When it comes to service, we can think of people. People are the main body of service activities. When customers encounter problems, they will call the manufacturer. Experienced maintenance engineers will rush to the site to troubleshoot the equipment.
Due to human reasons, services are associated with low efficiency and high cost. It is difficult to automate non-standard services, and the journey alone is time-consuming and laborious. Today's society has entered the service economy from the manufacturing economy. How to solve the problems of low service efficiency and high cost is a big challenge for enterprises.
The author believes that the future service model will change dramatically, and the hybrid service model will become the leading force.
Fewer and fewer people are engaged in after-sales service
Traditionally, Chinese people value marketing and despise service, thinking that service is serving people. In many companies, the income and status of service personnel are far lower than that of sales personnel, and parents are reluctant to engage their children in service work.
In order to increase the sales of equipment, many domestic brands shouted the slogan of "lifelong free service" more than a decade ago. It is difficult for people engaged in free work to feel the value of the service. As a result, many service technicians change to sales, and college graduates are also unwilling to engage in service work.
The mode of sending technicians to the site for free service has entered a dead end. Who will be engaged in service work in the future?
Robots reduce customer satisfaction
Artificial intelligence and machine learning seem to be the solution to the problem of insufficient service personnel. In recent years, more and more enterprises have used chat robots to replace the artificial seats in the call center. The robots have no mood fluctuations, are on duty 24 hours a day, do not need to rest, and have a lower cost.
However, the robot can only solve standard service problems. For some complex faults, the robot has no solution, and it is very necessary to involve real people when necessary. Otherwise, the closed loop cannot be formed to ensure customer satisfaction.
In May, 2020, I complained to the customer service of Air China when I was having problems on Air China. What I got was that the robots repeatedly pushed the legal terms, which made me feel that they were just shirking their responsibilities coldly (see "Air China, are you really doing nothing wrong?" So I chose not to take Air China.
Robots' lack of empathy often hurts users. We have encountered many "dead cycles" in call centers, and the problem of phone calls still cannot be solved. At this time, employees with good empathy are required to come forward, otherwise customers may lose.
Many customer surveys show that robot customer service has become one of the important reasons for customer turnover (2021 customer expectations report, gladly), and customers still like the help of real people. From this point of view, robots are not the ultimate solution to the contradiction of service resources.
Hybrid mode is the key to solve the problem
On the surface, outstanding customer service requires experienced technicians, and more manpower is required to ensure the timeliness of service. Today, with the rapid rise of labor costs, the contradiction between good service and high cost seems irreconcilable, which has become a paradox, leaving many enterprises unable to make any progress.
The mixed service mode is the key to solve this contradiction. 80% of the problems are solved through IOT, robots, artificial intelligence AI, standard repair kits and self-service. Machine learning makes robots more and more skilled and can handle more problems. 20% of the problems must be manually introduced and supported by technical experts.
In the future, engineers will be sent to the site for all after-sales service problems, which will become impossible. There are not so many people, and the customer can not afford such a high cost. The most expensive thing in the future is not products, but labor. Although many enterprises still insist on free services, they will soon realize that this practice is giving up the most valuable "customer adhesive" and is not conducive to the long-term development of enterprises.
In the future, enterprises will provide instant messaging glasses for key equipment and important customers. When customers wear glasses, they can contact customer service experts through mobile app. Experts guide them through the camera on the glasses, just like being on the scene.
The system can find the fault first through the sensor on the equipment, automatically remind the user to stop, and complete intelligent fault diagnosis. Then the system fault is solved by downloading and updating the software again; Replace a part or electronic board to eliminate hardware failure. As long as the system can provide a simple solution, there is no need for service technicians to visit the site. The UAV is used to send the parts to the construction site, and the customer can complete the replacement under the guidance of video assistance.
Only under special circumstances will maintenance service personnel go to the customer's site, which will be a very expensive and luxurious solution. In the future, the rate of choosing on-site service will be less than 5%.
The hybrid mode minimizes the dependence of services on people and reduces costs. At the same time, the application of artificial intelligence technology ensures the success rate of services, ensures timeliness and solves problems at the first time.
Use artificial intelligence to automatically diagnose fault causes, match solutions, and present fault handling solutions on customers' glasses by means of AR, so as to help non professional personnel solve professional problems, empower customers, and change the world with technology.
The mixed service model perfectly solves the contradiction between service timeliness and high cost, improves customer experience, helps enterprises build a good reputation and enhance competitive advantage.
