CUSTOMER OPINION ASSESSMENT USING ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING
Abstract
The consumer service has to be provided for every kind of product and organization. Be it day to day basic smartphone or high end car, its always backed up by the customer support team who is with consumer from the day one of the purchase. The support team takes care of introducing buyer to the new product, providing necessary details about functionality and features. As the product gets older, it requires maintenance and then service centers, customer support team pitches again. Most of the time customer at least visits authorized service centers until product is in warranty before seeking help from someone novice. In this complete lifecycle of product apart from product itself consumer does have fair number of interactions with support team, and this support team is always considered as single point of contact and owner for anything that goes wrong with product. Considering this huge part of customer support to make remarkable impact on how that product is going to perform in future is important factor. With the help of artificial neural network its possible to understand what went fantastic or awful when dealing with customers in past, this historic data can be used to train neural networks to avoid such mistakes to thrive on consumer service satisfaction.
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How to Cite This Article
Amit Ganesh Upadhye and A.C Lomte (2020); CUSTOMER OPINION ASSESSMENT USING ARTIFICIAL NEURAL NETWORKS AND MACHINE LEARNING, Int. J. of Adv. Res., 8 (07), 1829-1835, ISSN 2320-5407. DOI: https://doi.org/10.21474/IJAR01/11451
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This work is licensed under a Creative Commons Attribution 4.0 International License.





