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Evaluating Customer Experience and Satisfaction dynamics in online platforms

Authors: Tamanna Jeswani; Sneha Banga;

Evaluating Customer Experience and Satisfaction dynamics in online platforms

Abstract

The growing popularity of e-commerce platforms has significantly altered the way consumers make purchases through the integration of Artificial Intelligence (AI) personalization and social media interactions. This paper assesses the dynamics of customer experience and satisfaction with digital marketplaces by analysing the impact of technological innovation and interactive platforms on consumer buying behaviour and trust building.The existing literature acknowledges that AI-powered recommendation platforms, chat-bots, and advertising increase convenience and engagement, while social media interactions affect buying decisions through reviews, influencer marketing, and social proof. Nevertheless, the existing literature primarily concentrates on the consumer side and tends to analyse the impact of AI personalization and social media interactions individually. The proposed research work will follow a quantitative research methodology with the aid of qualitative knowledge. The target population will comprise people of all age groups (below 18 to above 40 years) living in Jaipur, Rajasthan. A sample of 100 participants was chosen through non-probability snowball sampling. Primary data was gathered from online marketplace users, including students, professionals, businesspeople, and industrial participants, through a structured Google Form questionnaire, while qualitative knowledge was obtained from focus group discussions. The proposed research work will attempt to create a triangular knowledge base of the relationship between customers, sellers, and corporations in AI-powered marketplaces. The proposed research work will attempt to create a triangular knowledge base of the relationship between customers, sellers, and corporations in AI-powered marketplaces.

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
0
Average
Average
Average
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