| Autor: |
Somkunwar, Rachna, Gupta, Anil Kumar, Jain, Ishika, Shilvant, Neha, Pandey, Rashi, Deshpande, Shreyas |
| Předmět: |
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| Zdroj: |
International Research Journal of Innovations in Engineering & Technology; 2023 Special Issue, Vol. 7, p116-120, 5p |
| Abstrakt: |
Businesses often underestimate the power of customer care or customer support to grow their revenues. Customers often receive generic responses that do not address their specific needs or emotions, leading to a lack of connection and dissatisfaction. Long wait times and slow response times can be frustrating for customers and lead to decreased satisfaction. Moreover poorly trained customer service agents can struggle to handle complex customer inquiries and provide adequate support, leading to dissatisfaction. They may not be able to accurately detect the emotional state of the customer, leading to an inappropriate response and further dissatisfaction. This can lead to shutting down of businesses. This paper proposes a system to provide a more personalized and empathetic response to customers by building a model using MLP Classifier. We are optimistic that our system based on MLP Classifier is more reliable as compared to the rest of the models available currently. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Complementary Index |
| Externí odkaz: |
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