Feature subdivision method for call center customer service staff in mass data

A call center and massive data technology, applied in the field of call center management, can solve problems such as staff cognitive bias and achieve high analysis performance

Inactive Publication Date: 2016-09-07
MERIT DATA CO LTD
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  • Abstract
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Problems solved by technology

[0003] The purpose of the present invention is to provide a method for subdividing the characteristics of call center staff under massive

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  • Feature subdivision method for call center customer service staff in mass data
  • Feature subdivision method for call center customer service staff in mass data
  • Feature subdivision method for call center customer service staff in mass data

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Embodiment Construction

[0051] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

[0052] see figure 1 , which shows a flow chart of a staff management method provided by an embodiment of the present invention, which may include:

[0053] S11: Obtain the KPI index data assessed by the staff of several teams in column M and row S in several years; including connection rate, inbound project share, outbound project work efficiency, average processing time, average queuing time, and one-time problem solving rate , average single call cost, atte...

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Abstract

The invention discloses a feature subdivision method for call center customer service staff in mass data. The feature subdivision method includes: acquiring a preset number of workers; determining a cluster index, and determining data corresponding to the cluster index, of each worker as cluster index data of the worker; performing clustering through a K-Means algorithm according to the cluster index data of each worker so as to obtain a cluster result; and dividing the workers into different classes according to the cluster result to obtain a group result. A call center work management method can automatically adapt worker subdivision work in the mass data, is high in accuracy, and can avoid the situations that classification based on subjective experience does not confirm with actual task performance of the workers.

Description

technical field [0001] The invention relates to the technical field of call center management, and more specifically, relates to a method for subdividing characteristics of call center customer service personnel under massive data. Background technique [0002] In the management of the operators of the call center, it is generally determined subjectively by the manager of the call center or the team manager to roughly divide the operators into several categories. However, in view of the fact that the number of agents in the call center has reached tens of thousands, there will be a big difference between the management's subjective understanding of some operators and their actual work performance, so that it is impossible to reasonably arrange related tasks based on the operator's working ability. Work. Therefore, there is a need for a technology that can help managers better understand the comprehensive performance of their subordinate agents, and better carry out related ...

Claims

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Application Information

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IPC IPC(8): G06F17/30G06K9/62G06Q10/06
CPCG06F16/285G06Q10/06398G06F18/23213
Inventor 程宏亮卢耀宗强劲黄蓉
Owner MERIT DATA CO LTD
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