Experiential tourism – role and application of micro-targeting in enhancing customer experience, engagement and loyalty

IF 1.1 Q3 INFORMATION SCIENCE & LIBRARY SCIENCE
Prashant Chaudhary, Prabha Kiran, Nilesh Kate, Shailesh B. Pandey
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引用次数: 0

Abstract

Abstract Micro-Targeting has emerged as preferred marketing and branding strategy in the travel and tourism sector across the world. This strategic marketing approach essentially leverages the deep consumer insights in order to design and develop personalised marketing content and recommendations. The digital technologies like Artificial Intelligence (AI), big data analytics, Machine Learning (ML), Augmented Reality (AR), and Virtual Reality etc. are helping the brands in this sector to predict the taste, preferences, priorities, and overall buying behaviour of their target audience. These valuable insights are subsequently utilised for influencing these prospects through hyper-targeted content and advertising. The overarching objective of this research study is to understand the effectiveness of micro-targeting for creating desired customer experience and subsequently its impact on the brand preference and purchase intention. Novelty of this study is reflected in its focus, which is on understanding the role micro-targeting can play in marketing and branding of offerings in experiential tourism category. It was observed that micro-targeting helps companies/brands to create personalised customer experience across different touch-points during the buying process of the high involvement offerings like experiential travel and tourism services.
体验式旅游——微目标在提升顾客体验、参与和忠诚度方面的作用和应用
微目标营销已成为全球旅游行业首选的营销和品牌策略。这种战略营销方法本质上是利用深入的消费者洞察来设计和开发个性化的营销内容和建议。人工智能(AI)、大数据分析、机器学习(ML)、增强现实(AR)和虚拟现实等数字技术正在帮助该领域的品牌预测目标受众的品味、偏好、优先事项和整体购买行为。这些有价值的见解随后被用于通过超针对性的内容和广告来影响这些潜在客户。本研究的首要目标是了解微观目标对创造理想客户体验的有效性,以及随后对品牌偏好和购买意愿的影响。本研究的新颖之处在于其重点在于理解微目标定位在体验旅游品类产品的营销和品牌化中所起的作用。据观察,微目标定位有助于公司/品牌在购买体验式旅行和旅游服务等高参与度产品的过程中,在不同的接触点上创造个性化的客户体验。
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来源期刊
JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES
JOURNAL OF INFORMATION & OPTIMIZATION SCIENCES INFORMATION SCIENCE & LIBRARY SCIENCE-
自引率
21.40%
发文量
88
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