<div>
<p>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. </p>
<p>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.</p>
</div>
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| Identifer | oai:union.ndltd.org:purdue.edu/oai:figshare.com:article/12221978 |
| Date | 01 May 2020 |
| Creators | Nimita Shyamsunder Atal (8785316) |
| Source Sets | Purdue University |
| Detected Language | English |
| Type | Text, Thesis |
| Rights | CC BY 4.0 |
| Relation | https://figshare.com/articles/APPLICATION_OF_BIG_DATA_ANALYTICS_FRAMEWORK_FOR_ENHANCING_CUSTOMER_EXPERIENCE_ON_E-COMMERCE_SHOPPING_PORTALS/12221978 |
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