Rate the Article: Enhancing Customer Experience through Personalized Recommendations: A Machine Learning Approach, IJSR, Call for Papers, Online Journal
International Journal of Science and Research (IJSR)

International Journal of Science and Research (IJSR)
Call for Papers | Fully Refereed | Open Access | Double Blind Peer Reviewed

ISSN: 2319-7064

Downloads: 7 | Views: 307 | Weekly Hits: ⮙2 | Monthly Hits: ⮙2

Informative Article | Data & Knowledge Engineering | India | Volume 11 Issue 9, September 2022 | Rating: 5 / 10


Enhancing Customer Experience through Personalized Recommendations: A Machine Learning Approach

Sai Kalyana Pranitha Buddiga, Siddhartha Nuthakki


Abstract: This paper explores how machine learning algorithms can be leveraged to enhance customer experience through personalized recommendations. In today's competitive market landscape, businesses strive to deliver tailored recommendations to their customers to increase engagement, retention, and revenue. By analyzing customer behavior and preferences, machine learning models can predict individualized recommendations for products, services, and content. This paper discusses various machine learning techniques, such as collaborative filtering, content-based filtering, hybrid approaches, and their applications in recommendation systems. Additionally, it examines challenges, best practices, and emerging trends in the field of personalized recommendations, offering insights for businesses seeking to implement effective recommendation systems.


Keywords: Recommender Systems, Machine Learning, Collaborative Filtering, Content-Based Filtering, Customer Experience


Edition: Volume 11 Issue 9, September 2022,


Pages: 1265 - 1267



Rate this Article


Select Rating (Lowest: 1, Highest: 10)

5

Your Comments (Only high quality comments will be accepted.)

Characters: 0

Your Full Name:


Your Valid Email Address:


Verification Code will appear in 2 Seconds ... Wait

Top