Enhancing Retail Customer Service with NLP
The Role of Natural Language Processing in Improving Consumer Interactions
Big Data
NLP
Customer Service
Chatbot
Machine Learning
Thesis project description
This thesis will delve into applying natural language processing (NLP) in the retail sector to enhance customer service. It will explore using NLP in chatbots for customer support, sentiment analysis of customer feedback, and its overall impact on improving the customer experience and engagement in retail businesses.
* Despite being enrolled at Aalborg University, I've taken this semester at CBS, so I'm primarily interested in collaborating with Greater Copenhagen companies.
Managerial value of the research
This thesis offers a unique opportunity for a retail company to pioneer customer service innovation through Natural Language Processing (NLP). By investigating advanced NLP applications like chatbots and sentiment analysis, the collaboration aims to boost customer interactions and satisfaction. The critical value lies in gaining early insights into consumer preferences and behaviour, providing the partnering company with a strategic edge. This collaboration will contribute to enhanced customer service practices and position the company as a leader in embracing cutting-edge technology for competitive advantage in the retail sector.
Research topic motivation
The decision to focus on NLP in retail customer service is deeply rooted in our previous project experience, where we developed a chatbot to assist mentally challenged individuals. This endeavor showcased the profound impact of NLP in aiding communication and sparked my curiosity about its broader applications in different sectors. The potential of NLP to revolutionize customer service in the retail industry, especially in enhancing interaction and engagement, is particularly compelling. This area combines my passion for technological innovation with the opportunity to make a substantial impact on everyday consumer experiences. I am motivated by the prospect of exploring this cutting-edge technology in a dynamic industry, where it can significantly enhance the quality of customer interactions and business operations.
Why collaborate with us
My background as a Business Intelligence Analyst combined with my academic focus in Business Data Science uniquely positions me for this thesis. With hands-on experience developing NLP applications and a solid foundation in business and finance, I bring a rare blend of technical know-how and business insight. This combination ensures that the solutions I develop are technically sound and strategically aligned with business goals. My commitment to innovation and a results-driven approach make me a valuable partner for any company looking to explore the potential of NLP in enhancing customer service.
![](https://excelerate.dk/wp-content/uploads/dk-aau.png)
Project information
Project type
Thesis project
Collaboration semester
Spring 2024
Collaboration duration
13 to 21 weeks.
Collaboration start date
2024-01-01
Number of student
1
Collaboration language
English
Interested in a collaboration?
Project Researcher #1
Researcher bio
Pursuing an MSc in Business Data Science I specialize in machine learning, deep learning, transformer models, and MLOps, focusing on practical business applications. As a former Business Intelligence Analyst, I've effectively utilized Tableau, Python, and SQL for insightful Big Data analysis to guide business decision-making. Passionate about data science, I am eager to contribute my analytical skills and innovative thinking in the data science realm. The fun thing about me is that I am a snow addicted person and one of my hobbies is by analyzing meteorological maps to predict the weather for the next few days :)
Passion and motivation
I am passionate about Big Data and finding patterns to extract meaningful insights. Having a specific goal is a motive for me to be focused on achieving this.
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