An Investigation of AI-Powered Recommendation Systems in Nigerian Retail: A Case Study of Supermarkets in Kano State
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Background of the Study
AI-powered recommendation systems have become indispensable tools in the retail industry, offering personalized product suggestions to customers based on their preferences, purchase history, and browsing behavior. These systems enhance customer experience, drive sales, and improve inventory management by leveraging machine learning algorithms and big data analytics (Huang et al., 2023).
In Kano State, the retail sector is expanding, with supermarkets adopting innovative technologies to remain competitive. However, the use of AI-powered recommendation systems remains at a nascent stage. This study explores the adoption and impact of recommendation systems in supermarkets in Kano State, focusing on their role in enhancing customer satisfaction and business performance.
Statement of the Problem
Retail supermarkets in Kano State face challenges such as inventory mismanagement, low customer retention, and limited personalization in customer interactions. AI-powered recommendation systems offer solutions to these challenges but are underutilized due to factors such as cost, technical know-how, and infrastructure limitations (Ahmed & Yusuf, 2024). This study investigates the implementation and effectiveness of recommendation systems in the retail sector in Kano State.
Objectives of the Study
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To assess the adoption of AI-powered recommendation systems in supermarkets in Kano State.
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To evaluate the impact of recommendation systems on customer satisfaction and sales performance.
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To identify challenges to the implementation of AI-powered recommendation systems in the retail sector.
Research Questions
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What is the adoption level of AI-powered recommendation systems in supermarkets in Kano State?
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How do recommendation systems impact customer satisfaction and sales performance?
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What challenges hinder the implementation of recommendation systems in the retail sector?
Research Hypotheses
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There is no significant relationship between recommendation system adoption and customer satisfaction.
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AI-powered recommendation systems do not significantly influence sales performance.
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Challenges to implementing recommendation systems are not significant in the retail sector in Kano State.
Scope and Limitations of the Study
The study focuses on supermarkets in Kano State, analyzing their use of AI-powered recommendation systems. Limitations include differences in technological adoption rates and the availability of customer purchase data.
Definitions of Terms
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AI-Powered Recommendation Systems: Technology that uses artificial intelligence to provide personalized product suggestions to customers.
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Retail Sector: Businesses involved in selling goods directly to consumers, including supermarkets.
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Customer Satisfaction: The degree to which customers are pleased with a product or service.
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