This paper’s primary objective is to segment the online marketplace of the Canary Islands’ museums by using different conversion funnel metrics. Little systematic research exists on digital user behaviour, and much less is known about how to segment cultural users with structured data from manually extracted and SEO software sources. With this aim in mind, we built a database with data related to the different phases of the conversion funnel of the museums to segment this online museum marketplace. In the findings, not only do we acknowledge the existence of different segments, but we also provide insight into the user’s digital behaviour by considering different metrics from the different phases of the conversion model process (awareness, consideration, conversion and loyalty). The originality of this paper is multifold. Firstly, it estimates the potential optimisation of these websites to improve the digital marketing implemented by the museum sector of the Canary Islands. Secondly, it sheds light on what benchmarking tactics and statistics procedures can be followed to carry out a non-hierarchical segmentation with standardised and comparable data. Thirdly, it contributes to the literature of digital marketing by eclectically combining the conversion funnel model, benchmarking techniques and non-hierarchical segmentation procedures.

中文翻译：

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使用结构化数据对在线博物馆进行细分：以加那利岛在线市场为例

本文的主要目标是通过使用不同的转换漏斗指标来细分加那利群岛博物馆的在线市场。关于数字用户行为的系统研究很少，关于如何使用来自手动提取和 SEO 软件源的结构化数据对文化用户进行细分的知识也少得多。考虑到这一目标，我们建立了一个数据库，其中包含与博物馆转换渠道不同阶段相关的数据，以细分这个在线博物馆市场。在调查结果中，我们不仅承认不同细分市场的存在，而且通过考虑来自转换模型过程不同阶段（意识、考虑、转换和忠诚度）的不同指标，我们还提供了对用户数字行为的洞察。这篇论文的原创性是多方面的。首先，它估计了这些网站的潜在优化，以改善加那利群岛博物馆部门实施的数字营销。其次，它阐明了可以遵循哪些基准策略和统计程序来使用标准化和可比数据进行非分层细分。第三，它通过折衷地结合转换漏斗模型、基准测试技术和非层次分割程序，为数字营销文献做出了贡献。