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A Proposed Framework for Measuring Customer Satisfaction and Product Recommendation for Ecommerce

by Sree Lakshmi Addepalli, Sree Gowri Addepalli, Monica Kherajani, Harsha Jeshnani, Sujata Khedkar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 138 - Number 3
Year of Publication: 2016
Authors: Sree Lakshmi Addepalli, Sree Gowri Addepalli, Monica Kherajani, Harsha Jeshnani, Sujata Khedkar
10.5120/ijca2016908757

Sree Lakshmi Addepalli, Sree Gowri Addepalli, Monica Kherajani, Harsha Jeshnani, Sujata Khedkar . A Proposed Framework for Measuring Customer Satisfaction and Product Recommendation for Ecommerce. International Journal of Computer Applications. 138, 3 ( March 2016), 30-35. DOI=10.5120/ijca2016908757

@article{ 10.5120/ijca2016908757,
author = { Sree Lakshmi Addepalli, Sree Gowri Addepalli, Monica Kherajani, Harsha Jeshnani, Sujata Khedkar },
title = { A Proposed Framework for Measuring Customer Satisfaction and Product Recommendation for Ecommerce },
journal = { International Journal of Computer Applications },
issue_date = { March 2016 },
volume = { 138 },
number = { 3 },
month = { March },
year = { 2016 },
issn = { 0975-8887 },
pages = { 30-35 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume138/number3/24362-2016908757/ },
doi = { 10.5120/ijca2016908757 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:38:43.827556+05:30
%A Sree Lakshmi Addepalli
%A Sree Gowri Addepalli
%A Monica Kherajani
%A Harsha Jeshnani
%A Sujata Khedkar
%T A Proposed Framework for Measuring Customer Satisfaction and Product Recommendation for Ecommerce
%J International Journal of Computer Applications
%@ 0975-8887
%V 138
%N 3
%P 30-35
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Ecommerce is a significant part in the global economy. Ecommerce websites users have high suppositions for the quality of products or services it provides, and if they are not met, the next ecommerce site is only a click away. Managing customer satisfaction, trust and loyalty of ecommerce services is very important for the long-term growth of many businesses. The tremendous growth of consumer-generated content on these sites has led to the development of big data analytics to solve real-life problems. This study aims to examine and demonstrate the utility of big data analytics to understand various important ecommerce-issues, namely the relationship between customer product reviews and satisfaction. Specifically, this study acknowledges semantic analysis and machine learning approach to a large quantity of consumer reviews to deconstruct consumer product reviews and examine its association with satisfaction ratings. This paper studies various approaches to build a framework for an ecommerce which is capable of assessing and modeling satisfaction of customers as well as deducing business intelligence for managers from online product reviews.

References
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Index Terms

Computer Science
Information Sciences

Keywords

Ecommerce Customer satisfaction Business Intelligence Big Data Analytics Product Reviews Framework Customers Managers Features Semantic Analysis Sentiment Score Machine Learning Recommendations Visualization Metrics.

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