Customer perception of souvenir clothing ethnic ornaments: Results of using neuromarketing technologies and artificial intelligence

O. Yarosh, Z. Zhavoronkova
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Abstract

Given consumer adaptability to the established marketing incentives, there emerges a need to improve the methods for promoting textile products. The use of neurotechnology allows determining potential ‘anchors’, such as ethnic ornaments, that can be associated with souvenir products. The article focuses on identifying neuromarketing metrics of consumer perception of souvenir clothing ethnic ornaments based on artificial intelligence technology. The foundation of the study resides in the provisions of sensory marketing. General marketing and special neuromarketing research methods were applied. The empirical data are obtained from electroencephalographic (EEG) experiments, a focus group survey (12 respondents), and a preliminary sample interview (90 respondents) conducted in January–February, 2024. We propose biometry-based approaches to neuromarketing consumer evaluation of ethnic patterns for souvenir clothing and reveal customer reactions to different types of ethnic clothing patterns. The strongest emotional responses to particular ornaments are identified based on the EEG test and verbal questioning of the experimental group. The collected data were processed using artificial intelligence to create modern textile designs for souvenir clothing. The results of the study contribute to the understanding of scent neurostimulation’s impact on the perception of clothing elements, as well as the capabilities of artificial intelligence in providing reasoned marketing solutions.
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顾客对纪念品服装民族饰品的感知:使用神经营销技术和人工智能的结果
鉴于消费者对既定营销激励措施的适应性,有必要改进纺织品的促销方法。利用神经技术可以确定潜在的 "锚",如民族饰品,从而与纪念品联系起来。文章的重点是基于人工智能技术,确定消费者对纪念品服装民族饰品感知的神经营销指标。研究的基础在于感官营销的规定。应用了一般营销和特殊神经营销研究方法。实证数据来自 2024 年 1 月至 2 月进行的脑电图(EEG)实验、焦点小组调查(12 名受访者)和初步抽样访谈(90 名受访者)。我们提出了基于生物计量学的神经营销方法,用于消费者对纪念品服装民族图案的评价,并揭示了顾客对不同类型民族服饰图案的反应。根据脑电图测试和对实验组的口头提问,确定了对特定饰品最强烈的情感反应。利用人工智能对收集到的数据进行处理,从而创造出用于纪念品服装的现代纺织品设计。研究结果有助于理解气味神经刺激对服装元素感知的影响,以及人工智能提供合理营销解决方案的能力。
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