MEASURING CUSTOMER SATISFACTION OF AN E-COMMERCE COMPANY BASED ON OPINION MINING USING SVM ALGORITHM, CSI AND IPA

Measuring customer satisfaction of an e-commerce company based on opinion mining using SVM algorithm, CSI and IPA

Measuring customer satisfaction of an e-commerce company based on opinion mining using SVM algorithm, CSI and IPA

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This study was carried out to examine the perceived service quality of an cortech sonic-flo gloves e-commerce company app users and the measures that may be taken to improve customer satisfaction.The analysis techniques used were opinion mining to analyse reviews on the Google Play Store, e-SERVQUAL and Customer Satisfaction Index (CSI) to assess customer satisfaction, and Importance Performance Analysis (IPA) to identify elements that require improvement.According to the findings of opinion mining, 65.86% of e-commerce company application users were satisfied, while 34.

14% were dissatisfied.Customer satisfaction levels were classified as satisfied for the dimensions of efficiency and reliability, and fairly satisfied for the dimensions of fulfilment, compensation, and responsiveness, based on questionnaire red prairie spy apple distribution.The Importance Performance Analysis method was used to determine the priority for service quality improvement.Findings showed that delivery time, product suitability, refund and return policy, and service time were the top priorities for service improvement.

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