User Engagement Research Articles

Google, SEO and helpful content: How artificial intelligence can be helpful for e-commerce websites

This paper explores the impact of artificial intelligence (AI) on search engine optimisation (SEO) practices within a marketing agency setting, with a particular focus on quality, topical authority and relevance over quantity. By leveraging AI-powered content creation tools, the study explores the effectiveness of generating various SEO elements for enhancing the visibility and ranking of product pages. Using models such as OpenAI’s text-davinci-003, the study demonstrates the generation of SEO elements tailored to specific product details, brand names and website URLs. Through examples of fitness equipment, the study showcases the creation of SEO-friendly content, enhancing the discoverability of product pages and user engagement. Furthermore, the study extends its focus beyond textual content to include the generation of image alt tags, identifying low-resolution images and implementing contextual internal linking using AI techniques. The study explores methodologies for generating alt tags for images based on image URLs, identifying low-resolution images from a list of URLs, and recommending internal links based on content similarity and topical relevance. The study also describes practical applications of AI in various SEO optimisation tasks, emphasising the role of AI-driven solutions in enhancing website crawlability, user experience and overall SEO performance, thereby contributing to improved visibility, traffic and conversion rates. By addressing key SEO challenges and leveraging AI technologies, marketing agencies can optimise their strategies for better search engine visibility, ultimately driving growth and competitiveness in the digital landscape.

Enhancing user experience in online learning environments: Design, evaluation, and usability techniques

This study aims to enhance user experience on online learning platforms by investigating design principles, usability evaluation techniques, and rede-sign processes. A total of 150 participants, divided equally among students, educators, and professionals, were stratified by age, gender, education level, and familiarity with online learning. Various evaluation methods, including heuristic evaluation, guideline reviews, and cognitive walkthroughs, were employed. Metrics such as task success rate, time-on-task, and Net Promoter Score (NPS) were used to quantify user satisfaction and effectiveness. Addi-tionally, five qualitative interviews were conducted for deeper insights. The results revealed specific usability issues and demonstrated the effectiveness of the applied evaluation techniques. Post-redesign metrics indicated signif-icant improvements in user satisfaction and engagement. The study under-scores the importance of a multi-faceted approach to design and evaluation in online learning platforms and suggests avenues for future research.

THE ROLE OF A CLIENT-ORIENTED APPROACH IN MANAGING WEB DESIGN PROJECTS

The article is devoted to the study of the place of the client-oriented approach in the management mechanism of web design projects. In the context of the dynamic development of the digital economy, as well as increased competition in the market of services in this area, the task of adapting development processes to individual customer needs becomes urgent. The purpose of the study is to identify the most effective methods of implementing a client—oriented approach to web design project management and characterize their impact on the final result. There are contradictions in understanding the optimal level of client participation in the project: on the one hand, high customer engagement helps to ensure that their needs are met, on the other hand, it sometimes significantly slows down the development process and significantly increases costs. It was concluded that the use of a client-oriented approach, provided that there is a well-organized process of interaction with the customer, can improve the quality of services and customer satisfaction, which, in turn, contributes to the successful implementation of projects. The novelty lies in the fact that an innovative methodology "Integrative client-centered design" is proposed. It is based on the synthesis of best practices of project management, design thinking, Agile approaches adapted to the specifics of web design projects. The article will be useful for web design project managers, developers, as well as management and marketing specialists who seek to implement effective strategies for interacting with customers.

Enhancing Customer Engagement through Dynamics CRM Customization

Enhancing Customer Engagement through Dynamics CRM Customization

User acceptance of AI voice assistants in Jordan’s telecom industry

Purpose:This study aims to understand factors influencing consumer acceptance of artificial intelligence (AI) voice assistants used in customer support within telecom companies in Jordan. Methodology:A survey was conducted involving 248 individuals who have experience with telecom support services. To evaluate consumer acceptance, the study incorporates the Unified Theory of Acceptance and Use of Technology (UTAUT) framework and extends it with attributes specific to AI, such as Perceived Reliability, Voice Quality, and Quality of Information. Advanced statistical methods, including structural equation modeling with SPSS AMOS 28 and SmartPLS, were utilized to analyze the collected data. Findings:The results revealed that Perceived Reliability and Quality of Information were significant predictors of AI voice assistant adoption in the telecom sector, while traditional factors such as Perceived Usefulness and Trust showed no significant impact. These findings suggest that performance-related elements play a more crucial role in user acceptance of AI in this context compared to earlier technological acceptance models. Implications:The study offers an expansion to traditional technology acceptance models by highlighting the importance of AI-specific attributes over conventional factors like Perceived Usefulness and Trust. For telecom operators in developing markets, this research provides guidance on enhancing customer engagement with AI voice assistants. It suggests focusing on improving the reliability and quality of information provided by AI systems to boost user acceptance. Originality/value:The study provides valuable insights into the changing dynamics of consumer acceptance of AI in customer support, emphasizing a shift toward performance-based criteria. Telecom companies in Jordan can use these findings to inform their AI adoption strategies and enhance customer satisfaction.

Comparison on Applications and Impact of AI in English Grammar Learning

English grammar plays an important role in the learning of English language skills. However, it has always been challenging for students to understand grammar right from school. Complicated rules make the learning process even harder. Teachers have tried to come up with many ways to make the learning process interesting and simple yet there exists a gap. Artificial Intelligence bridges the gap and achieves the goal of attaining grammar learning in interesting ways. The integration of artificial intelligence (AI) in grammar learning applications represents a transformative approach to language education. Many applications focus on teaching grammar by gamifying the learning process. AI-powered applications provide personalized learning experiences, immediate corrective feedback, and adaptive difficulty adjustments, leading to improved grammatical competence and sustained user engagement. This research attempts to make a comparative study of English grammar learning platforms and applications by analyzing their impact on the autonomous learning of students. Applying AI has been considered learner-centric as it stimulates learning and fascinates the learners with expected learning outcomes.

The Application of Generative AI in Virtual Reality and Augmented Reality

This study explores the historical development of Virtual Reality (VR) and Augmented Reality (AR) technologies and their applications in various fields, such as education, tourism, and consumer experiences. Through a review of relevant literature, the paper analyzes how VR and AR enhance user engagement and satisfaction by providing immersive and interactive experiences. In education, VR and AR are used to create vivid learning environments, promoting students' understanding and interest; in the tourism industry, these technologies enhance visitors' exploration and experience of destinations; in business, AR applications improve consumer shopping experiences and brand loyalty. Despite the widespread application of these technologies facing challenges such as high costs and user adaptability issues, research shows their potential remains significant. Future research should focus on optimizing user experience, lowering technological barriers, and expanding application scenarios. In conclusion, the development of VR and AR technologies will drive innovation and transformation across industries, offering richer experiences in daily life.

Impact of different regulatory approaches in renewable energy communities: A quantitative comparison of european implementations

Recently, the uptake of renewable energy has surged in distribution networks, particularly due to the cost-effectiveness and modular nature of photovoltaic systems. This has paved the way to a new era of user engagement, embodied by individual and collective self-consumption, and promoted by the EU Directive 2018/2001, which advocates for the establishment of Renewable Energy Communities. However, the transposition of this directive varies across Member States, resulting in specific rules for each country. In this work, the impact that different energy sharing models have on the same community is quantitatively assessed. The policy analysis focuses on the regulation of two countries, Italy and Portugal, chosen for the specular ways in which their models operate, respectively virtually and physically. The analysis is supported by a suite of tools which includes two optimization problems for community's operations, one for each analysed regulation, and a set of consumer protection mechanisms, to ensure no member is losing money while in community. Results demonstrate that the sharing model impacts community's optimal operations, optimal battery size and configuration, and members' benefit. As these models are sensitive to different variables, personalized interventions at national level are required.

Transforming Financial Interactions: Best Practices for Mobile Banking App Design and Functionality to Boost User Engagement and Satisfaction

Transforming Financial Interactions: Best Practices for Mobile Banking App Design and Functionality to Boost User Engagement and Satisfaction

P[formula omitted]ED: A four-quadrant framework for progressive prompt enhancement in 3D interactive medical imaging segmentation

Interactive segmentation allows active user participation to enhance output quality and resolve ambiguities. This may be especially indispensable to medical image segmentation to address complex anatomy and customization to varying user requirements. Existing approaches often encounter issues such as information dilution, limited adaptability to diverse user interactions, and insufficient response. To address these challenges, we present a novel 3D interactive framework P2ED that divides the task into four quadrants. It is equipped with a multi-granular prompt encrypted to extract prompt features from various hierarchical levels, along with a progressive hierarchical prompt decrypter to adaptively heighten the attention to the scarce prompt features along three spatial axes. Finally, it is appended by a calibration module to further align the prediction with user intentions. Extensive experiments demonstrate that the proposed P2ED achieves accurate results with fewer user interactions compared to state-of-the-art methods and is effective in promoting the upper limit of segmentation performance. The code will be released in https://github.com/chuyhu/P2ED.

AI -Powered Content Management: How Adobe Experience Manager (AEM) and OpenAI Elevate SEO and Customer Engagement

The way organizations handle their content is undergoing a transformation with the incorporation of Artificial Intelligence (AI). Adobe Experience Manager (AEM) when combined with the capabilities of OpenAI’s technology marks a step forward in AI driven content management that boosts Search Engine Optimization (SEO) and enhances engagement, with customers. Through the power of AI technology content managers are able to streamline content creation processes enhance the precision of metadata labeling and offer tailored content experiences on a scale. This change does not enhance SEO rankings but also enhances user involvement by providing tailored user experiences as well as better interactions, with the audience. Moreover, by incorporating AI in AEM enables ongoing enhancement, where AI algorithms examine user actions and tweak content approaches. This article discusses the influence AI, specifically OpenAI has had on enhancing SEO and engaging customers through AEM. The document explores the obstacles in technology encountered by content management systems and the solutions offered by AI powered tools along with their lasting impacts for companies implementing these cutting-edge systems. It will discuss how AI is transforming tasks such, as creating content, tagging metadata. Customizing user experiences and shaping the future of digital content management. Keywords: AI-Powered Content Management, Adobe Experience Manager, OpenAI, Search Engine Optimization, Customer Engagement, Content Personalization, Metadata Tagging, Automation, User Experience, Digital Content Strategy

Improving Customer Engagement with Digital Gift Features in Mobile Banking Using Design Thinking Stages

Among the challenges faced by conventional banks is the provision of banking services that can compete with digital banks. Mobile banking is one of the banking services in the form of an application that can be a tool to compete through the development of relevant, attractive, and effective features or services to meet customer needs. People have a habit of giving gifts to each other adopting the value of the spirit of giving in social life, especially at special moments. Digital gifts are a new trend to be able to send gifts to each other without the need to meet face-to-face. The development of digital gift services in mobile banking is the result of observing customer needs using the Design Thinking stage to obtain solutions to these problems. The addition of gamification elements to the development of digital gift services is expected to increase customer engagement and increase customer retention. The data collection method is in the form of a survey of customers. This research is a qualitative research that describes the needs of customers for digital gift services. This research was conducted from January to May 2024. The respondents of this study are customers who have been actively using mobile banking.

Animated Web Application

This project will attempt to develop animated web applications using both HTML, CSS, JavaScript, Three.js, and React at the same time as approaches that make user experiences immersive and interactive using the capabilities of the technologies in question. Thus, HTML provides the structural backbone, while CSS adds the visuals and makes it more responsive. The JavaScript core programming language enables dynamic behavior and interactivity. The library Three.js was used in order to include 3D graphics to create stunning visualizations and animations that appeal to a user on a deeper level. React will be used to handle the state and the structure of an application, hence the effective rendering to and smooth experience for the user. The use of animations and 3D elements used in this project brings into view the further possibilities modern web technologies can produce in creating applications that break the limits set by conventional web-based design. Therefore, this final product is to exemplify the best practices of optimization in terms of performance, user engagement, and responsive design.

Revolutionizing library systems with advanced automation: A blueprint for efficiency in academic resource management

The advent of advanced automation technologies has the potential to revolutionize library systems, particularly within academic institutions, where effective resource management is essential. This paper outlines a comprehensive blueprint for integrating automation into library operations to enhance efficiency, accessibility, and user engagement. Key technologies discussed include Radio Frequency Identification (RFID), Artificial Intelligence (AI), and Machine Learning (ML), which streamline processes such as cataloging, circulation, and inventory management. The implementation of RFID facilitates self-service checkouts and real-time inventory tracking, significantly reducing the time spent on manual tasks, thereby allowing library staff to concentrate on enhancing user experiences and curating resources strategically. Furthermore, AI-driven chatbots provide personalized recommendations, improving user satisfaction and ensuring that patrons receive tailored support. This blueprint emphasizes the role of automated digital repositories and intelligent content indexing systems, which accelerate cataloging and ensure timely access to scholarly materials. By automating information retrieval processes, libraries can reduce wait times and improve the overall accessibility of resources. Data analytics are also pivotal, enabling libraries to monitor usage patterns, optimize resource allocation, and forecast future demands, ensuring alignment with academic priorities. Moreover, the paper addresses challenges related to automation implementation, including financial constraints, data privacy concerns, and staff training requirements, proposing solutions such as gradual implementation and interdepartmental collaboration. Ultimately, the transition to advanced automation not only enhances operational efficiency but also boosts academic productivity by making resources more accessible and user-centered. This strategic move toward a digital-first library environment signifies a profound transformation in academic libraries, promoting an agile approach to resource management. As institutions increasingly adopt these technologies, they position themselves at the forefront of educational innovation, effectively integrating academic resources into the digital learning landscape.

Emerging Trends in Real-time Recommendation Systems: A Deep Dive into Multi-behavior Streaming Processing and Recommendation for E-commerce Platforms

This paper aims to assess the effectiveness of recommendation systems, focusing on multi-behavior streaming processing to enhance accuracy. It studies recommendation system performance using AI and data science, focusing on user behaviour, algorithm refinement, and satisfaction. E-commerce, streaming, and social media datasets with 93 anonymous participants were employed in experiments. These files from 93 anonymized users show typical internet use. Data anonymization and strict data management ensured anonymity. These databases track clicks, views, purchases, and ratings for empirical research and model evaluation. Collaborative filtering, matrix factorization, and TensorFlow/Keras train and assess application-specific recommendation models. Multi-behavior streaming processing and recommendation accounts assess each method's pros and downsides, system correctness, efficacy, and user involvement. The outcome compares domain-wide recommendation system precision, recall, NDCG, and conversion rate. Multi-behavior streaming processing adapts to user preferences and interactions to improve model accuracy and adaptability. Multi-behavior streaming processing improved model accuracy and flexibility by reacting to user inputs and choices. With error margins for all significant metrics, statistical significance was confirmed. The findings suggest that recommendation systems with real-time adaptation and multi-behavior streaming processing can improve user satisfaction and engagement in the changing digital landscape. It encourages algorithm advancement, model interpretation, user-centric evaluation, and ethics to improve information retrieval and personalisation. The study concluded that algorithm refinement, transparent model interpretation, user-centric evaluation, and ethical problems including data protection and bias mitigation increase information retrieval and personalisation. For durable and flexible recommendation systems, research should improve multi-behavior processing and sectoral applications.

Artificial intelligence in digital marketing automation: Enhancing personalization, predictive analytics, and ethical integration

Artificial Intelligence (AI) is revolutionizing digital marketing automation by enhancing efficiency, personalization, and predictive capabilities. This study examines the role of AI in transforming marketing practices, focusing on its applications, benefits, ethical considerations, and future directions. By leveraging AI tools such as predictive analytics, NLP, and chatbots, businesses can achieve improved customer segmentation, content personalization, and campaign optimization in marketing strategies. Secondary data from journals, articles, and conference papers were synthesized to provide insights into AI's impact on digital marketing automation. A systematic literature review utilizing the PRISMA methodology initially identified 2,850 records from database searches. Following the removal of duplicates and non-relevant studies, 1,035 records were screened for eligibility based on defined criteria, resulting in the inclusion of 150 relevant studies and 25 high-quality reports for detailed analysis. This robust approach ensured the inclusion of high-quality research, minimizing biases. The findings reveal that AI enhances digital marketing by streamlining processes, automating repetitive tasks, and delivering hyper-personalized customer experiences. Predictive analytics helps anticipate consumer behavior, while chatbots improve real-time customer engagement. However, challenges such as data privacy, algorithmic bias, and the high costs of AI adoption persist. AI adoption allows businesses to make data-driven decisions, improve customer retention, and maximize return on investment. Ethical AI practices, such as transparency and algorithm fairness, are essential for maintaining consumer trust. The study primarily focuses on existing literature, with limited empirical validation. Future research should explore long-term effects of AI-driven marketing on consumer behavior and investigate its integration with emerging technologies like the Internet of Things (IoT) and blockchain. Additionally, tailored AI solutions for SMEs and under-researched areas, such as B2B marketing, are critical for inclusive growth.

Big data for SMEs: A review of utilization strategies for market analysis and customer insight

This paper provides a comprehensive review of how small and medium-sized enterprises (SMEs) can leverage big data for market analysis and customer insights, offering strategies to enhance competitiveness in today’s data-driven economy. The study explores the role of big data in helping SMEs understand customer behavior, preferences, and trends, enabling them to make informed decisions and improve customer satisfaction. It highlights the practical challenges SMEs face in adopting big data solutions, including limited resources and technical expertise, and suggests scalable, cost-effective strategies for data collection, storage, and analysis. Key utilization strategies discussed include the integration of cloud-based platforms for data management, the use of data analytics tools to process customer feedback, and the application of machine learning algorithms to predict customer behavior. The paper also examines case studies where SMEs successfully implemented big data solutions to achieve significant market insights and improve business outcomes, such as enhanced marketing strategies, personalized customer experiences, and streamlined operations. The review concludes that, despite the challenges, SMEs can effectively harness the power of big data by adopting tailored strategies that align with their specific business needs and resources. By utilizing big data, SMEs can gain a competitive edge, improve customer engagement, and ultimately drive business growth. The paper emphasizes the importance of training, data literacy, and the need for partnerships with technology providers to ensure the successful integration of big data into business processes.

Predictive Analytics for Customer Retention: A Data-Driven Framework for Proactive Engagement and Satisfaction Management

This comprehensive article examines the implementation of predictive analytics and data-driven frameworks for enhancing customer retention in modern business environments. The article explores how advanced analytics, machine learning algorithms, and proactive engagement strategies can significantly improve customer satisfaction and reduce churn rates. Through detailed article analysis of usage patterns, engagement metrics, and customer behavior, the article demonstrates the effectiveness of sophisticated intervention strategies in maintaining strong customer relationships. The article investigates the development and implementation of satisfaction score algorithms, real-time monitoring systems, and customized support mechanisms that enable organizations to identify and address potential issues before they lead to customer attrition. Furthermore, it evaluates the impact of integrated feedback systems and sentiment analysis in creating more responsive and effective customer retention strategies. The article provides valuable insights into how organizations can leverage data analytics to create more personalized and proactive customer engagement approaches, ultimately leading to improved customer lifetime value and business sustainability.

Meta-Learning to Rank for Sparsely Supervised Queries

Supervisory signals are a critical resource for training learning to rank models. In many real-world search and retrieval scenarios, these signals may not be readily available or could be costly to obtain for some queries. The examples include domains where labeling requires professional expertise, applications with strong privacy constraints, and user engagement information that are too scarce. We refer to these scenarios as sparsely supervised queries which pose significant challenges to traditional learning to rank models. In this work, we address sparsely supervised queries by proposing a novel meta-learning to rank framework which leverages fast learning and adaption capability of meta-learning. The proposed approach accounts for the fact that different queries have different optimal parameters for their rankers, in contrast to traditional learning to rank models which only learn a global ranking model applied to all the queries. In consequence, the proposed method would yield significant advantages especially when new queries are of different characteristics with the training queries. Moreover, the proposed meta-learning to rank framework is generic and flexible. We conduct a set of comprehensive experiments on both public datasets and a real-world e-commerce dataset. The results demonstrate that the proposed meta-learning approach can significantly enhance the performance of learning to rank models with sparsely labeled queries.

Virtual Tourism Android-Based Application

The Virtual Tourism- Android-based Application revolutionizes the tourism indus try by offering users a unique opportunity to explore global destinations from the comfort of their homes. Leveraging cutting-edge technologies such as 360-degree panoramic views, augmented reality (AR), and interactive multimedia, the app cre ates an immersive and engaging travel experience that brings famous landmarks, historical sites, and natural wonders to life. This application is especially valuable for individuals who face physical, financial, or time-related constraints, allowing them to virtually visit locations they may oth erwise be unable to access. It also serves as an educational tool, enabling students and culture enthusiasts to learn about the world in a highly interactive and accessible manner. The real-time tour guides and interactive maps add a dynamic layer to the virtual exploration, enhancing user engagement. In addition to these features, the app integrates social media sharing, user reviews, and offline access, fostering a community-driven platform where users can share their experiences, rate destinations, and download content for use without internet connectivity. This comprehensive combination of innovative features positions the Virtual Tourism app as a game-changer in the future of travel and education.