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Konstantia Darvidou, Evangelos Siskos: Digital Marketing Tools in the EU Tourism Sector

for feedback from viewers of interactive digital television systems and automatically
customizing services within tourism relationship marketing.

Krabokoukis (2025) considered a neuromarketing and data analytics-based tourism
adaptive digital marketing framework for hotels and destinations. The main components
include attraction, engagement and conversion. Feedback is provided within behaviour
analysis, campaign performance optimization, heatmap insights, and A/B testing
feedback. Several technologies may be integrated: including Google Analytics to track
consumer online behaviour; Hotjar, Crazy Egg, or Smartlook to highlight areas of user
attention; and Tobii Pro and Bitbrain for eye-tracking. Ad-hoc solutions include seasonal
campaigns, segmentation strategies, loyalty programs and crisis response.

Meanwhile, a differentiated approach in feedback analysis is necessary. According to
Mariani et al. (2023), online consumer reviews (at TripAdvisor.com and Booking.com)
in America and Europe depend on online review policies about length of reviews. Better
evaluation is provided to services when the policy is lenient (such as at Booking.com)
in comparison to platforms with stricter policies (TripAdvisor allows to submit only
larger reviews with more than 200 characters, which is a constraint for mobile phone
users). Therefore, reviews at different websites should be evaluated separately during
analysis.Artificial intelligence in marketing is a new field of study. According to a
survey of marketing professionals from tourism companies by Muntean et al. (2024),
AI helps to make digital marketing strategies more adaptive to technological changes
and consumer behaviour. Advantages of AI application are customer segmentation,
personalized content, predictive analytics and automated processes.

Lacárcel (2022) used systemic literature analysis to assess the role of artificial intelligence
in digital marketing strategies. This included data-driven learning for decision support
(Machine Learning, Data Mining, Deep Learning, Support Vector Machine, Q-Learning,
Association Rule Learning and Decision Tree), decision support systems (Decision
Support Systems, Knowledge-Based Systems, Environmental and Decision Support
Systems), social data analysis (Social Media Analytics, Sentiment Analysis and Network
Analysis), artificial intelligence algorithms (Natural Language Processing, K-Nearest
Neighbors algorithm, Multilayer Feedforward, Artificial Neural Networks, Probabilistic
Neural Networks, Artificial Neural Network, R programming language, Bayesian
inference and Data Cleaning), and artificial intelligence strategies for the improvement of
the user experience (Virtual Reality, Chatbots and Self-service kiosks).

Several studies analysed digital marketing tools in specific temporal conditions.
Avraham (2020) used content analysis of digital marketing tools to determine the
strategies used to restore confidence in European destinations after terror attacks in
2014-2019 (““business as usual”, crisis mitigation, initiating events and new attractions,

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