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DON HONORIO VENTURA STATE UNIVERSITY
COLLEGE OF COMPUTING STUDIES
Enhancing Customer Experiences through Personalized E-commerce
GROUP CODE GROUP MEMBERS ADVISER
INTRODUCTION
The e-commerce industry has witnessed exponential growth over the past few years, changing businesses' and consumers' shopping habits. E-commerce has experienced remarkable growth and has become an integral part of global retail. Parts of the online economy have boomed since COVID-19 began, while some pre-pandemic big-hitters have seen a reversal of their fortunes in the last years. As a result, the e- commerce market has become fiercely competitive, with businesses for customers' attention and loyalty. One key aspect that has emerged as a crucial determinant of success in the e-commerce sector is personalized shopping experiences. E-commerce personalization refers to the practice of creating personal interactions and experiences for customers online. Personalization can be based on a customer's previous purchases, browsing behavior, geographic location, language and other personal information. It covers the whole customer journey, from product discovery to post-purchase interactions, and goes beyond simply making product recommendations.
COLLEGE OF COMPUTING STUDIES
OBJECTIVES OF THE STUDY
The objectives of a study focused on enhancing customer experiences through personalized e-commerce can vary depending on the specific context and goals of the research. Specifically:
- To enhance the customer experience and satisfaction, making it more relevant and appealing.
- To increase customer loyalty and retention by making customers feel valued and understood.
- To improve conversion sales rates and sales by recommending complementary or higher-value items based on a customer's browsing and purchase history.
SCOPE AND LIMITATION
Enhancing customer experience through personalized e-commerce offers numerous advantages, but it also comes with its own set of scope and limitations. The scope of personalized e-commerce lies in its ability to tailor the shopping experience to individual preferences and behaviors. e-commerce platforms can analyze past purchases, browsing history, and demographic information to recommend products and content that are most relevant to each customer. This personalization can lead to increased customer satisfaction, higher conversion rates, and ultimately, greater loyalty and repeat business Moreover, personalized e-commerce allows for targeted marketing efforts, enabling companies to deliver customized promotions and messages that resonate with
COLLEGE OF COMPUTING STUDIES experiences involve tailoring product recommendations, content, and marketing messages to the specific needs and preferences of individual customers. This approach aims to create a more engaging and relevant online shopping experience, ultimately driving higher customer satisfaction and loyalty. In the literature on personalized e-commerce, various methods and techniques have been explored to achieve effective personalization. Collaborative filtering, content-based filtering, and hybrid recommendation systems are commonly used approaches. Collaborative filtering analyzes user behavior and preferences to make recommendations based on the behavior of similar users, while content-based filtering relies on the attributes of products and users to make recommendations. Hybrid recommendation systems combine these approaches to provide more accurate and diverse recommendations C. Personalized E-commerce Recommendations: Recommendation systems are special personalization tools that help users to find interesting information and services in complex online shops. Even though today's e-commerce environments have drastically evolved and now incorporate techniques from other domains and application areas such as Web mining, semantics, artificial intelligence, user modeling and profiling, etc. setting up a successful recommendation system is not a trivial or straightforward task. This paper argues that by monitoring, analyzing and understanding the behavior of customers, their demographics, opinions, preferences and history, as well as taking into consideration the specific e-shop ontology and by applying Web mining techniques, the effectiveness of produced recommendations can be significantly improved. In this way, the e-shop may upgrade users'
COLLEGE OF COMPUTING STUDIES interaction, increase its usability, convert users to buyers, retain current customers and establish long-term and loyal one-to-one relationships.
REFERENCES
Enhancing User Experience in E-Commerce through Personalization Algorithms Bok, Sun Khi (2023) Desaid, Darshana. (2020). A study of Personalization effect on Users Satisfaction with E Commerce Websites. Felix, Antonius & Rembulan, Glisina. (2023). Analysis of Key Factors for Improved Customer Experience, Engagement, and Loyalty in the E-Commerce Industry in Indonesia. Aptisi Transactions on Technopreneurship (ATT). 5. 196-208. 10.34306/att.v5i2sp.350. Martasari, Gacelia. (2023). Impact of Industrial Technology 4.0 In Improving Service Quality and Customer Experience on E-Commerce Platforms: Literature Review. International Journal of Social Service and Research. 3. 1427-1435. 10.46799/ijssr.v3i6.407. Kanth, Mangalagiri & Mujeeb, Mohd & Harshitha, Manda & Rajinesh, Chennoju & Bhukya, Madhu & Reddy, G. & Sobti, Rajeev. (2024). Personalizing the E- Commerce – Experience: A Recommendation System. MATEC Web of Conferences.
- 10.1051/matecconf/202439201095. P. Markellou, I. Mousourouli, S. Sirmakessis and A. Tsakalidis, "Personalized e- commerce recommendations," IEEE International Conference on e-Business Engineering (ICEBE'05) , Beijing, China, 2005, pp. 245-252, doi: 10.1109/ICEBE.2005.95.
