Customer Behaviour Analysis of E-commerce: What information can we get from customers' reviews through big data analysis
2019 (English)Independent thesis Advanced level (degree of Master (One Year)), 10 credits / 15 HE credits
Student thesis
Abstract [en]
Online transactions have been growing exponentially in the last decade, contributing to up to
11% of total retail sales. One of the parameters of success in online transactions are online
reviews where customers have the chance to assign level of satisfaction regarding their
purchase. This review system acts as a bargaining power for customers so that their
suppliers pay more attention to their satisfaction, as well as benchmark for future prospective
customers. This research digs into what actually causes customers to assign high level of
satisfaction in their online purchase experience: Whether it is packaging, delivery time or
else. This research also tries to dig into customer behaviour related to online reviews from
three different perspectives: gender, culture and economic structure. Data mining
methodology is used to collect and analyse the data, thus providing a reliable quantitative
study. The end result of this study is expected to assist in marketing decisions to capture
certain types of consumers who significantly place or purchasing decision based on online
reviews.
Place, publisher, year, edition, pages
2019. , p. 37
Series
TRITA-ITM-EX ; 2019:212
Keywords [en]
Customer behaviour analysis, Online reviews, text analysis, cultures, genders, e-commerce
National Category
Other Engineering and Technologies
Identifiers
URN: urn:nbn:se:kth:diva-254194OAI: oai:DiVA.org:kth-254194DiVA, id: diva2:1328724
Subject / course
Entrepreneurship and Innovation Management
Educational program
Master of Science - Industrial Engineering and Management
Presentation
2019-05-28, 243, Lindstedtsvägen 30, Stockholm, 23:22 (English)
Supervisors
Examiners
Projects
Entrepreneurship & Innovation Management2019-09-062019-06-222025-02-10Bibliographically approved