The hottest JD smart customer service concept has

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JD smart customer service concept is further implemented

as one of the important bridges to communicate with consumers, the service quality of e-commerce customer service plays a vital role in user satisfaction. As a domestic self-supporting e-commerce enterprise with a hydraulic price at least 10000 yuan higher than the leverage price, has always been making efforts to improve the quality of customer service through technological progress. Through the precipitation and innovation of data application, the concept of smart customer service has been further implemented. Through the application of big data, the user experience has been greatly improved, the efficiency of customer service has been improved, and the operation cost has been reduced, It provides a solid guarantee for the upcoming 618 promotion

intelligent IVR: personalized service under big data application

in modern enterprises, customer service mostly adopts interactive voice question and answer between call center and IVR (int uses residual energy after punching the sample, that is, automatically swings the active voice response), but the traditional IVR is not intelligent enough. For example, the user must press the number key several times according to the voice prompt to find the corresponding customer service personnel. On the one hand, the operation is cumbersome, the voice broadcasting time is long, and the user experience is poor; On the other hand, a large number of users will choose the wrong number keys, and the same query entered by a user at different times may be about different needs, resulting in invalid consultation and customer service transfer, or even interruption of service. Traditional IVR design only considers the basic menu services of all audiences, which is difficult to realize customization and user segmentation services, so the service mode is often unsatisfactory's intelligent IVR project takes data processing, analysis and prediction technology as the brain, scenario as the condition, and IVR as the carrier. It uses data analysis, mining and processing technology to lock in users' high possibility appeal scenarios. When users call, they will directly enter the exclusive customer service. The project fully reflects JD's big data accumulation, application and intelligence, makes intelligent predictions for different users, and quickly and accurately distinguishes users' business types, product classifications, after-sales services and other personalized services

for example, user Feng placed an order yesterday, and the order is currently suspended. When a user calls for consultation, the data brain finds that the user often places an order when he is anxious to use it according to his previous behavior. It predicts that the most likely reason for the user's call is to send a reminder. The user's call is directly assigned to the exclusive customer service specialist of the reminder, and the customer service specialist receives it; At the same time, the solution is directly displayed to the customer service specialist on the CRM (customer relationship management system) workbench. The customer service specialist quickly solves the problem for the user according to the solution provided by the system has huge and real user data. Through the data brain, it analyzes users' different portraits and adds personalized labels such as post-90s and digital talent, so as to bring users more exclusive services that meet their characteristics.'s intelligent IVR is based on user identification and tagging. According to the further analysis and mining of user consultation business scenarios,'s intelligent IVR matches exclusive teams for's customer service platforms, and realizes differentiated service processes for users with different needs

Tong Lina, head of the after-sales customer service research and development data analysis department of's operation research and development department, said: by establishing a large number of data analysis models, intelligent IVR has been able to predict more than 20000 user consultation scenarios, with an accuracy rate of more than 90%

customer service workload prediction and intelligent scheduling

618, 11.11 and other e-commerce promotion periods must be the time when the order volume and customer service volume surge. At this time, the scheduling of customer service resources is particularly important, which is related to the customer experience and the company's operating costs

JD big data helps the customer service center realize the prediction of customer service resources in advance by mining the fluctuation pattern of traffic with time and special events through data analysis and prediction technology, and analyzing and mining the traffic in the past three years, based on the research on the accuracy, availability and integrity of the underlying data of customer service events, focus activities, station views, market activities, event summaries and other related businesses, So as to prepare in advance for events that may cause abnormal fluctuations in customer service resources, so as to reduce operating costs, reasonably arrange customer service resources, and arrange shifts scientifically and reasonably

the figure is: the trend chart of traffic on that day

taking the traffic forecast as an example, JD big data sorts the historical traffic data provided by the customer service center in chronological order, and the interval between two starts is much longer, including regular time, major festivals, large market promotions, etc., which are marked in combination with the reasons for fluctuations; Secondly, JD big data models the regular traffic fluctuation, the additional fluctuation during major festivals and the additional fluctuation during large-scale market activities respectively, simulates the traffic prediction range of the day, and forecasts the demand for e-commerce promotion such as 11.11 and 618, so that customer service can be prepared in advance. The project has been able to achieve a prediction cycle 28 days in advance, and the prediction accuracy has reached 80%

big data is being widely used and has great value. It will also bring a huge change to the customer service industry. As a window for direct communication with customers, the service level of the after-sales customer service system will directly affect JD's overall operation ability and user shopping experience. Through the implementation of JD smart customer service project, the after-sales customer service system has also achieved a technological leap, which will provide a strong guarantee for the rapid development of JD business. This year's 618 promotion is just around the corner, and the achievements of JD smart customer service are even more expected

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