Exploring Shopping Opportunities and Elevating Customer Experiences Through AI-Powered E-Commerce Strategies
- Title
- Exploring Shopping Opportunities and Elevating Customer Experiences Through AI-Powered E-Commerce Strategies
- Creator
- Maurya N.; Singh J.; Singh N.P.; Chaudhary A.; Patil S.; Tiwari M.
- Description
- This research explores the efficacy of clustering algorithms in enhancing customer experiences within the e-commerce landscape. Through experiment trials utilizing K-means and DBSCAN clustering techniques, valuable insights have been gleaned. The trials yielded silhouette scores ranging from 0.55 to 0.72, indicating moderate to good clustering quality across different experiments. In K-means clustering, the number of clusters varied from 3 to 6, with inertia values spanning approximately 722.41456.8. Conversely, DBSCAN clustering resulted in varying cluster numbers, ranging from 2 to 4, contingent on the combinations of epsilon and min_samples values explored. These findings underscore the significance of judiciously selecting clustering algorithms and parameter settings to achieve meaningful segmentation of e-commerce data. Effective utilization of clustering algorithms empowers businesses to discern valuable insights into customer behavior, preferences, and patterns. Consequently, businesses can tailor their strategies to deliver personalized experiences, targeted marketing campaigns, and optimized product recommendations. This research propels the exploration of additional clustering techniques and parameter refinements for enhanced clustering performance in e-commerce applications. The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2024.
- Source
- Lecture Notes in Networks and Systems, Vol-1117 LNNS, pp. 149-159.
- Date
- 2024-01-01
- Publisher
- Springer Science and Business Media Deutschland GmbH
- Subject
- Clustering algorithms; Customer experiences; E-commerce; Personalized recommendations; Segmentation
- Coverage
- Maurya N., Department of Management, KCC Institute of Legal and Higher Education, Greater Noida, India; Singh J., Alliance School of Advanced Computing, Alliance University, Bengaluru, India; Singh N.P., School of Computer Science Engineering and Technology, Bennett University, Greater Noida, India; Chaudhary A., School of Law, CHRIST (Deemed to be University) Delhi-NCR, Ghaziabad, India; Patil S., Dr. D. Y. Patil Vidyapeeth, Centre for Online Learning, Pimpri, Pune, India; Tiwari M., Department of Computer Science and Engineering, Bharati Vidyapeeths College of Engineering, Delhi, India
- Rights
- Restricted Access
- Relation
- ISSN: 23673370; ISBN: 978-981976991-9
- Format
- Online
- Language
- English
- Type
- Conference paper
Collection
Citation
Maurya N.; Singh J.; Singh N.P.; Chaudhary A.; Patil S.; Tiwari M., “Exploring Shopping Opportunities and Elevating Customer Experiences Through AI-Powered E-Commerce Strategies,” CHRIST (Deemed To Be University) Institutional Repository, accessed February 25, 2025, https://archives.christuniversity.in/items/show/19010.