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Improving Customer Relationship Management based on Intelligent Analysis of User Behavior Patterns

机译:基于用户行为模式智能分析的客户关系管理

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摘要

A set of regression, cluster analysis, and association rule mining models, is proposed to search for patterns in user behavior regarding marketing campaigns taking into account user characteristics and financially significant metrics. Using the example of two organizations, it was possible to accurately predict the cost of customer acquisition (CPA, cost-per-action). The use of the models proposed allows organizations to improve advertisement settings to increase online advertising efficiency.
机译:提出了一组回归,聚类分析和关联规则挖掘模型,以在考虑到用户特征和财务上重要指标的情况下搜索与营销活动有关的用户行为模式。使用两个组织的示例,可以准确预测客户获取的成本(CPA,每次操作成本)。所建议的模型的使用使组织可以改善广告设置,以提高在线广告效率。

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