User Experience

Building and maintaining brand loyalty is a vital issue for market research departments. Various means, including online advertising, helps with promoting loyalty to the brand amongst users. The present paper studies intelligent web advertisements with an eye-tracking technique that calculates users’ eye movements, gaze points, and heat maps. This paper examines different features of an online ad and their combinations, such as underlining words and personalization by eye-tracking. These characteristics include underlining, changing color, number of words, personalizing, inserting a related photograph, and changing the size and location of the advertisement on a website. They help advertisers to improve their ability to manage the ads by increasing users' attention. Moreover, the current research argues the impact of gender on users' visual behavior for advertising features in different Cognitive Demand (CD) levels of tasks while avoiding interruption of users’ cognitive processes with eye-tracking techniques. Also, it provides users the most relevant advertisement compatible with CD level of a task by Support Vector Machine (SVM) algorithm with high accuracy. This paper consists of two experiments that one of them has two phases. In the first and second experiments, a news website alongside an advertisement and an advertising website is shown to the users. The results of the first experiment revealed that personalizing and underlining the words of the ad grabs more attention from users in a low CD task. Furthermore, darkening the background promotes users' frequency of attention in a high CD task. By analyzing the impact of gender on users' visual behavior, males are attracted to the advertisement with red-colored words sooner than females during the high CD task. Females pay more prolonged and more frequent attention to the ads with red-colored words and larger sizes in the low CD task. The second experiment shows that the gazing start point of users with a right to left mother tongue language direction is mainly in the middle of the advertising website.

The purpose of this study is to identify the components of information illustration related to user experience in the digital library of Allameh Tabatabai University. The research method is thinking aloud protocol and with a qualitative approach. The study population was undergraduate, graduate and doctoral students who were purposefully selected as a sample population of 30 people. Data collection was performed using Morae software, face-to-face observation, researcher's notebook and users' audio files. Findings show that elements such as fonts, color combinations, graphic images and their placement and arrangement in library pages have been of interest to users. Problems include not knowing how to use advanced search, as well as the use of a number of image icons. Based on the evidence, elements such as fonts, color combinations, graphic images, and their placement on page have been important to users. Users considered the suggestion of using animated visual symbols to be necessary to make the appearance attractive and facilitate users' information-seeking behavior, which to a large extent overlaps with and is in line with the principles and basis of information visualization. In this way, the use of eye-catching tools such as blinking characters, in turn, can play a key role in identifying important parts. Using fewer visual elements on the front page to increase the focus of the front page, using navigation features on the search page, and displaying a sequence of retrieved records on the results page were some of the common points that users mentioned.

The objective of this study is to understand the customer journey in technology product adoption by exploring the experiences and perspectives of individuals who have recently adopted new technology products. This research aims to identify key themes and factors influencing the customer journey from initial awareness to ongoing engagement and retention, providing insights to enhance customer experiences and inform marketing strategies. This qualitative study employed semi-structured interviews with 20 participants selected through purposive sampling to ensure diverse representation. Participants included individuals who had recently adopted technology products within the past six months. Data collection continued until theoretical saturation was reached. The interview transcripts were analyzed using NVivo software, following an inductive approach to identify patterns and themes. The analysis revealed three main themes: Awareness and Decision-Making, First-Time Use and Learning, and Ongoing Engagement and Retention. Initial awareness was driven by advertising, social media, and word-of-mouth, while decision-making was influenced by peer recommendations, brand reputation, and price sensitivity. The first-time use phase highlighted the importance of intuitive design and support resources. Regular updates, community engagement, and product reliability emerged as critical factors in ongoing engagement and retention. Participants valued seamless omnichannel experiences, personalized marketing efforts, and robust support systems. The study underscores the significance of personalized, seamless customer journeys in technology product adoption. Businesses should focus on integrating physical and digital touchpoints, leveraging AI for personalized experiences, and maintaining active user communities to enhance customer satisfaction and loyalty. Addressing cultural nuances in global markets and managing digital signals effectively can further optimize the customer journey. These insights provide valuable guidance for businesses aiming to improve customer experiences and foster long-term engagement in the competitive technology market.

Computational aesthetics is a field that combines science and art to explore aesthetic measurement, generative art, and design generation using computational methods. In the context of university library websites, adhering to aesthetic standards, particularly focusing on "moderate visual complexity," could enhance their visibility online (according to some previous studies). This research, analyzed 82 university library websites, including top international and Iranian academic libraries, to assess visual complexity based on Berlyne's theory of stimulus complexity using the Athec Python library. The study found that international university libraries have a complexity of over 0.57, while Iranian academic libraries lack the minimum complexity needed to motivate users. Moreover, the study found significant differences between the library websites of top Iranian and international universities. The linear regression statistic test was used to analyze the relationship between the visual complexity of academic library websites and the rank of the university, revealing a significant difference for the 41 top Iranian universities but not for the 41 top international universities. The Beta coefficient of linear regression between the visual complexity of academic library websites and the rank of the university is -0.502, and Sig=0.001, obtained for the top Iranian universities. On the other hand, the Beta coefficient of linear regression between the visual complexity of academic library websites and the ranks of the university is -0.062, and Sig=0.701, obtained for top international universities. This research highlights the innovation of connecting Berlyne’s theory of stimulus complexity with Python programming, providing a new perspective for university library website managers.