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Enhancing Visitor Experience at ISKCON Using Text Analytics
內容大綱
Janarthanan Balasubramanian, Division Head, Information Technology and online Communications at ISKCON wanted to understand the visitor feedback so that appropriate measures can be taken to improve the visitor experience at ISKCON. The primary problem at hand for Janarthanan was to reduce the existing manual effort for his team. Currently three resources are involved in collecting the reviews from social platforms and labeling each review into one of the four classes, viz. positive, negative, neutral and mixed. Two other resources convert the reviews from paper feedback forms/feedback registers placed at different points inside the temple, to an Excel file. The team begins its day by manually collecting, labeling and collating the reviews in an Excel file. At the end of the day, these labelled reviews would be stored in the database. At the end of the week, the total count of reviews for the four classes, viz. positive, negative, neutral and mixed was calculated to understand the overall sentiment. This was an extremely time-consuming manual process from data collection, that is, manually copy pasting the comments from social mediums to data collation and labeling. Janarthanan wanted his team to spend time and effort on analyzing the data and working on remedial actions. He wanted to understand the issues/topics that ISKCON should work on, rather than manually classify reviews and get the count of each review type. Janarthanan felt that getting only the split of positive/negative/neutral/mixed classes is not enough to draw inferences.