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Mapping touchpoint exposure in retailing Implications for developing an omnichannel customer experience

机译:映射零售中的接触点曝光对开发全渠道客户体验的意义

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Purpose - The purpose of this paper is to identify the patterns of customer exposure to touchpoints by segmenting consumers based on the frequency of their exposure, and to understand the relationship of patterns of exposure with customer loyalty intentions (relationship commitment, self-disclosure and positive word-of-mouth) and demographic characteristics. Design/methodology/approach - An online survey of almost 4,000 customers was employed in a supermarket retail setting. Customers were segmented based on their frequency of recalled exposure to multiple touchpoints, by means of a latent class cluster analysis, while considering the role of demographic characteristics. Afterwards, loyalty intentions variables were regressed on the resulting customer segments. Findings - Based on the touchpoint exposure, six customer segments emerge. The main differences across segments relate to the intensity of frequency of exposure and the types of touchpoints customers have been exposed to. Sex, age, shopping role and geographic area of residence are related to segment membership. The identified patterns of exposure explain relationship commitment, self-disclosure and positive word-of-mouth: clusters displaying higher exposure to touchpoints display higher loyalty intentions than clusters displaying lower exposure. Practical implications - The study offers actionable implications for brands and retailers on how to manage touchpoints for implementing omnichannel strategies. Originality/value - As far as the authors know, this study is the first to identify exposure to multiple touchpoints and understand the role of demographics as far as touchpoint exposure is concerned. It also provides interesting findings on the relationship of different combinations of touchpoints with customer loyalty.
机译:目的-本文的目的是通过根据接触频率对消费者进行细分来确定客户接触点的方式,并了解接触方式与客户忠诚度意图(关系承诺,自我披露和积极态度)之间的关系。口碑)和人口特征。设计/方法/方法-在一家超级市场零售店中,对近4,000位客户进行了在线调查。根据潜在召回的接触多个接触点的频率,通过潜在类别聚类分析对客户进行细分,同时考虑人口统计特征的作用。之后,将忠诚度意图变量回归到最终的客户群。调查结果-根据接触点的暴露情况,出现了六个客户群。各个细分市场的主要区别在于曝光频率和客户接触的接触点类型。性别,年龄,购物角色和居住的地理位置与细分受众群成员身份有关。识别出的暴露模式可以说明关系承诺,自我披露和积极的口碑:与接触点较低的组相比,接触点较高的组显示出更高的忠诚度。实际意义-该研究为品牌和零售商在如何管理实施全渠道战略的接触点方面提供了可行的意义。原创性/价值-据作者所知,这项研究是第一个确定暴露于多个接触点并了解人口统计学在接触点暴露方面的作用的研究。它还提供了关于接触点不同组合与客户忠诚度之间关系的有趣发现。

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