Application of Big Data Analytics Framework for Enhancing Customer Experience on E-Commerce Shopping Portals
Abstract
E-commerce organizations, these days, need to keep striving for constant innovation. Customers have a massive impact on the performance of an organization, so industries need to have solid customer retention strategies. Various big data analytics methodologies are being used by organizations to improve overall online customer experience. While there are multiple techniques available, this research study utilized and tested a framework proposed by Laux et al. (2017), which combines Big Data and Six Sigma methodologies, to the e-commerce domain for identification of issues faced by the customer; this was done by analyzing online product reviews and ratings of customers to provide improvement strategies for enhancing customer experience. Analysis performed on the data showed that approximately 90% of the customer reviews had positive polarity. Among the factors which were identified to have affected the opinions of the customers, the Rating field had the most impact on the sentiments of the users and it was found to be statistically significant. Upon further analysis of reviews with lower rating, the results attained showed that the major issues faced by customers were related to the product itself; most issues were more specifically about the size/fit of the product, followed by the product quality, material used, how the product looked on the online portal versus how it looked in reality, and its price concerning the quality.
Degree
M.Sc.
Advisors
Springer, Purdue University.
Subject Area
Commerce-Business|Marketing
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