Implementation of Digital Marketing in Tourism Industry

Ziakis, Christos; Vlachopoulou, Maro

doi:10.1007/978-3-031-24294-6_23

Cited by 2 publications

(2 citation statements)

References 19 publications

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“…Digital marketing, through online platforms and social media, provides technology and engineering companies with precise opportunities for market positioning and product development. The 2023 Innovative Survey Report on AI in Digital Marketing delved into AI's innovation and disruptive changes in digital marketing, providing robust support for future digital marketing strategies (Ziakis & Vlachopoulou, 2023). The 2022 Sustainable Digital Marketing Practices Report focused on sustainable practices in the digital marketing field and the role of big data and AI in promoting green digital marketing (Thangam & Chavadi, 2023).…”

Section: Introductionmentioning

confidence: 99%

Sustainable Digital Marketing Under Big Data: An AI Random Forest Model Approach

Jin,

Zhong,

Zhao

2024

IEEE Trans. Eng. Manage.

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Digital marketing refers to the process of promoting, selling, and delivering products or services through online platforms and channels using the internet and electronic devices in a digital environment. Its aim is to attract and engage target audiences through various strategies and methods, driving brand promotion and sales growth. The primary objective of this scholarly study is to seamlessly integrate advanced big data analytics and artificial intelligence (AI) technology into the realm of digital marketing, thereby fostering the progression and optimization of sustainable digital marketing practices. Firstly, the characteristics and applications of big data involving vast, diverse, and complex datasets are analyzed. Understanding their attributes and scope of application is essential. Subsequently, a comprehensive investigation into AI-driven learning mechanisms is conducted, culminating in the development of an AI random forest model (RFM) tailored for sustainable digital marketing. Subsequent to this, leveraging a real-world case study involving enterprise X, fundamental customer data is collected and subjected to meticulous analysis. The RFM model, ingeniously crafted in this study, is then deployed to prognosticate the anticipated count of prospective customers for said enterprise. The empirical findings spotlight a pronounced prevalence of university-affiliated individuals across diverse age cohorts. In terms of occupational distribution within the customer base, the categories of workers and educators emerge as dominant, constituting 41% and 31% of the demographic, respectively. Furthermore, the price distribution of patrons exhibits a skewed pattern, whereby the price bracket of 0-150 encompasses 17% of the population, while the range of 150-300 captures a notable 52%. These delineated price bands collectively constitute a substantial proportion, whereas the range exceeding 450 embodies a minority, accounting for less than 20%. Notably, the RFM model devised in this scholarly endeavor demonstrates a remarkable proficiency in accurately projecting forthcoming passenger volumes over a seven-day horizon, significantly surpassing the predictive capability of logistic regression. Evidently, the AI-driven RFM model proffered herein excels in the precise anticipation of target customer counts, thereby furnishing a pragmatic foundation for the intelligent evolution of sustainable digital marketing strategies.

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Section: Introductionmentioning

confidence: 99%

Sustainable Digital Marketing Under Big Data: An AI Random Forest Model Approach

Jin,

Zhong,

Zhao

2024

IEEE Trans. Eng. Manage.

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“…As we navigate through this review, we delve into the multifaceted strategies employed by marketers to harness the potential of Big Data and leverage the capabilities of AI in their digital campaigns. The confluence of these technologies has reshaped the way businesses understand, engage with, and respond to their target audiences (Rathore, 2020, Teixeira & Remondes, 2023, Ziakis & Vlachopoulou, 2023.…”

Section: Introductionmentioning

confidence: 99%

Digital marketing analytics: A review of strategies in the age of big data and AI

Rhoda Adura Adeleye,

Kehinde Feranmi Awonuga,

Onyeka Franca Asuzu

et al. 2024

World J. Adv. Res. Rev.

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Digital Marketing Analytics has become increasingly crucial in the contemporary business landscape, especially with the advent of Big Data and Artificial Intelligence (AI). This paper provides a comprehensive review of the strategies employed in Digital Marketing Analytics within the context of the rapidly evolving landscape of Big Data and AI. In the age of Big Data, businesses are inundated with vast amounts of information, making it imperative for marketers to leverage analytics tools effectively. This review explores the role of Digital Marketing Analytics in harnessing the power of Big Data, enabling marketers to extract actionable insights, identify trends, and make informed decisions. The integration of AI further enhances these capabilities, automating processes and offering predictive analytics for more targeted and personalized marketing strategies. The paper delves into various strategies employed in Digital Marketing Analytics, encompassing data collection, analysis, and interpretation. It discusses the significance of real-time analytics in responding promptly to market changes, optimizing campaigns, and enhancing customer experiences. Additionally, the review addresses the ethical considerations surrounding data privacy and the responsible use of AI in marketing practices. The synergy between Big Data and AI is explored as a catalyst for innovation in digital marketing. Strategies such as machine learning algorithms for customer segmentation, sentiment analysis, and predictive modeling are examined for their potential to revolutionize marketing effectiveness. Moreover, the paper highlights the evolving role of analytics in measuring the return on investment (ROI) of digital marketing initiatives. This review provides insights into the evolving landscape of Digital Marketing Analytics, emphasizing the strategic importance of leveraging Big Data and AI. Businesses that embrace these technologies stand to gain a competitive edge by unlocking valuable insights, optimizing marketing efforts, and staying agile in response to dynamic market conditions.

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Implementation of Digital Marketing in Tourism Industry

Cited by 2 publications

References 19 publications

Sustainable Digital Marketing Under Big Data: An AI Random Forest Model Approach

Sustainable Digital Marketing Under Big Data: An AI Random Forest Model Approach

Digital marketing analytics: A review of strategies in the age of big data and AI

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