Application of Text Mining on Customer Buying Pattern of Cosmetic Products
Athira K1, Dhanya M2, Sinita S Ashok3

1Athira K*, Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India.
2Dr Dhanya M, Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India.
3Sinita S Ashok, Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India.

Manuscript received on April 02, 2020. | Revised Manuscript received on April 21, 2020. | Manuscript published on May 30, 2020. | PP: 904-908 | Volume-9 Issue-1, May 2020. | Retrieval Number: A2071059120/2020©BEIESP | DOI: 10.35940/ijrte.A2071.059120
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC-BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)

Abstract: The cosmetic industry is one of the major emerging trends in the present world. People are very keen on purchasing cosmetic products, and at the same time, they are very conscious in choosing the right cosmetic items. While making their purchase decisions, customers refer to previous online reviews and the ratings given for that particular product by those who have already purchased, which helps them to get a clear idea about that product. This research paper has focused on looking at the indicators that make the customer’s satisfied or dissatisfied towards the purchase-related decisions of cosmetics. Text analysis of the online reviews and the ratings given by customers from the leading e-commerce websites have been analyzed in this paper. The present study focused on understanding some cosmetics attributes that lead to customer satisfaction and dissatisfaction using online reviews. The commonly used attributes from the online text reviews were identified and classified on the polarity basis through the text mining analysis and hence finding out the buying pattern of the customers on cosmetic products.
Keywords: Sentimental Analysis, Cosmetic Products, Quality, Buying Behavior.
Scope of the Article: Data Mining