Please use this identifier to cite or link to this item:
https://repository.iimb.ac.in/handle/2074/20039
Title: | NPS prediction for GE | Authors: | Malhotra, Siddharth Jain, Rhythm |
Keywords: | Net Promoter Score (NPS);NPS prediction;Customer feedback;Customer loyalty;Customer behavior | Issue Date: | 2019 | Publisher: | Indian Institute of Management Bangalore | Series/Report no.: | PGP_CCS_P19_170 | Abstract: | Net Promoter Score (NPS) is a tool used by firms to gauge loyalty of its customers. It measures their willingness to recommend company’s products and services to others. Customers are asked to rate company’s products and services on a scale of 0-10. Based on their rating customers are classified into 3 categories – Detractors (score <= 6), Passives (score 7-8) and Promoters (9-10). Net Promoter Score is calculated by subtracting percentage of promoters from percentage of detractors. GE Medical offers wide range of medical services ranging from imaging, ultrasound, software to life sciences solutions. GE Medical wants to review the loyalty of its customers across different products and services. The cost of acquiring a customer is way more than retaining the existing ones. A loyal customer will reduce annual cost and create a positive word of mouth. Hence, we would be looking at NPS to gauge difference between promoters and detractors across different GE Medical products and services. Our ultimate objective is to find out the reasons for customers becoming detractors. The dataset given to us was a consolidated customer feedback dataset across various products/services that GE Medical provides. The most important component of the dataset was the NPS and customer feedback associated with it. The feedback talked about reasons for the given rating and the areas of improvement for Wipro GE Healthcare services. Additionally, it contained product details like Model ID, Modality, System ID etc. It also contained some customer details like Owner’s Name, Location etc. Moreover, the data also mentioned date/month/week of feedback, NPS agent name and other details. | URI: | https://repository.iimb.ac.in/handle/2074/20039 |
Appears in Collections: | 2019 |
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File | Size | Format | |
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PGP_CCS_P19_170.pdf | 1.99 MB | Adobe PDF | View/Open Request a copy |
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