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首页> 外文期刊>International journal of entrepreneurial behaviour & research >Analysing customer behaviour in mobile app usage
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Analysing customer behaviour in mobile app usage

机译：分析移动应用使用中的客户行为

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摘要

Purpose - Big data produced by mobile apps contains valuable knowledge about customers and markets and have been viewed as productive resources. The purpose of this paper is to propose a multiple methods approach to elicit intelligence and value from big data by analysing the customer behaviour in mobile app usage.Design/methodology/approach - The big data analytical approach is developed using three data mining techniques: RFM(recency, frequency, monetary) analysis, link analysis, and association rule learning. The authors then conduct a case study to apply this approach to analyse the transaction data extracted from a mobile app. Findings - This approach can identify high value and mass customers, and understand their patterns and preferences in using the functions of the mobile app. Such knowledge enables the developer to capture the behaviour of large pools of customers and to improve products and services by mixing and matching the functions and offering personalised promotions and marketing information.Originality/value - The approach used in this study balances complexity with usability, thus facilitating corporate use of big data in making product improvement and customisation decisions. The approach allows developers to gain insights into customer behaviour and function usage preferences by analysing big data. The identified associations between functions can also help developers improve existing, and design new, products and services to satisfy customers' unfulfilled requirements.
机译：目的-移动应用程序产生的大数据包含有关客户和市场的宝贵知识，被视为生产性资源。本文的目的是提出一种通过分析移动应用程序使用中的客户行为从大数据中获取情报和价值的多方法方法。设计/方法/方法-大数据分析方法是使用三种数据挖掘技术开发的：RFM （新近度，频率，货币）分析，链接分析和关联规则学习。然后作者进行案例研究，以应用这种方法来分析从移动应用程序中提取的交易数据。调查结果-这种方法可以识别高价值和大量客户，并了解他们使用移动应用程序功能的方式和偏好。这些知识使开发人员能够捕获大量客户的行为，并通过混合和匹配功能并提供个性化促销和营销信息来改善产品和服务。原始性/价值-本研究中使用的方法在复杂性和可用性之间取得了平衡，因此促进企业使用大数据制定产品改进和定制决策。该方法使开发人员可以通过分析大数据来洞悉客户行为和功能使用偏好。所确定的功能之间的关联还可以帮助开发人员改善现有产品并设计新产品和服务，以满足客户未满足的需求。

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