Application of web Metrics and Text Mining on the IRCTC Portal
Adwaith KT1, Athira K2, Krishnapriya S3, Reuben Thomas Mathew4

1Reuben Thomas Mathew*, Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India.
2Krishnapriya S, Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India.
3Athira K, Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India.
4Adwaith KT, Department of Management, Amrita Vishwa Vidhyapeetham, Kochi, India.
Manuscript received on March 12, 2020. | Revised Manuscript received on March 26, 2020. | Manuscript published on March 30, 2020. | PP: 4805-4810 | Volume-8 Issue-6, March 2020. | Retrieval Number: F9897038620/2020©BEIESP | DOI: 10.35940/ijrte.F9897.038620

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Abstract: The Indian railways, a historical inheritance, the 4th largest railway network in the world by size, is an important force in our economy. The digitalization has enabled the customer to get the railway services on their finger tip. IRCTC, the subsidiary of the Indian railway offers variety of service like catering, tourism and the online ticket operation. As technology advancement is taking place, but the IRCTC has been widely criticized for many lacunas in meeting the customer needs and preference. So the study focuses on how Indian Railway needs to revamp the website to make it more contributing to customer expectations. An analysis of customer reviews, revealed that the customers experience many problems while using the IRCTC website to make their choice about the type of travel, coach preference, seat preferences, age group, payment gateways, time and date of travel, etc. The study attempts to find out the user-friendliness of IRCTC website from the point of view of the customers using four identified dimensions or variables. The analysis was done using various web metrics and a text-mining based on the customer reviews. It helped to know about the clicks rates pattern, visit rate, the various activities performed by the customer, time spent, type of device used, keywords used etc. The result shows that majority users have stated negatively towards the features and usability of the website. Based on the analysis of the study a brief summary of findings have been made and a meaningful conclusion have been obtained.
Keywords: Customer preferences, Website, Web analytics, Website features.
Scope of the Article: Visual Analytics.