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User-Centered Design in Digital Marketing

User-Centered Design in Digital Marketing/strong>
Authors:-Abhijit Mojumder, Susmita Biswas

Abstract-Purpose: This thesis investigates how user-centered design (UCD). , user experience (UX) principles can have a remarkable impact on digital marketing campaigns, focusing on consumer engagement. , conversion rates. With the rising complexity of online consumer behavior. , ever-increasing competition in digital marketplaces, leveraging strategic UX design has emerged as a powerful tool for marketers. Methodology: The study adopts a mixed-methods approach, incorporating both quantitative data (such as user analytics, A/B testing results)., qualitative insights (such as interviews, focus groups). A framework is established to evaluate campaign performance metrics, user satisfaction scores, . , conversion funnels within diverse digital platforms—social media, e- commerce websites, mobile applications. Findings: The findings suggest that user-centered design elements—such as intuitive navigation, responsive interfaces, consistent br. ,ing, . , personalization—lead to higher levels of user satisfaction, br. , trust, , customer retention. In addition, campaigns designed around UX principles witnessed a measurable uptick in conversion rates compared to those that lacked deliberate UX planning. Implications: This thesis contributes to the existing literature on digital marketing by incorporating comprehensive UX design strategies. By applying user-centered methodologies, marketers can cultivate more engaging. , persuasive digital experiences, thus boosting key performance indicators (KPIs) such as click-through rates, time on site, average order value., customer lifetime value.

DOI: 10.61137/ijsret.vol.10.issue6.422

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An Overview of Textual Sentiment Analysis and Emotion Recognition

An Overview of Textual Sentiment Analysis and Emotion Recognition/strong>
Authors:-Pallavi Suryavanshi, Dr Sunil Patil

Abstract-Opinion mining, another name for sentiment analysis, is a crucial task in natural language processing (NLP) that enables the extraction of subjective information from text. Sentiment analysis can use machine learning algorithms to classify opinions in text into three categories: neutral, negative, and positive. In the Internet age, social networking sites have grown rapidly, making them an essential tool for communicating emotions to individuals all over the world. Many people use music, video, photos, and text to express their ideas or perspectives. Sentiment analysis is inadequate in certain applications; therefore, emotion detection is necessary to accurately ascertain a person’s emotional and mental condition. The degrees of sentiment analysis, different models, and the steps involved in sentiment analysis and emotion detection, challenges faced are all explained in this review study.

DOI: 10.61137/ijsret.vol.10.issue6.421

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AcademEase: Revolutionizing Online Assignment Management for Enhanced Academic Efficiency

AcademEase: Revolutionizing Online Assignment Management for Enhanced Academic Efficiency/strong>
Authors:-Chethan M S, Associate Professor Dr S R Raja

Abstract-The traditional methods of managing assignments are steadily becoming outdated due to their numerous drawbacks, including inconvenience, inefficiency, and a lack of accuracy. These limitations have prompted a growing need for more effective solutions in the educational domain. With the rapid advancement of web technologies, web-based management systems have gained significant traction and are being widely adopted across various sectors. This paper presents a novel AcademEase: Revolutionizing Online Assignment Management for Enhanced Academic Efficiency that not only integrates the most effective features of existing commercial systems but also introduces innovative functionalities tailored specifically for modern assignment management needs. The proposed system addresses critical gaps in traditional practices by offering a comprehensive platform designed to streamline assignment handling processes for both administrators and students. Key features of the AMS include a user-friendly interface that simplifies the user experience, ensuring that assignments are managed in a convenient, efficient, and systematic manner. Furthermore, the system is designed with a high degree of portability and extensibility, making it adaptable to various educational environments and capable of evolving with future technological advancements. To safeguard sensitive data and ensure secure operations, the system incorporates robust, multi-layered security strategies that enhance its overall reliability. By leveraging the power of web technologies, this innovative system not only improves assignment management workflows but also sets a new benchmark for efficiency, usability, and security in academic institutions. This paper delves into the design, functionality, and benefits of the AMS, showcasing how it effectively meets the demands of modern educational practices.

DOI: 10.61137/ijsret.vol.10.issue6.420

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