Story

Congratulations to Krish for designing “Customer service chatbot with sentiment analysis”
&
being part of the upcoming
MoonBattle Conference 2024 in Milpitas, Silicon Valley

My project uses sentiment analysis to generate a response based on the sentiment of the user after answering a question/prompt given by the computer. It generates a polarity score based on the user’s response that determines the sentiment. The score ranges from -1 to +1 and is generated with the help of python’s Textblob library.

My project makes customer service effortless, powered by sentiment analysis to detect the mood of the user, and then generate a response accordingly. My program chooses from a pool of questions such as “Have you shopped with us before? If yes, what was your previous experience?” and  “Were you able to find everything that you were looking for?”, and then takes an answer from the user. Once the answer has been provided, a sentiment score ranging from -1 to +1 is generated (lower scores indicate sad and angry emotions and vice versa). After the score is generated, the program selects a response to output accordingly. To conclude, we can harness the power of sentiment analysis to greatly improve customer service.

If you like Krish’ project, support “Customer service chatbot with sentiment analysis” by sharing and liking it.

Story

• Develop a chatbot to automatically analyze user feedback and generate appropriate responses using natural language processing.
• Provide a tool to streamline communication processes and improve customer satisfaction by efficiently addressing user concerns and inquiries.