Advances in Consumer Research
Issue 2 : 873-878
Original Article
Machine Learning for Product Development: Predicting Consumer Preferences and Market Trends
 ,
 ,
 ,
1
Assistant Professor, Department of Management Studies, Middle East College, Muscat, Oman
2
Senior Lecturer, Department of Management Studies, Middle East College, Muscat, Oman
Abstract

Product administrators may now make better choices about costs, advertising, and development of products thanks to machine learning (ML), which is transforming analytical forecasting. They may search through enormous databases for unseen relationships or trends using this equipment, which gives them fresh perspectives on how decisions are made. A person pursuing a career in machine learning product management has to be well-versed in statistical analysis, mathematics, and the constraints of adaptive programming. To predict future trends and make better judgments about managing products, advanced machine learning algorithms can evaluate previous sales data. Additionally, they may use consumer preferences for items to tailor recommendations to make items and services stand out and inspire fresh, clever ideas for internet marketing. Managers of products may also benefit from using machine learning technologies to set goals for developing products and discover features that consumers find most useful.

Keywords
Recommended Articles
Original Article
Exploring the Impact of Hybrid Work Enablers on Employee Productivity: An empirical study with special reference to IT Sector in Delhi NCR
...
Original Article
The Effect of Multichannel Services on Customer Engagement Mediated by Brand Trust and Brand Commitment with Offline and Online Familiarity as Moderation at the Southeast Sulawesi Regional Development Bank
...
Original Article
Dialogues of Knowledge for Agroecology: Participatory Strategies for Peasant Strengthening in Boyacá
...
Original Article
The Contributions Of Non-Muslim Local Civilians In The Islamic Conquests. (3-40 AH / 625-660 AD)
Loading Image...
Volume 2, Issue 2
Citations
272 Views
340 Downloads
Share this article
© Copyright Advances in Consumer Research