动态发现与识别有价值客户声音的网上聆听方法

Listening Method of Discovering and Identifying Dynamically Valuable Customers' Voice

聆听客户声音的关键是发现对企业有价值的信息。在网络社区中,客户的信息量大且密度高,致使企业聆听声音困难。运用特征筛选和信息融合相结合的特征识别方法,将表征客户特征的有价值的相关数据项经过筛选、分类进行动态地提取和融合,完整地表征和反映有价值的客户信息;同时,采用聚类算法,对具有高、中和低价值的客户特征数据分类过滤,以识别出具有高价值信息特征的客户。该方法对企业聆听网上客户声音,发现其中有价值的信息,以支持其战略和营销决策具有重要的理论意义与实用价值。

The key of listening to our customers is to find the valuable information for an enterprise. In the virtual communities, the information of customers is heavy and has high density, resulting in difficulties in listening to voice of customers. In this paper, a feature recognition method was used, combining feature selection and information fusion to extract and fuse dynamically the valuable data related to customers＇ features through the filtration and classification. Meanwhile, clustering algorithm was used to classify and filter the feature data of high, medium and low value customers to identify the characteristics of high-value information. The method has an important theoretical meaning and practical value for an enterprise to listen to online customers＇ voice and find valuable information to support its strategic and marketing decisions.