Personalisation and Predictive Marketing in a Croatian Tourist Destination: Behavioural Strategies for Enhancing the Tourist Experience

Abstract

This paper explores the role of personalisation and predictive marketing in Croatian tourism and analyses how behavioural strategies can enhance the tourist experience and increase visitor loyalty. In today’s competitive tourism market, personalised marketing strategies have become a key factor in attracting and retaining tourists. Based on the theoretical framework and previous research, hypotheses were formulated on various aspects of behavioural marketing, such as the impact of personalisation on destination choice, the perception of marketing effectiveness by different demographic groups and the correlation between tourists’ satisfaction and their willingness to revisit a destination. The aim of this study was to test six hypotheses relating to the personalisation of marketing messages, demographic factors and their correlation with tourists’ willingness to revisit the destination. Using a quantitative methodology, a survey was conducted among 415 tourists who had visited the Croatian city of Vodice. A total of 257 questionnaires were completed. The data was analysed using descriptive statistics, correlation analysis and regression models to identify the most important factors influencing tourists’ behaviour and preferences. The results show that personalised marketing messages have a positive impact on tourists’ decision to visit the destination. In addition, this study shows that demographic factors such as gender, age and education significantly influence the perception of marketing effectiveness. Tourists who received predictive marketing messages expressed higher satisfaction with their stay and showed a greater willingness to visit the destination again than those who did not receive personalised offers. These results underline the importance of integrating behavioural strategies into marketing activities to build tourist loyalty and improve the overall tourism experience. Based on the research findings, further application of these marketing approaches is recommended to increase competitiveness and attract more loyal tourists.

1. Introduction

The tourism industry is experiencing a dynamic shift in consumer behaviour, with digital transformation enabling increasingly personalised marketing strategies. Personalisation and predictive marketing have become important tools to attract and retain tourists (Chen, 2024). They enable service providers to tailor their offers to the individual preferences of travellers. Research has shown that personalised marketing messages can significantly increase tourist engagement and satisfaction and ultimately influence their decision to return to a destination (Buhalis & Sinarta, 2019; Xiang & Fesenmaier, 2017).

Behavioural strategies in marketing are based on the analysis of consumer patterns and psychological factors that influence decision making. Previous studies have shown that a personalised approach can increase perceived value for tourists, while predictive models allow for more precise targeting based on users’ previous interactions (Gretzel et al., 2020).

In the context of Croatian tourism, where competition between destinations is becoming increasingly intense, the implementation of personalisation and predictive marketing strategies can significantly contribute to increasing tourist loyalty and improving the overall visitor experience. The application of new technologies allows service providers to tailor offers to the specific preferences and needs of individual tourists, resulting in higher satisfaction and loyalty (Mušanović & Šimić, 2022). A 2024 study on young adult tourists in Croatian cities found that tailored marketing strategies, based on demographic segmentation and travel preferences, significantly enhance the tourism experience. The research highlights a clear move toward personalised travel experiences and shows that understanding the preferences of different demographic clusters leads to more effective marketing and increased tourist satisfaction and engagement. (Müller et al., 2024).

Studies have shown that personalised offers can increase tourist satisfaction and spending. Brands that are at the forefront of personalisation report a significant increase in engagement, average spending and overall customer satisfaction (GoDigital, 2024). In addition, younger consumers, such as millennials and Generation Z, are increasingly looking for unique and personalised travel experiences, relying on various sources of information and inspiration (Kaikara, 2024).

The analysis of key factors contributing to the success of marketing strategies in Croatian tourism includes the study of tourists’ demographic characteristics and their reactions to different types of personalised messages. (Dujmović & Vitasović, 2024). Based on empirical data, this research provides deeper insights into the effectiveness of behavioural strategies and offers recommendations for improving marketing activities in the Croatian tourism sector. Automated segmentation systems, for example, enable hoteliers to better understand guests’ interests and preferences and offer highly personalised hotel services that lead to an increase in overnight stays and guest value (Mušanović & Šimić, 2022).

The city of Vodice was chosen as the case study location because it is one of the most popular tourist destinations on the Croatian coast. With a population of approximately 4 million, Croatia registered 20.2 million tourist arrivals and 93.7 million overnight stays in 2024—highlighting that tourists outnumber residents by more than fivefold; most of this tourism activity is concentrated along the Adriatic coast, where Vodice remains a top destination (Croatian Bureau of Statistics, 2025). Located in Šibenik-Knin County, Vodice attracts many domestic and foreign tourists every year thanks to its diverse offerings, including beaches, cultural events, gastronomy and proximity to national parks such as Krka and Kornati. As a destination visited mainly in summer (June to October), Vodice provides a suitable environment to study the impact of personalised and anticipatory marketing strategies in conditions of high tourist demand. The high turnover of visitors of different age groups and nationalities offers a representative sample for analysing the perception of marketing messages and the tourist experience. In addition, Vodice’s well-developed infrastructure and strong competition among accommodation and hospitality providers make it a suitable place to study the impact of behavioural strategies on tourist loyalty. Vodice hosts a variety of hotels, accommodation options, and tourism-related services, reflecting a mature and well-established tourism infrastructure. Although the research is based on data from Vodice, the destination shares several features with many other coastal towns in Croatia, including seasonal tourism patterns, tourist demographics, and service structures. Therefore, the findings may be considered transferable to destinations of similar typology, although not to the national context.

The aim of this study is to gain a better understanding of the impact of personalisation and predictive marketing on the perception and behaviour of tourists in Croatia. The main objectives of this study are as follows:

• To analyse the impact of personalised marketing messages on tourists’ destination choice.
• To examine the role of demographic factors in the perception of behavioural marketing strategies.
• To assess the relationship between tourist satisfaction and willingness to revisit the destination.
• To provide empirical evidence for the effectiveness of predictive marketing models in the tourism sector.

The contribution of this study is to provide concrete recommendations for the improvement of marketing strategies in Croatian tourism to increase the competitiveness of destinations, promote tourist loyalty and ensure sustainable, long-term growth of the sector. The results can serve as a guide for tourism organisations and service providers looking to implement more effective behavioural marketing strategies based on personalisation and data analysis.

Although the results are specific to Vodice, the conclusions can serve as a basis for future research in similar destinations across Croatia, especially those characterised by pronounced seasonality and strong competition.

2. Literature Review

Personalised marketing has become an increasingly important concept in modern tourism, as it enables a more targeted and effective approach to meeting the individual needs of travellers. In a paper by Mitrović et al. (2019), the authors emphasise the importance of personalised marketing and its potential to improve the operations of tourism businesses. They explain how analysing the content that tourists interact with, both when advertising and visiting, can help shape future offers and define precise target groups. This approach helps to better align tourists’ expectations and the services offered by destinations.

In the context of Croatian tourism, Godnov and Redek (2019) examine the role of user-generated content (UGC) in the development of business intelligence. Through a comprehensive analysis of online reviews of Croatian hotels, the study concludes that textual content reveals tourists’ perceptions of service quality and thus provides valuable information for the development of personalised marketing strategies. This research emphasises the benefits of computational linguistics in interpreting customer feedback and predicting future market trends. The integration of digital technologies is also addressed in a study by Perišić Prodan et al. (2024), which examines the impact of digital content marketing (DCM) in wine tourism in Istria. Their findings suggest that the usefulness, entertainment value and overall quality of digital content significantly influence tourist satisfaction and the perceived image of a destination. The study concludes that effective DCM strategies can increase the likelihood of repeat visits and strengthen the emotional connection between tourists and destinations, improving the overall experience.

In terms of destination branding, Parlov et al. (2016) analyse the effectiveness of digital marketing strategies in positioning Croatia as a competitive destination. They compare Croatian efforts with those of other European countries and suggest that more strategic and data-driven digital marketing could improve the country’s visibility and attractiveness. The authors argue that predictive marketing tools, especially those that rely on behavioural data, are crucial for creating tailored experiences that meet the expectations of modern tourists.

Furthermore, Vuić et al. (2020) emphasise the importance of Croatian tourist boards implementing a structured approach to social media marketing. Their research shows that well-planned social media strategies can contribute to the long-term development of tourism and improve tourist engagement through personalised interactions and data-driven communication.

Taken together, these studies provide a solid foundation for understanding how personalised and predictive marketing guided by behavioural data and digital engagement can significantly improve the tourism experience in Croatia. They also show how the strategic use of digital content, user feedback and social media can support more effective destination management and advertising.

H1: 

The impact and effectiveness of personalised marketing strategies varies significantly across demographic characteristics such as gender and age group.

The effectiveness of personalised marketing strategies varies greatly depending on demographic characteristics, especially gender and age. As digital marketing tools become more sophisticated, understanding how different demographic groups respond to targeted campaigns is critical to developing more inclusive and effective strategies.

According to Tifferet and Vilnai-Yavetz (2014), gender plays a crucial role in how consumers interact with personalised online content. Their study shows that women tend to respond more positively to emotionally appealing and relationship-oriented content, while men are more likely to be influenced by utilitarian and targeted marketing messages. These findings highlight the importance of developing personalised strategies that take gender preferences into account in both design and messaging.

In terms of age, Bolton et al. (2013) highlight that different generations—such as Millennials, Generation X and Baby Boomers—have different digital behaviours, higher technology acceptance and expectations of brands. For example, millennials value dynamic, data-driven personalisation via social media platforms, while older consumers prefer more traditional, privacy-conscious approaches. Pappas et al. (2017) examine how personalisation impacts consumer behaviour across different demographic segments and find that younger consumers are more likely to view personalised marketing as useful and relevant, while older consumers are more sceptical and often associate personalisation with intrusive data practices.

In the Croatian context, a study by Jelušić et al. (2021) underlines the important role of digital technologies in shaping consumer behaviour in tourism. Their study shows that the availability and use of digital platforms influence tourists’ decisions, with younger population groups showing a higher propensity to engage with technology-enabled advertising content. This suggests that age is a crucial factor in determining the effectiveness of digital marketing strategies in tourism.

Furthermore, Pavlić and Vukić (2019) examine the decision-making styles of Generation Z consumers in Croatia and find that female members of this cohort are more inclined towards leisure activities and hedonism in their travel decisions while at the same time being less price-sensitive than their male counterparts. These findings highlight the importance of taking gender differences into account when designing personalised marketing campaigns, as they can have a significant impact on consumer engagement and satisfaction.

Taken together, these studies confirm that demographic characteristics, particularly age and gender, have a significant impact on how personalised marketing strategies are received and perceived (Pavlić & Vukić, 2019; Jelušić et al., 2021). By incorporating these insights into campaign planning, tourism marketers can design more effective and inclusive strategies that meet the expectations and preferences of different target groups.

There is also clear evidence that the impact and effectiveness of personalised marketing strategies vary greatly depending on demographic characteristics such as gender and age group. Research consistently emphasises the importance of demographic segmentation when it comes to tailoring marketing efforts for optimal engagement and business results. Young consumers’ e-loyalty to tourism sites is influenced more by internal factors (trust and satisfaction) than external factors (site design and eWOM) (Buhalis et al., 2020).

AI-driven segmentation systems use demographic data (including gender and age) to create meaningful customer groups that enable more precise and effective personalised marketing strategies. These approaches help organisations tailor campaigns to the unique needs and values of different demographic segments, resulting in better engagement and campaign performance (Alijoyo et al., 2025; Babatunde et al., 2024; Manoharan et al., 2024; Kim et al., 2001; Amin, 2024).

Machine learning and decision tree techniques can be used to extract marketing rules that match customer demographics with product categories, enabling targeted recommendations and advertising based on age, gender and other factors (Alijoyo et al., 2025; Manoharan et al., 2024; Kim et al., 2001; Amin, 2024). Empirical studies with different consumer samples (e.g., in Saudi Arabia) show that personalised marketing strategies have a positive impact on consumer engagement and loyalty across different age and gender groups. Respondents from different demographic groups reported positive attitudes and increased engagement with personalised offers and messages. The use of stratified sampling in such studies ensures that the results reflect the differences in effectiveness between demographic strata and confirms that demographic characteristics have an impact on how consumers perceive and respond to personalised marketing (Tarifi & Bakhsh, 2024).

Gender and age group are important demographic factors that influence the effectiveness of personalised marketing. Gender has a significant impact on consumer preferences and responses to personalised offers, as shown in studies where responses to tailored content vary by gender. Similarly, age group influences the level of engagement with personalised content and communication channels. Age shapes consumers’ habits, their media preferences and their openness to personalised marketing messages, as shown by extensive research in the field of digital marketing (Alijoyo et al., 2025; Tarifi & Bakhsh, 2024; Kim et al., 2001).

Generation Z consumers with dominant extraversion, conscientiousness, and neurotic personality traits perceive personalised social media advertisements positively, increasing perceived usefulness and click-through intentions, while openness and agreeableness-dominant consumers perceive them negatively (Saha et al., 2024).

Personalised marketing strategies are most effective when they consider demographic differences such as gender and age. Segmenting and targeting these characteristics lead to increased engagement, satisfaction and loyalty, confirming that demographic differences are a key factor in the success of personalised marketing.

H2: 

There is a significant correlation between the frequency of personalised marketing offers and tourists’ overall satisfaction with their stay.

The increasing use of personalised marketing in tourism has prompted researchers to investigate its direct impact on customer satisfaction and experience. Studies show that personalised communication not only contributes to higher engagement but also to tourists’ overall perception of value and service quality.

A study by Buhalis and Sinarta (2019) shows that smart tourism technologies, when used to offer timely and relevant personalised services, significantly improve customer experience and satisfaction. Personalised offers delivered through digital platforms help tourists feel recognised and valued, which improves emotional connection and loyalty (Buhalis & Sinarta, 2019). Xiang et al. (2017) examine how customer satisfaction is influenced by customised digital interactions, particularly in the hospitality industry. They find that frequent, relevant and unobtrusive marketing messages contribute positively to guests’ experiences, especially when offers are tailored to their preferences and behavioural patterns.

In the context of service quality, Cobos et al. (2009) emphasise the role of real-time data in shaping tourism experiences. Their study suggests that the frequency of targeted communication must be balanced. Too few offers reduce visibility, while too many can overwhelm the tourist and reduce satisfaction. Personalised marketing, especially through digital channels and social media, is highlighted as important for improving business outcomes, building long-term relationships and improving communication with tourists, which can contribute to overall satisfaction with tourism services (Mitrović et al., 2019; Basyuk et al., 2019). Tourism marketing trends include personalisation, digitalisation, AI, socio-ethical concepts and creative marketing, resulting in new travel products and services that meet consumer needs (Zhuravleva et al., 2024).

The use of personalised emails, advertising and content helps tourism businesses to build effective and lasting relationships with their customers, which is a key factor in customer satisfaction and loyalty (Basyuk et al., 2019). Website personalisation on tourism websites has a significant impact on first impressions, perceived quality and ultimately on loyalty and purchase intentions of young consumers, suggesting a positive relationship between personalisation and satisfaction (Martínez-González & Álvarez-Albelo, 2021).

Digital marketing interactions, including personalised content and user-friendly online information, are important determinants of tourist satisfaction and behavioural intentions, such as the intention to revisit or recommend a destination. Satisfaction acts as a mediator between tourists’ perceptions of digital marketing content and their behavioural intentions, suggesting that positive digital interactions (which may include personalised offers) can increase satisfaction (Armutcu et al., 2023). Recommendation systems and personalised travel planning tools have been shown to improve the tourist experience by tailoring recommendations to individual needs, which can increase satisfaction and positive word of mouth (I. Y. Choi et al., 2019; Kabassi, 2010). Customising experiential marketing initiatives to different tourist segments is recommended to better manage tourism experiences and potentially increase satisfaction (Le et al., 2018).

In Croatian tourism, Mandić and Petrić (2021) investigate how the location and characteristics of nature reserves influence hotel pricing, providing insights into sustainable tourism development. Their research shows that hotels near protected areas can utilise this proximity in their marketing strategies to attract environmentally conscious tourists. Similarly, Perišić Prodan et al. (2024) confirm that useful and engaging digital content, including personalised marketing, positively influences tourists’ perceived image of a destination and their intention to revisit it. The emotional and practical relevance of marketing communication seems to have a direct impact on satisfaction.

Personalised marketing is increasingly used in tourism to tailor offers and communications to individual travellers. There is evidence that personalised marketing and personalised recommendations can improve tourist satisfaction by increasing the relevance and quality of the experience. Personalised tourism recommendations, especially those that use digital tools and artificial intelligence, increase tourists’ trust and positive attitude towards the service, which is associated with higher satisfaction (Yang et al., 2023). Personalisation in international tourism enhances the tourist experience by providing unique solutions adapted to personal preferences, increasing customer satisfaction (Simakin, 2025).

Personalised marketing, especially through social networks and digital channels, strengthens communication between tourism providers and tourists. This approach helps build long-term relationships and improves overall business performance, which is closely linked to customer satisfaction (Mitrović et al., 2019). The use of personalised marketing strategies, including targeted content on social media, plays an important role in tourists’ choice of destination and perception of the destination’s offerings (Armutcu et al., 2023; Mitrović et al., 2019). Social media strategies in tourism destinations can help them remain competitive by interacting with visitors and monitoring their opinions and evaluations (Kiráľová & Pavlíčeka, 2015).

Tourist satisfaction has a significant effect on the intention to recommend a destination to others, indicating that satisfied tourists are more likely to share their positive experiences and encourage others to visit (Widjanarko et al., 2025). In addition, personalised recommendation systems help tourists navigate the overwhelming number of online offerings, making it easier to find suitable options and increasing satisfaction with the decision-making process (Kabassi, 2010). The extent to which tourists perceive marketing and recommendations as tailored to their needs directly influences their satisfaction and trust in the service (Yang et al., 2023).

Overall, these studies support the hypothesis that there is a strong relationship between the frequency and relevance of personalised marketing messages and overall tourist satisfaction, especially when personalisation is meaningful, data-driven and non-intrusive. Personalised marketing, especially when delivered through digital channels and recommendation systems, is associated with higher tourist satisfaction. By making offers and information more relevant and accessible, personalised marketing improves the overall travel experience and increases the likelihood of positive reviews and repeat visits.

H3: 

Tourists who are exposed to marketing messages based on their previous interests are more likely to revisit a destination or share the experience with others.

Personalising marketing messages based on tourists’ past behaviour and preferences play a key role in destination retention and word of mouth (WOM). Research has shown that tourists who recognise that offers and messages reflect their previous interests are more likely to form an emotional attachment to the destination and continue to engage with it. Šegota et al. (2022) examine how residents’ self-congruence (the match between their self-image and the image of their city), satisfaction with the place, engagement and expectations influence their voluntary WOM behaviour about their city as a destination. They find that satisfaction with the place and expectations mainly influence positive word of mouth in a one-to-one ratio, while commitment to the place strongly influences both word of mouth in a one-to-many ratio and word of mouth in a many-to-many ratio. Actual and ideal self-congruence affect place satisfaction, commitment, and expectations, and the dimensions of social self-congruence are related to person-to-person word of mouth. The results show that different types of WOM are motivated by different psychological mechanisms and emphasise the importance of residents as brand ambassadors of destinations.

Zhang et al. (2025) conducted a study on the impact of digital transformation on visitor engagement and their willingness to recommend a destination to others. Their findings suggest that technologies such as virtual and augmented reality improve visitor satisfaction, engagement and the perception of authenticity, which in turn increases the likelihood that visitors will recommend the destination to others. These results support the broader theory of customer-centric marketing communication, which emphasises the importance of relevance and continuity in communicating with tourists. Pappas et al. (2017) emphasise that personalisation promotes shared value creation, especially when marketing messages are tailored to individual preferences. This personalised engagement encourages tourists to engage more deeply with a destination and increases the likelihood of repeat visits and referrals. Similarly, Gretzel et al. (2015) argue that digital platforms that can track and analyse tourists’ past behaviour can be powerful tools to encourage repeat visits. These platforms enable destination marketers to create highly relevant messages that connect to tourists’ memories and emotions, thus strengthening loyalty.

Personalised marketing in tourism aims to increase visitor engagement by tailoring messages to individual interests. There is evidence that personalised or emotionally appealing marketing messages can positively influence tourists’ attitudes and the likelihood that they will recommend or revisit a destination. Promoting a destination based on a tourist’s previous interests or search behaviour is more effective. The design and appeal of these messages, especially when tailored to the recipient’s psychological distance from the trip (how soon or how far away the trip is), can significantly influence consumer response and engagement with the destination (S. Wang & Lehto, 2020). Marketing messages that target emotions or are created by users (e.g., reviews, testimonials) are more effective than generic, rational or destination-created messages. These types of messages are particularly effective in improving tourists’ attitudes and their intention to recommend the destination to others, even after unsatisfactory experiences. Tourists who are exposed to emotionally appealing or personalised messages are more likely to recommend the destination to others, especially if these messages help to make their experiences positive (S. Wang et al., 2017).

While there is little direct evidence on revisit rates, the improved attitude and increased engagement that result from personalised and emotionally engaging messages suggest that the likelihood of revisiting the destination is higher (S. Wang & Lehto, 2020; S. Wang et al., 2017). Different types of marketing messages have different effects on consumer behaviour, especially in terms of recommendations and revisit intentions. Personalised and interest-based messages have been shown to strongly encourage consumers to recommend and increase the likelihood of revisiting (S. Wang & Lehto, 2020). Emotional and user-generated messages also have a strong influence on consumers’ recommendation and revisit intent. In contrast, generic and rationally formulated marketing messages have a weaker effect and are less likely to motivate referrals or revisit intentions (S. Wang et al., 2017).

In the Croatian context, Pandža Bajs (2015) emphasises that tourist satisfaction and perceived value are the most important determinants of revisit intention. Although her study does not focus exclusively on personalised digital marketing, the results suggest that positive experiences and high perceived value increase the likelihood that tourists will return and recommend the destination to others. These findings support the hypothesis that, by increasing satisfaction and perceived value, personalised marketing approaches can significantly influence tourists’ post-visit behaviour, including their willingness to share positive experiences and promote the destination.

There is clear evidence that marketing messages tailored to tourists’ interests or utilising emotional/user-generated content increase the likelihood that they will share their experience with others and recommend the destination to others. These strategies are also likely to increase revisit intent, making personalised marketing a valuable tourism promotion tool. This type of marketing is increasingly being used in tourism to increase tourist engagement and encourage repeat visits. The study shows that personalised marketing strategies increase tourists’ engagement, loyalty and intention to revisit. Tourists respond positively to personalised tourism recommendations, which increase their trust in the technology and their positive attitude towards the recommended content. This leads to higher loyalty to tourism platforms and services (Yang et al., 2023).

Personalisation of tourism websites significantly improves first impressions, perceived quality and online purchase intentions, which contributes to greater customer loyalty and engagement, especially among younger travellers (Martínez-González & Álvarez-Albelo, 2021).

High-quality, user-friendly and personalised digital marketing content has a direct impact on tourists’ intentions to visit and revisit destinations. Satisfaction with the first visit and positive interactions with digital marketing increase the likelihood of revisiting and sharing experiences online (Armutcu et al., 2023). Personalisation, combined with a strong first impression and good website design, leads to stronger loyalty towards tourism websites, which is closely linked to higher revisit intentions (Martínez-González & Álvarez-Albelo, 2021). Personalised recommendations have a strong impact on user engagement and revisit intent. Customised suggestions based on users’ interests contribute to greater satisfaction and increase the likelihood of a return visit or continued use of services (Yang et al., 2023; Martínez-González & Álvarez-Albelo, 2021).

High-quality digital marketing also has a significant effect on both dimensions by increasing engagement and positively influencing the intention to revisit the offer. This emphasises the importance of strategic, content-rich online communication (Armutcu et al., 2023; Martínez-González & Álvarez-Albelo, 2021). Finally, user satisfaction is clearly associated with high levels of engagement and a greater intention to return, emphasising the essential role of user experience in digital marketing efforts (Armutcu et al., 2023).

Personalised marketing in tourism through tailored recommendations, personalised websites and high-quality digital content significantly boosts tourist engagement and increases the likelihood that they will visit a destination again. These strategies also promote loyalty and encourage tourists to share their experiences, thus extending the reach of the destination.

H4: 

The source of destination information significantly influences the likelihood of exposure to personalised marketing messages.

The source through which tourists access information about their destination, such as search engines, social media, travel blogs or booking platforms, plays a crucial role in the type and scope of personalised marketing messages they receive. Various studies suggest that certain channels are more likely to track user behaviour and therefore enable more precise targeting. According to Xiang et al. (2015), digital information sources not only serve as tools for travel planning but also as mechanisms for collecting behavioural data. This data is then used for personalised retargeting and content customisation, often without the tourist being fully aware of it. Gretzel and Yoo (2008) emphasise that user-generated content platforms such as TripAdvisor or travel blogs encourage the sharing of data and the expression of opinions, which in turn support strategies for targeted behaviour management. The source thus becomes not only an information medium but also a basis for building personalised marketing stories.

Mariani et al. (2016) examine the use of social media platforms and find that these channels have a particular influence on the personalisation of tourism offers. As users tend to voluntarily engage with destination content, these platforms collect extensive data sets that enable tailored advertising and sponsored messages.

In the Croatian tourism context, Mandić and Petrić (2021) analyse the impact of digital marketing strategies on tourist behaviour and destination image. Their research shows how personalised digital communication, especially via social media and online platforms, increases tourist engagement and their intention to recommend Croatian destinations. The study confirms that tailored marketing messages based on tourists’ preferences increase satisfaction and loyalty.

These results support the hypothesis that the source of information about the destination plays a crucial role in the likelihood of receiving personalised marketing, both in terms of frequency and relevance. So, whether tourists receive personalised offers depends not only on their preferences but also on the digital environment they initially interact with.

There is also evidence that the source of information about the destination can have a significant impact on exposure to personalised marketing messages and their effectiveness. The way in which information is sourced, presented and personalised affects how likely consumers are to perceive, engage with and respond to the marketing content. The nature and credibility of the information source (e.g., specialised websites vs. general websites, the presence of recommendations, user reviews) shape tourists’ perception of credibility and influence their behavioural intentions towards destinations, which in turn can influence engagement with marketing messages (Y. Choi et al., 2018). Familiarity with a destination changes the sources that travellers rely on. For example, less familiar travellers are more likely to seek out in-person or online sources, which are often channels for personalised marketing (Gursoy et al., 2018).

Personalised content (such as using the recipient’s name or tailoring messages to user profiles) increases the likelihood that consumers will open, read and interact with marketing messages, leading to higher contact and engagement rates (Sahni et al., 2016; Shareef et al., 2017; Matloka & Buhalis, 2010).

User Personalised Content (UPC) and context-based marketing use data from various sources to deliver tailored information, increasing the relevance and reach of marketing messages to travellers (Buhalis & Foerste, 2015; Matloka & Buhalis, 2010).

Mobile and digital channels that use personalisation and segmentation are more effective in reaching and targeting consumers, especially when the content matches users’ preferences and context (Buhalis & Foerste, 2015; Shareef et al., 2017; Matloka & Buhalis, 2010).

Social media and digital information sources play an important role in influencing travel decisions and loyalty, with different platforms and content types (emotional vs. informational) influencing user engagement and exposure to marketing (Almeida-Santana & Moreno-Gil, 2017; Molina et al., 2020). The influence of social media as a source varies depending on the profile of the traveller and their familiarity with the destination, but it remains an important channel for personalised marketing (Almeida-Santana & Moreno-Gil, 2017; Gursoy et al., 2018; Molina et al., 2020). Multimodal credibility assessment of user-generated content (UGC) considers audio, video and images in addition to text, aiding in identifying fake news, suspicious profiles and fake reviews (Choudhary et al., 2024).

The source and personalisation of destination information are key factors that influence how consumers engage with marketing messages. Personalised and contextualised content provided through trusted and relevant sources increases the likelihood that consumers will engage with the messages and that they will be effective.

H5: 

The source of information about the destination significantly influences the level of satisfaction with the stay.

The way tourists inform themselves before travelling plays a crucial role in shaping their expectations, their decisions and ultimately their satisfaction with the travel experience. Numerous studies have confirmed that the source of information can influence both the perceived image of a destination and the consistency of this perception with the actual experience.

Choe et al. (2017) argue that online sources, especially user-generated content such as reviews and social media posts, provide a more emotional and experiential image of a destination. When the information comes from trusted peers or influencers, tourists are more likely to feel confident in their decisions and are more satisfied. Bigné Alcañiz et al. (2009) emphasise that the congruence between the information before the trip and the actual experience correlates strongly with satisfaction after the visit. Their research shows that tourists who rely on informative, detailed and realistic sources are more likely to have their expectations met, leading to a more positive overall evaluation of the destination.

Xiang et al. (2015) discuss how the digital transformation of information sources has changed tourist behaviour and satisfaction outcomes. They conclude that personalised digital platforms such as customised travel apps and interactive websites tend to increase satisfaction as they reduce uncertainty and improve the efficiency of travel planning.

In a study focusing on Croatian tourism, Perišić Prodan et al. (2024) confirm that the source and format of destination content–especially if it meets travellers’ expectations–significantly influences perceived quality and satisfaction. Their results show that official sources combined with personalised digital content provide the most reliable and satisfying experience for modern tourists.

Taken together, these findings support the hypothesis that the type and quality of information sources about a destination directly affect satisfaction by influencing expectations, trust and planning accuracy.

There is clear evidence that the source and quality of information about a destination significantly influence tourists’ satisfaction with their stay. Information sources—especially their credibility, reliability and satisfaction—play a key role in shaping expectations, experiences and overall satisfaction with a destination.

Satisfaction with information from the internet is positively related to satisfaction with the destination. This effect is stronger for tourists with less prior experience with the destination or the internet itself (Castañeda et al., 2007; Chang & Wang, 2019; Sanz-Blas et al., 2017). Information from electronic word of mouth (e.g., reviews, social media) increases satisfaction and intention to revisit the destination, while information from online advertising can sometimes lead to negative disappointment and lower satisfaction if expectations are not met (Chang & Wang, 2019; Cho et al., 2014). Tourists who rely on official government sources, word of mouth and credible internet advertising report higher satisfaction, which is likely due to the perceived reliability of these sources (Cho et al., 2014). The importance of different sources of information varies depending on how familiar travellers are with the destination. Less familiar travellers rely more on in-person and online sources, which can influence their satisfaction (Gursoy et al., 2018; Sanz-Blas et al., 2017).

Destinations that provide high-quality, easily accessible information tend to receive higher satisfaction ratings from tourists, emphasising the essential role of information in the overall experience (Tavares et al., 2018). The source of information not only affects satisfaction but also influences tourists’ intentions to revisit the destination and recommend it to others (Sanz-Blas et al., 2017; Chang & Wang, 2019; Cho et al., 2014). Different types of information sources influence tourist satisfaction in different ways. In general, the use of the internet as an information source has a positive effect on user satisfaction, as shown by several studies (Castañeda et al., 2007; Chang & Wang, 2019; Sanz-Blas et al., 2017). Electronic word of mouth has a strong positive influence, as users tend to trust information that comes from other consumers (Chang & Wang, 2019; Cho et al., 2014). In contrast, online advertising tends to have a mixed or even negative impact on satisfaction, possibly due to its perceived intrusiveness or lack of authenticity (Chang & Wang, 2019). Formal or governmental sources of information contribute positively to satisfaction, likely due to their perceived credibility and accuracy (Cho et al., 2014).

Finally, the quality and availability of information also play a positive role in shaping satisfaction, emphasising the importance of clear, timely and relevant content (Tavares et al., 2018). There is clear evidence that the source and quality of information about a destination have a significant influence on tourist satisfaction. Reliable, credible and user-friendly sources of information, especially electronic word of mouth and formal channels, increase satisfaction, while misleading or overly polished advertising can have the opposite effect.

H6: 

Tourists who are exposed to personalised marketing messages will recommend the destination significantly more than those who are not.

It has been proven that personalised marketing not only influences tourists’ decision-making processes but also their willingness to recommend destinations to others. The link between personalisation and word of mouth (WOM) is particularly important in tourism, where reputation and recommendations play a central role in attracting new visitors.

According to Bagheri et al. (2024), “increased well-being has a positive impact on tourists’ satisfaction and their intention to revisit a destination”, which emphasises the importance of designing experiences that promote emotional connection and personal value.

Yang et al. (2023) investigate how personalised tourism recommendations influence tourists’ user experience and behavioural intentions. Their study shows that travellers who receive destination recommendations tailored to their interests and preferences are more likely to feel emotionally connected to the place. This feeling of connection significantly increases the likelihood of recommending the destination to others and sharing positive experiences online. The findings highlight the role of digital personalisation in driving tourist engagement and improving post-visit behaviour. Tsiotsou and Ratten (2010) emphasise the importance of personalised marketing approaches as a future research direction in tourism marketing. Although their study does not focus exclusively on personalised recommendations, it shows that personalised marketing strategies can significantly influence consumer behaviour in the tourism industry. When tourists feel that a service or communication is tailored to their preferences, they are more likely to engage in positive word of mouth marketing and build a stronger emotional bond with the destination.

These studies also confirm that personalised marketing significantly increases the likelihood of tourists recommending a destination to others, underlining the role of tailored communication in promoting word of mouth.

In the context of Croatian tourism, Pivčević et al. (2020) examine regional similarities and differences in the sustainability of tourism development across the Mediterranean, including Croatia. While their research does not focus exclusively on personalised marketing, it highlights the importance of adapting tourism strategies to local preferences and tourist behaviour. The findings suggest that a personalised and tailored approach to tourists’ expectations, particularly through digital communication, can contribute to long-term sustainability and improve the perceived value of destinations. These findings support the notion that personalisation is not only a marketing tactic but also a tool to promote sustainable tourism development.

There is growing evidence that personalised marketing messages and recommendation systems in tourism can positively influence tourists’ attitudes, satisfaction and behavioural intentions, including the likelihood that they will recommend a destination to others. However, there is little direct evidence that personalised marketing leads to a significant increase in the recommendation rate, even though several studies suggest a strong correlation.

Systems that tailor travel suggestions to individual preferences improve user satisfaction and engagement, which is closely linked to positive word of mouth and recommendation behaviour (I. Y. Choi et al., 2019; Kabassi, 2010; X. Wang, 2020; Esmaeili et al., 2020; Yuan & Zheng, 2024).

High-quality, user-friendly digital marketing interactions and content have a direct effect on tourists’ intentions to recommend destinations online (electronic word of mouth or eWOM). Destination satisfaction and digital marketing experiences act as mediators and strengthen the relationship between personalised content and recommendation intentions (Armutcu et al., 2023).

Personalisation of tourism websites improves first impressions and perceived quality, which in turn increases purchase intentions and loyalty factors that are often associated with higher recommendation rates, especially among younger consumers (Martínez-González & Álvarez-Albelo, 2021). Personalised recommendation systems automate and amplify WOM effects and outperform non-personalised systems when it comes to encouraging tourists to share and recommend their experiences (I. Y. Choi et al., 2019; Esmaeili et al., 2020). Marketing messages that are emotionally appealing or user-generated are more effective in improving tourists’ attitude and intentions to recommend, especially after unsatisfactory experiences (S. Wang et al., 2017). Various personalisation approaches have a strong influence on users’ recommendations and behavioural intentions. Personalised recommendation systems have been shown to increase user satisfaction and stimulate positive word of mouth, as shown in several studies (Y. Choi et al., 2018; Kabassi, 2010; Esmaeili et al., 2020; Yuan & Zheng, 2024). Interactions in digital marketing environments lead to a higher level of eWOM and a higher intention to revisit (Armutcu et al., 2023). Website personalisation contributes to increased user engagement and purchase intent, which further strengthens loyalty towards a destination or brand (Martínez-González & Álvarez-Albelo, 2021). Finally, emotional and user-generated content has a strong influence on the intention to recommend, as such content is perceived as authentic and personally relevant (S. Wang et al., 2017).

While there is little direct experimental evidence on the effect of personalised marketing on tourist recommendations, several studies suggest that personalisation of marketing and digital experiences leads to higher satisfaction, loyalty and positive word of mouth, supporting the claim that personalised marketing messages increase the likelihood that tourists will recommend a destination to others.

3. Materials and Methods

3.1. Quantitative Research Design

This study uses a quantitative research design to investigate the impact of personalised and predictive marketing strategies on tourists’ satisfaction and behavioural intention to revisit or recommend destinations in the context of Croatian tourism. Quantitative research allows for the identification of statistically significant relationships between variables and is often used to generalise findings across populations (Bryman, 2016; Creswell & Creswell, 2018).

In tourism research, digital marketing has proven to be an important tool to understand and increase visitor engagement, satisfaction and loyalty. Veseli et al. (2025) emphasise that personalised digital strategies not only promote destinations but also contribute to sustainable tourism development by fostering a deeper connection with tourists. Their study highlights that such approaches significantly influence tourists’ behaviour, including repeat visits and the likelihood to recommend destinations to others.

The present study follows this model and focuses on measuring the relationship between personalised messages and tourist behaviour in Vodice, a popular Croatian coastal destination.

3.2. Data Collection Procedure

The primary data source for this study was a standardised questionnaire in English, which was used to collect information on how tourists were exposed to personalised marketing, how satisfied they were with their stay and what their behavioural intentions were, e.g., likelihood to revisit or recommend the destination. The data collection was conducted from June to October 2024, i.e., during the peak tourist season in Vodice.

The questionnaire was distributed through direct personal contact with small and medium-sized private accommodation facilities and via e-mail communication. Hosts were asked to share the questionnaire with guests who had recently stayed in their accommodation. A total of 415 tourists were invited to participate, of which 257 completed the questionnaire, representing a valid response rate of 61.9 per cent. The sample included both domestic and international visitors, allowing a wide range of demographic characteristics and travel motivations to be captured, which is essential for hypothesis testing in this type of behavioural research.

3.3. Measurement Scales

The questionnaire consisted of several sections based on previous studies on the personalisation of marketing and consumer behaviour. Variables such as satisfaction, marketing exposure and behavioural intention to revisit or recommend destination were measured using five-point Likert scales ranging from 1 (“strongly disagree”) to 5 (“strongly agree”), as recommended by Hair et al. (2022). Demographic information such as age, gender, education and sources of information was recorded using nominal and ordinal scales.

The measures were derived from empirical studies and adapted to the tourism context in Croatia. The questionnaire captured whether tourists perceived personalised marketing messages, including those based on their previous interests, and how these messages influenced their perception of the destination. Respondents were also asked to indicate how they had discovered the destination (e.g., internet, media, recommendations), which provided insight into the role of information sources in personalisation. Prior to final distribution, the questionnaire was pretested to ensure clarity and internal consistency (Pallant, 2020).

3.4. Data Analysis

The data collected were analysed using IBM SPSS Statistics, Version 28 (IBM Corp., Armonk, NY, USA) and R version 4.2.1 (R Core Team, 2022), both widely recognised for their robustness in social science research and their ability to handle non-parametric data (Pallant, 2020). The initial analysis included descriptive statistics to summarise sample characteristics and overall response patterns.

To test the hypotheses of this study, non-parametric tests were selected due to the ordinal nature of the key variables. Spearman’s rank order correlation coefficient was used to examine the relationships between marketing personalisation and satisfaction. Differences between independent groups, such as gender and exposure to marketing, were tested using the Mann–Whitney U test, while comparisons between more than two groups, such as age categories or information sources, were assessed using the Kruskal–Wallis test. Chi-square tests were used to analyse associations between categorical variables such as exposure to advertising messages and the likelihood of a destination recommendation. In addition, regression analysis was used to identify significant predictors of tourist satisfaction and behavioural intention.

This multi-layered analytical approach enabled a comprehensive examination of the data and ensured methodological consistency with previous behavioural and marketing studies in tourism (Perišić Prodan et al., 2024).

4. Results

H1: 

The impact and effectiveness of personalised marketing strategies vary significantly across demographic characteristics such as gender and age group.

We first analysed whether there was a statistically significant difference in the effect of these strategies between the age groups. The sample is divided into six age categories: 18–24 (1), 25–34 (2), 35–44 (3), 45–54 (4), 55–64 (5), and 65+ (6).

A non-parametric Kruskal–Wallis test was conducted to determine whether there were statistically significant differences in responses to the question of whether personalised messages influenced tourists’ decision to visit the destination. Responses were measured using an ordinal scale: No Influence, Slight Influence, Moderate Influence and Strong Influence.

The aim was to determine whether one age group differed significantly from the others in their responses. In

Table 1. Impact of personalised marketing on destination choice by age group. Kruskal–Wallis test results.

Ranks
	Age Group	N	Mean Rank
Offer Impact	(1) 18–24	49	123.43
	(2) 25–34	73	146.08
	(3) 35–44	45	128.90
	(4) 45–54	46	119.54
	(5) 55–64	31	111.97
	(6) 65+	13	128.50
	Total	257
Test Statistics a,b
		Offer Impact
Kruskal–Wallis H		8.483
df		5
Asymp. Sig.		0.132

^a Kruskal–Wallis test; ^b Grouping variable: Age group.

, thehe Kruskal–Wallis test yielded the following results:

The calculated p-value is 0.132, which is above the significance threshold of 0.05. From this we conclude that there are no statistically significant differences in the distribution of answers to this question between the age groups.

Next, we applied the same procedure to analyse possible differences in terms of gender. As there are two gender groups in the sample, we used the non-parametric Mann–Whitney U test to determine whether there are significant differences in the distribution of responses between male and female participants.

The test revealed a statistically significant difference between male and female respondents (U = 6804.5, Z = −2.543, p = 0.011). Women stated that they were more influenced by personalised offers than men, which is reflected in higher average values. This supports the hypothesis that gender plays a role in the effectiveness of personalised marketing strategies. Results are presented in

Table 2. Gender differences in the impact of personalised marketing. Mann–Whitney U test results.

Ranks
	Gender	N	Mean Rank	Sum of Ranks
Offer Impact	Male	112	117.25	13,132.50
	Female	145	138.07	20,020.50
	Total	257
Test Statistics a
			Offer Impact
Mann–Whitney U			6804.500
Wilcoxon W			13,132.500
Z			−2.543
Asymp. Sig. (2-tailed)			0.011

^a Grouping variable: Gender.

.

The p-value of 0.011 is statistically significant and indicates that there are significant differences in the effect of personalised offers between male and female respondents. Personalised offers appear to have a significantly stronger influence on women. This can be seen from the mean ranking values, where the female group (group 2) has a higher average. This trend is illustrated in the following graph.

The grouped bar chart (Figure 1) shows that the proportion of women who stated that they had been “slightly influenced” by personalised offers was less than half that of men. Furthermore, personalised offers had a strong influence on 26.2% of female respondents, compared to only 11.6% of male respondents.

H2: 

There is a significant correlation between the frequency of personalised marketing messages and tourists’ overall satisfaction with their stay.

To explore the relationship between marketing communication and tourist satisfaction, we investigated how frequently personalised advertising messages appear and how this affects the overall visitor experience. As satisfaction is a key indicator of tourist behaviour and loyalty, understanding its link with marketing presence provides valuable insights for optimising strategy. The following

Table 3. Correlations between promotional messages, satisfaction, and message frequency. Spearman’s rho coefficients.

Correlations
			Promotional Messages	Satisfaction with Stay	Frequency of Marketing Messages
Spearman’s rho	Promotional Messages	Correlation Coefficient	1.000	−0.118 **	−0.073
		Sig. (2-tailed)		−0.007	−0.094
		N	522	522	522
	Satisfaction with Stay	Correlation Coefficient	−0.118 **	1.000	−0.040
		Sig. (2-tailed)	0.007		0.363
		N	522	522	522
	Frequency of Marketing Messages	Correlation Coefficient	−0.073	−0.040	1.000
		Sig. (2-tailed)	0.094	0.363
		N	522	522	522

** Correlation is significant at the 0.01 level (2-tailed).

shows the results of a Spearman correlation analysis.

The Spearman correlation was used to test the relationship between satisfaction and perceived exposure to marketing messages. A weak but statistically significant negative correlation was found between the frequency of perceived exposure to marketing messages and tourist satisfaction (ρ = −0.118, p = 0.007), suggesting that more frequent exposure may be associated with slightly lower satisfaction levels. However, the correlation is weak and does not allow a causal conclusion to be drawn.

The relationship between perceived personalisation and satisfaction was also investigated.

Table 4. Correlations between tourist satisfaction, offer impact, and personalised messages. Spearman’s rho coefficients.

Correlations
			Satisfaction with Stay	Offer Impact	Personalised Offers
Spearman’s rho	Satisfaction with Stay	Correlation Coefficient	1.000	0.049	0.277 **
		Sig. (2-tailed)		0.268	0.000
		N	522	522	522
	Offer Impact	Correlation Coefficient	0.049	1.000	−0.127 **
		Sig. (2-tailed)	0.268		0.004
		N	522	522	522
	Personalised Offers	Correlation Coefficient	0.277 **	−0.127 **	1.000
		Sig. (2-tailed)	0.000	0.004
		N	522	522	522

** Correlation is significant at the 0.01 level (2-tailed).

shows positive correlation found between the perception of personalised offers and overall satisfaction (ρ = 0.277, p < 0.001), suggesting that tourists who reported having seen personalised offers tended to express higher levels of satisfaction. Although the correlation was statistically significant, it remained only moderately strong, indicating the possible influence of additional, unmeasured factors on tourist satisfaction.

H3: 

Tourists who are exposed to marketing messages based on their previous interests are more likely to revisit a destination or share the experience with others.

To investigate whether there was a statistically significant correlation between the perception of personalised offers and the likelihood of recommending the destination to others, a chi-square test for independence was conducted. The results in

Table 5. Relationship between personalised offers and destination recommendation. Chi-square test and crosstabulation.

Personalised Offers * Destination Recommendation Crosstabulation
Count
			Destination Recommendation		Total
			Yes	No
Personalised Offers		Yes	151	18	169
		No	73	15	88
Total			224	33	257
Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)	Exact Sig. (2-sided)	Exact Sig. (1-sided)
Pearson Chi-Square	2.114 a	1	0.146
Continuity Correction b	1.582	1	0.209
Likelihood Ratio	2.042	1	0.153
Fisher’s Exact Test				0.170	0.106
N of Valid Cases	257

^a In total, 0 cells (0.0%) have an expected count of less than 5. The minimum expected count is 11.30. ^b Computed only for a 2 × 2 table. * means “in relation to”.

are as follows:

The p-value is 0.146, which means that there is no statistically significant difference in the likelihood of a tourist recommending the destination depending on whether or not they have seen personalised marketing offers.

However, to investigate whether there are statistically significant differences in the level of satisfaction between two groups—those who have seen personalised offers (Group 1) and those who have not (Group 0)—a non-parametric Mann–Whitney U-test was conducted.

As shown in

Table 6. Differences in tourist satisfaction based on exposure to personalised offers. Mann–Whitney U test results.

Ranks
	Personalised Offers	N	Mean Rank	Sum of Ranks
Stay Satisfaction	0	88	100.84	8874.00
	1	169	143.66	24,279.00
	Total	257
Test Statistics a
		Stay Satisfaction
Mann–Whitney U		4958.000
Wilcoxon W		8874.000
Z		−4.976
Asymp. Sig. (2-tailed)		0.000

^a Grouping variable: Personalised offers.

, the analysis yielded a p-value of 0.000, indicated a statistically significant difference in the degree of satisfaction between the two groups. The calculated mean rank values show that the group that took advantage of the personalised offers is significantly more satisfied with their stay than the other group.

The following Figure 2 illustrates the distribution of satisfaction values in the two groups.

We can see clear differences in the proportions for certain satisfaction levels between the two groups. Of the respondents who did not take advantage of personalised offers, 13.6% said they were very dissatisfied with their stay, compared to only 1.8% in the group that did. Similarly, 26% of Group 0 respondents expressed a neutral attitude towards their stay, compared to only 11.8% of Group 1.

Of those who said they were satisfied, around 46% were in the group that did not take advantage of personalised offers, while this percentage rose to 66% for those who did. Among respondents who were very satisfied, the percentage in Group 0 was 10 compared to 19.5% in Group 1.

Together with the visual representation of the proportions between the groups and the results of the Mann–Whitney test, in Figure 2. we can see that the group that perceived personalised offers has a significantly higher distribution of satisfaction scores. In other words, a significantly larger proportion of this group reported higher satisfaction than those who did not take advantage of such offers.

H4: 

The source of destination information significantly influences the likelihood of exposure to personalised marketing messages.

To test the hypothesis, we use the Kruskal–Wallis test, presented in

Table 7. Influence of information source on exposure to personalised offers. Kruskal–Wallis test results.

Ranks
	Information Source	N	Mean Rank
Personalised Offers	1—recommendation	78	136.76
	2—internet	116	141.98
	3—media	34	78.51
	4—travel agencies	15	147.30
	5—other	14	81.21
	Total	257
Test Statistics a,b
		Personalised Offers
Kruskal–Wallis H		39.623
df		4
Asymp. Sig.		0.000

^a Kruskal–Wallis test; ^b Grouping variable: Information source.

which compares five groups based on their source of information. The groups are labelled 1 to 5 and represent, respectively, recommendation, internet, media, travel agencies and others.

The Kruskal–Wallis test indicates that the source of information about the destination has a significant influence on the awareness or use of personalised offers. Based on the mean ranking values, the sources “media” and “others” stand out in particular. Respondents who obtained information from the media or indicated “other” as a source were significantly less likely to have perceived personalised marketing offers. This result is in line with our expectations.

H5: 

The source of information about the destination significantly influences the level of satisfaction with the stay.

As it has been shown that personalised offers are related to the level of satisfaction and the source of information is related to the exposure to such offers, we are now interested in whether there is a direct relationship between the source of information and the level of satisfaction with the stay. To investigate this, we conduct the Kruskal–Wallis test.

The p-value of 0.593 in

Table 8. Relationship between information source and tourist satisfaction. Kruskal–Wallis test results.

Ranks
	Information Source	N	Mean Rank
Stay Satisfaction	1—recommendation	78	135.51
	2—internet	116	129.95
	3—media	34	125.01
	4—travel agencies	15	112.40
	5—other	14	112.32
	Total	257
Test Statistics a,b
		Stay Satisfaction
Kruskal–Wallis H		2.796
df		4
Asymp. Sig.		0.593

^a Kruskal–Wallis test; ^b Grouping variable: Information source.

. indicates that there is no significant difference between the groups regarding the source of information and the degree of satisfaction with the stay.

From the three previous hypotheses, it can be concluded that tourists who were exposed to promotional offers were significantly more satisfied with their stay and that those who had obtained information via the internet or personal recommendations were significantly more likely to be exposed to such offers. Thus, while the source of information influences exposure to promotional offers and exposure to offers influences satisfaction, there is no direct correlation between the source of information and the level of satisfaction with the stay. This suggests that, while personalised promotional offers have a positive impact on satisfaction, this is also influenced by other factors that were not captured in the survey, such as the overall experience or the perceived quality of the promotional offers.

H6: 

Tourists who are exposed to personalised marketing messages will recommend the destination significantly more than those who are not.

To test the hypothesis, a chi-square test is performed. As with the previous hypothesis, two response categories (“Yes, regularly” and “Yes, occasionally”) are combined into one category (Group 1), while all other responses are combined into a second category (Group 0). The results of the chi-square test presented in

Table 9. Effect of interest-based personalisation on destination recommendation. Chi-square test and crosstabulation.

Destination Recommendation * Previous Interest Crosstabulation
Count
			Previous Interest		Total
			0.00	1.00
Destination Recommendation		0	18	15	33
		1	55	169	224
Total			73	184	257
Chi-Square Tests
	Value	df	Asymptotic Significance (2-sided)	Exact Sig. (2-sided)	Exact Sig. (1-sided)
Pearson Chi-Square	12.722 a	1	0.000
Continuity Correction b	11.290	1	0.001
Likelihood Ratio	11.542	1	0.001
Fisher’s Exact Test				0.001	0.001
Linear-by-Linear Association	12.673	1	0.000
N of Valid Cases	257

^a In total, 0 cells (0.0%) have an expected count of less than 5. The minimum expected count is 9.37. ^b Computed only for a 2 × 2 table. * means “in relation to”.

are as follows:

The chi-square test indicates statistical significance, which means that there are significant differences in the proportions of destination recommendations between the groups. Respondents who were aware of messages tailored to their personal interests were significantly more likely to recommend the destination to others than respondents who were not. Of the 184 people who were aware of such messages, 169 (91.8%) recommended the destination to others, while of those who were not aware of the messages, 55 out of 73 (75%) did so.

It is important to note that in both cases most respondents would recommend the destination. This test shows a significant correlation between the perception of personalised marketing messages and the likelihood of recommendation, but it does not imply causality. The survey indicates the presence of certain associations but cannot definitively determine the causal factors for satisfaction with the stay or the intention to recommend the destination to others.

To better understand the shape of the data distribution, in Figure 3. skewness and kurtosis were calculated for key variables. The variable Offers Impact exhibited a strong negative skew (−2.09) and a leptokurtic distribution (excess kurtosis = 2.36), indicating a high concentration of responses at the higher end of the scale. Stay Satisfaction showed moderate negative skewness (−1.08) and a pronounced leptokurtic shape (excess kurtosis = 3.14), suggesting most participants reported high satisfaction. Finally, Destination Recommendation was highly negatively skewed (−2.51) with strong leptokurtosis (excess kurtosis = 4.29), reflecting a dominant tendency among respondents to recommend the destination. These deviations from normality further justify the use of non-parametric tests such as the Mann–Whitney U and chi-square tests applied in the analysis.

A more detailed study would be required to determine specific causal relationships.

5. Discussion

The aim of this study was to investigate the impact of personalised and predictive marketing strategies on tourist satisfaction, as well as the behavioural intention to revisit or recommend a destination in the context of Croatian tourism. By applying a quantitative methodology and testing six hypotheses, this study provides important insights into how tourists react to personalised marketing measures.

The results for H1 show that gender plays an important role in the perception of personalised marketing strategies, while age has no significant influence on tourists’ reactions. Women were found to be significantly more influenced by personalised offers compared to men, confirming the findings of previous research emphasising demographic differences in consumer behaviour (Tifferet & Vilnai-Yavetz, 2014). However, no statistically significant differences were found between the different age groups, suggesting that personalisation strategies should prioritise gender customisation over age-specific segmentation.

While the current findings provide valuable insights into general demographic patterns, they should not be interpreted as universally applicable. Future iterations of this research will benefit from a more nuanced approach that considers individual personality traits and psychological profiles, which can significantly influence how tourists perceive and respond to personalised marketing efforts.

Regarding H2, the results showed a weak but statistically significant negative correlation between the frequency of advertising messages and tourist satisfaction, indicating that excessive exposure may slightly reduce satisfaction. On the other hand, a positive and moderate correlation was found between the perception of personalised offers and satisfaction, supporting previous studies that have shown that relevance and targeting of consumers’ interests are crucial for increasing satisfaction (Gretzel et al., 2015).

These findings underscore the need for a balanced approach in the application of personalised marketing strategies. While personalization can enhance tourist satisfaction and foster loyalty, overly aggressive or excessive promotional efforts may diminish their effectiveness or even provoke negative reactions. It is therefore essential that marketing communications remain both relevant and proportionate, aligning with tourists’ actual interests and preferences without overwhelming them.

H3 investigated the relationship between the perception of personalised marketing based on previous interests and the likelihood of tourists recommending the destination to others. The results of the chi-square test confirmed a statistically significant relationship: tourists who were exposed to such personalised messages were more likely to recommend the destination to others than those who were not. This finding is consistent with previous research highlighting the power of personalised communication to promote positive word of mouth (Yang et al., 2023).

In reviewing H4, this study found that the source of information about the destination significantly influenced the likelihood of perceiving personalised offers. Tourists who relied on internet sources or personal recommendations were more likely to be exposed to personalised marketing, while those who obtained information through traditional media were less likely to perceive such messages. This finding highlights the growing importance of digital platforms in delivering personalised experiences (Xiang et al., 2015).

However, the results of H5 showed that there was no direct significant relationship between the source of information and tourists’ satisfaction with their stay. Although the source of information influenced exposure to personalised messages, it alone did not determine the level of satisfaction. This finding suggests that satisfaction is influenced by a broader range of factors, including the overall quality of services, the destination experience, and perhaps the relevance and quality of the personalised offers themselves.

Finally, H6 examined the differences in satisfaction between tourists who had experienced personalised offers and those who had not. The Mann–Whitney U-test confirmed a statistically significant difference: those who had experienced personalised offers indicated a higher level of satisfaction. This underlines the positive role of personalisation in improving the tourism experience and the strategic advantage of investing in targeted communication measures.

5.1. Practical Implications

For practitioners in the Croatian tourism sector, these results provide clear guidance for improving marketing strategies. Destination marketing organisations (DMOs) and service providers should prioritise personalised communication and ensure that messages are relevant, timely and aligned with tourists’ interests. Special attention should be paid to gender differences when designing personalisation campaigns.

The results also underline the importance of optimising the frequency of advertising messages. Overexposure can have a negative impact on satisfaction, even when messages are personalised. Marketing efforts should aim to strike a balance between visibility and consumer convenience.

The findings also highlight the need to improve personalisation on digital channels, particularly websites and social media platforms, where tourists are more likely to encounter marketing content. Personalised marketing should not be viewed in isolation but should be integrated into efforts to improve overall service quality, destination management and tourist experiences to maximise satisfaction and loyalty.

Results emphasise that the quality of information outweighs its quantity—tourists value information that is relevant, trustworthy, and aligned with their personal interests, whereas excessive exposure to generic messages can have a counterproductive effect.

Moreover, a positive personal experience has proven to be a key prerequisite for destination recommendation behaviour. Establishing an emotional connection with the destination, along with a sense of authenticity and trust, has a long-term impact on tourist loyalty. Therefore, marketing strategies should aim not only to capture attention but also to create lasting value through experiences that tourists will want to share.

Overall, this study supports the growing body of evidence that personalised and predictive marketing strategies, when carefully implemented, can significantly improve tourist satisfaction and behaviour in competitive destinations such as Vodice.

5.2. Limitations and Future Research Directions

Although this study provides valuable insights into the role of personalised and predictive marketing strategies in Croatian tourism, several limitations must be acknowledged.

First, this study was conducted in a single coastal destination, namely, Vodice, which may limit the generalisability of the results to other types of destinations such as urban, rural or inland regions. Future research could broaden the scope by including multiple destinations with different tourist profiles.

Secondly, the sample consisted mainly of tourists who were willing to participate in the survey through accommodation providers. This may lead to self-selection bias, as more engaged or satisfied tourists may have been more willing to participate in the survey.

Third, while this study focused on self-reported perceptions of personalisation, the objective quality or content of the personalised marketing offers was not directly assessed. Future studies should integrate content analysis of marketing messages or experimental designs to better capture causal relationships between the type of personalisation and tourist satisfaction.

Furthermore, satisfaction was only measured at a single point in time, immediately after the visit. Longitudinal studies could provide deeper insights into how personalised marketing influences not only immediate satisfaction but also long-term loyalty and repeat visits.

Finally, while several key variables were examined, satisfaction and behavioural intention to revisit or recommend a destination are multi-faceted constructs that are influenced by various psychological and contextual factors that were not captured in this study. Future research could incorporate additional variables such as emotional engagement, destination image and perceived authenticity to develop more comprehensive models. If these limitations are addressed, future research can build on the findings of this study to provide a more nuanced understanding of personalisation strategies in tourism marketing.