Cognitive technology-based electric power service data process system and processing method thereof

Abstract

A cognitive technology-based electric power service data process system and a processing method thereof are provided; the method comprises the following steps: continuously learning and analyzing artificial service data; automatically replying client service requests according to the learning result; requesting artificial customer service assistance if no reply matched with the service request can be found in the learning result, and learning and analyzing the newly generated artificial service data. The cognitive technology-based electric power service data process system and method can use the cognition technology to fast process businesses round-the-clock, thus improving artificial business accepting efficiency by times, greatly reducing enterprise manpower resource cost, enhancing emergent event emergency processing capability, and improving client service experiences.

Description

technical field [0001] The invention relates to a power system, in particular to a power service data processing system and a processing method for a customer service system of a power supply enterprise. Background technique [0002] The customer service system of the power supply enterprise actually carries out the power service and marketing work, but with the growth of business volume and the emergence of new business, the functions of the original program can no longer meet the new needs of customers. The main manifestations are: [0003] 1. The business volume is heavy, especially in the case of peak traffic in summer and obstructive weather such as typhoon and cold wave, the speed of consultation and trouble ticket processing is prominent. [0004] 2. Lack of information, such as invisible business processes, difficult to track and analyze fault reports and repairs, incomplete data analysis, and lack of interaction with customers. [0005] 3. Labor limitations, high ...

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Problems solved by technology

[0003] 1. The business volume is heavy, especially in the case of peak traffic in summer and obstructive weather such as typhoon and cold wave, the speed of consultation and fault work order processing is prominent

[0004] 2. Lack of information, such as invisible business processes, difficult to track and analyze fault reports and repairs, incomplete data analysis, lack of interaction with customers, etc.

[0005] 3. Labor limitations, high training costs and long training time for customer service personnel, incomplete personal knowledge, and traditional service methods waste service resources, making customer service personnel in a long-term labor environment of heavy physical strength, simple help and repeated repetitions In the process, it adds a lot of unnecessary labor costs and operating costs to the enterprise

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