The customer service industry has always been a labor-intensive industry. With the development of AI technology, enterprises began to use intelligent customer service to optimize their service capabilities.
But can intelligent customer service solve the pain points of enterprises? What work can it undertake? What kind of intelligent customer service is suitable for enterprises? These problems require managers to think ahead and analyze the necessity and feasibility of applying intelligent customer service in combination with the actual business situation of enterprises.
Why should we introduce intelligent customer service?
The functions of each customer service center are different, so when considering the introduction of intelligent customer service, we must objectively evaluate the functions of the customer service center.
What business is the customer service center mainly responsible for? Is it based on service care or marketing? Is it incoming or outgoing? Which business accounts for a large proportion? What function does the enterprise need it to achieve?
Followed by further evaluation, which kind of intelligent customer service is more suitable to solve the pain points of enterprises? This needs to combine the pain points of enterprises and the advantages of all kinds of intelligent customer service, and choose the more needed intelligent customer service model.
Is the business volume of the enterprise suitable for online intelligent customer service?
The business volume that enterprises can divert to intelligent customer service can easily fall into two misunderstandings.
One is too optimistic, the business volume of the customer service center is not large, but it fluctuates greatly, but some intelligent customer service that causes fluctuations cannot be solved, so the effect is not obvious.
The other is too conservative. After the intelligent customer service goes online, the processing capacity has increased greatly, but the number of manual customer service has not decreased significantly, and the labor cost has not decreased, so enterprises are reluctant to continue to use it.
In fact, this is not that the function of intelligent customer service is not obvious, but that the pent-up customer demand is released after going online. Originally, it may be limited by manpower or system waiting number, which leads to the bottleneck in the number of service customers.
After the online intelligent customer service, because there is no additional increase in manpower, the need to find human services is still maintained at a certain level. However, the processing capacity has increased significantly, indicating that robots have enabled customer service centers to serve more customers.
In order to avoid this misunderstanding, enterprises can objectively predict and analyze the handling capacity of the customer service center, and objectively evaluate the single CALL cost from each service.
What preparations do enterprises need to make before intelligent customer service goes online?
The premise of artificial intelligence is manpower. In order to make intelligent customer service play its greatest role, enterprises need to set up an operation and maintenance team. It includes key functions such as wrong answer to knowledge points, maintenance and update, graphic editing, data analysis and voice management. Enterprises need to set up a team according to the current business situation, constantly optimize the knowledge points that fail to answer, and improve the intelligence of robots.
In addition, before going online, we should sort out the industry knowledge points to see which business types are suitable for intelligent customer service response. It can be viewed from the two dimensions of large consultation volume and many queries, and the hot issues can be filtered out and entered into the knowledge base. Because intelligent customer service is in the form of question and answer, it is necessary to consider how the knowledge base structure can better match the logic of intelligent customer service and improve the efficiency of problem solving.
Of course, knowledge sorting, input, training and subsequent optimization and upgrading can also be entrusted to service providers for operation, further reducing the burden on enterprises.