Personalization in Online Car Shopping: A Data-Driven Approach
Author(s): Divya Chockalingam
Publication #: 2503078
Date of Publication: 02.01.2024
Country: United States
Pages: 1-3
Published In: Volume 10 Issue 1 January-2024
DOI: https://doi.org/10.5281/zenodo.15087123
Abstract
The online car shopping experience has evolved significantly with advancements in artificial intelligence (AI) and big data analytics. Personalization has become a crucial component in enhancing user experience, driving customer engagement, and improving conversion rates. This paper explores the role of personalization in online car shopping, the challenges faced, and the data-driven solutions that enable a tailored shopping experience. Various aspects such as machine learning algorithms, recommendation systems, and predictive analytics are discussed, along with their impact on the automotive retail industry. The paper also examines the scope of personalization in future advancements, highlighting emerging trends such as blockchain integration and AI-driven price negotiation.
Keywords: Personalization, Online Car Shopping, AI, Machine Learning, Data Analytics, Recommendation Systems, User Experience, Predictive Analytics, Big Data, Virtual Reality.
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