RetailGPT: A Fine-Tuned LLM Architecture for Customer Experience and Sales Optimization

In today’s fast-paced retail environment, customer experience quality has become a key determinant of business success. RetailGPT is an AI system designed to revolutionize retail operations by offering personalized shopping experiences, automated customer service, and insights into inventory management. Powered by deep learning algorithms, RetailGPT analyzes data from e-commerce transactions, customer interactions, and sales records to predict consumer behavior with high accuracy.RetailGPT’s core feature is personalized product recommendations, which enhance customer satisfaction and boost sales by suggesting products that align with individual preferences. It also employs advanced sentiment analysis to gauge customer emotions and feedback in real time, allowing retailers to swiftly adjust their strategies for improved service quality.RetailGPT streamlines customer interactions, reduces wait times, cuts operational costs, and enhances engagement. Beyond answering FAQs, it learns from each interaction, continually refining its response accuracy. Additionally, RetailGPT provides data-driven sales optimization strategies by analyzing sales trends and forecasting future demand, aiding retailers in making informed decisions on stock levels and marketing campaigns. With visual tools like sales trend graphs, recommendation accuracy plots, customer satisfaction heatmaps, and inventory forecasts, RetailGPT offers managers actionable insights into business performance, enabling them to address issues promptly. As a disruptive solution, RetailGPT not only enhances customer experiences but also optimizes sales operations, helping retailers achieve better business outcomes and foster customer loyalty.

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Publication Details

Published
2024-10-23
DOI
https://doi.org/10.1109/icssas64001.2024.10760685
Citations
4
Primary Topic
Traffic Prediction and Management Techniques
Type
article
Field-Weighted Citation Impact
1.06
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article

RetailGPT: A Fine-Tuned LLM Architecture for Customer Experience and Sales Optimization

Farooq Shareef, Rishi Ajith, Parth Kaushal, Karthik Sengupta
4 citations
Traffic Prediction and Management Techniques
1.06
article

RetailGPT: A Fine-Tuned LLM Architecture for Customer Experience and Sales Optimization

Farooq Shareef, Rishi Ajith, Parth Kaushal, Karthik Sengupta
article en
4 citations

Abstract

In today’s fast-paced retail environment, customer experience quality has become a key determinant of business success. RetailGPT is an AI system designed to revolutionize retail operations by offering personalized shopping experiences, automated customer service, and insights into inventory management. Powered by deep learning algorithms, RetailGPT analyzes data from e-commerce transactions, customer interactions, and sales records to predict consumer behavior with high accuracy.RetailGPT’s core feature is personalized product recommendations, which enhance customer satisfaction and boost sales by suggesting products that align with individual preferences. It also employs advanced sentiment analysis to gauge customer emotions and feedback in real time, allowing retailers to swiftly adjust their strategies for improved service quality.RetailGPT streamlines customer interactions, reduces wait times, cuts operational costs, and enhances engagement. Beyond answering FAQs, it learns from each interaction, continually refining its response accuracy. Additionally, RetailGPT provides data-driven sales optimization strategies by analyzing sales trends and forecasting future demand, aiding retailers in making informed decisions on stock levels and marketing campaigns. With visual tools like sales trend graphs, recommendation accuracy plots, customer satisfaction heatmaps, and inventory forecasts, RetailGPT offers managers actionable insights into business performance, enabling them to address issues promptly. As a disruptive solution, RetailGPT not only enhances customer experiences but also optimizes sales operations, helping retailers achieve better business outcomes and foster customer loyalty.

Indraprastha Institute of Information Technology Delhi (IN), Indiana Wesleyan University (US), Vellore Institute of Technology University (IN)
Openalex Percentile: Top 23%
Traffic Prediction and Management Techniques
1.06
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