AI together to establish a structure where customers are welcomed by the AI and transferred to a customer agent for defined synerios.
In addition to this, a setup that positions AI as the assistant of the customer agents who is always with them and helps them do their job faster and easier, also provides an additional benefit. In this cooperation, companies that maximise the use of AI increase the efficiency of customer service more. Gartner estimates that conversational AI will reduce customer service costs $80 billion by 2026 and $240 billion by 2031.
So, what are the ways of creating the best use of AI as an agent assistant? Let’s briefly mention the most prominent methods.
How does AI augment the customer agents?
AI-based informative assistant
Your assistant is helping the agents just as he/she is helping the customer. When the agent needs any information in response to the customer’s question or request, he/she asks it to the assistant. The assistant crawls the information base and provides the most up-to-date information to the agent. Thus, the agent immediately accesses the most up-to-date information regarding the changes in the law, changes in company policies, new products and campaigns, etc. This method makes it very easy and fast for the agent to reach the information and diminishes the call resolution time.
Prompt support for the agent
An important way to reduce the agent’s response time is to provide ready to use responses. While the agent corresponds with the customer, the answer for each question is prepared by the assistant and displayed to the agent instantly. If the agent thinks that the answer is correct and appropriate, he/she presses the send button or edits it if necessary. Thus, the assistant provides the answers for the agent like a prompter, shortens the call resolution time and ensures an efficient operation.
Bilateral transmission structure
Another component is that there is a two-way transfer mechanism between the agent and the assistant. We know that the virtual assistant transfers the customer to the agent in some defined situations. In this setup, the agent transfers the customer to the assistant when necessary. In other words, there is a two-sided transfer structure. If a simple information is required, for example an address needs to be reported, or a simple confirmation process is in question, the agent transfers this dialog to the virtual assistant. The virtual assistant, who receives the address information from the customer, writes it to the relevant system, and then transfers the dialog back to the agents or terminates it. Thus, it enables the agent to do his/her job easier and faster.
These implementations, in which an AI-based virtual assistant strengthens the customer agents, create an efficient working model between the two and increase the overall performance of the company.
We can summarize the prominent effects as follows:
- Shortening call resolution time
- Increasing the first contact resolution ratio
- Improving the customer experience
- Increasing customer loyalty
Conclusion
In every sector, it is possible to find use cases that can be automated with AI and quickly create a financial impact. These fields may be credit inquiry and money transfer, doctor appointment, automobile maintenance appointment, cargo tracking, invoicing and more. When the company discovers a use case that is easy to automate and makes a high proportion of customer queries, it can create 70-80% efficiency in customer service. Automating these processes with AI makes life easier for customers by providing a better experience. The critical question here is, “How can AI and humans best collaborate?”. In this collaboration, AI should be positioned as serving not only the customer but also the agent. Companies should also consider the issue of empowering their agents with the methods mentioned in this blog when building their strategies.