An important channel for enterprise marketing. Since the development of Chinese customer service industry in 1990, it has evolved from the initial call center to the full scene intelligent customer service.Next, True-E Canada Digital Marketing expert Jenny Mei will tell you more about it.
In the past five years, with the technological development of the Internet, big data, cloud computing and artificial intelligence, more and more enterprises have invested in building customer service centers. The seating scale of Chinese customer service centers has increased year by year, maintaining a compound annual growth rate of 17%. By 2020, the number has exceeded 3 million.
"Enterprise customer Service" is a product launched by Tencent in the field of intelligent SaaS. It is understood that its embryonic form can be traced back to 2007, when a newspaper in Hangzhou would print its QQ number on the newspaper, and every day some citizens added it to ask for help in solving people's livelihood problems. The service was good at first, but soon the client crashed as the number of users increased. Therefore, a special QQ customer service system was integrated within Tencent at that time.
After more than ten years of development, the connotation of customer service business has also undergone great changes. at present, many traditional industries still use customer service operation as "porters". It generally responds to customers' mechanical questions about commodity prices, stocks and so on, which results in a lot of waste of manpower.
The focus of enterprise customer service is this kind of scenario demand, enterprise customer service can help customer enterprises to complete the direct docking between background business systems, so as to improve the overall efficiency of enterprise operation.
In order to improve the customer experience, in order to make the intelligent customer service more humanized, the enterprise customer service has designed the function of man-machine-assisted intelligence, that is, it can intelligently judge whether the response of the robot has satisfied the customer. If the customer's problem is not solved, human-aided intelligence can find out the problem node that the customer needs to solve urgently by combing the route of human-computer interaction, and receive the artificial customer service in time.