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THE IMPACT OF ARTIFICIAL INTELLIGENCE APPLICATIONS IN PRODUCT PRICING STRATEGIES: A CASE STUDY OF RETAIL MARKETS IN PLATEAU STATE

  • Project Research
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  • Abstract : Available
  • Table of Content: Available
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  • NGN 5000

Background of the Study

Pricing is a critical factor influencing consumer purchasing decisions and business profitability. In Plateau State’s retail markets, traditional pricing strategies are often based on intuition or manual analysis, which can lead to inconsistencies and missed opportunities for optimization.

AI has revolutionized product pricing strategies by offering tools for demand forecasting, competitor analysis, and dynamic pricing. These applications enable businesses to adjust prices in real-time based on market trends, ensuring competitiveness while maximizing profitability. Integrating AI into pricing strategies can provide retail markets in Plateau State with the agility to respond to changing consumer behavior and economic conditions.

Statement of the Problem

Retail markets in Plateau State face challenges in adopting data-driven pricing strategies, leading to inefficiencies and reduced profitability. The lack of AI integration in pricing decisions hinders businesses from achieving competitive pricing advantages.

Aim and Objectives of the Study

  1. To examine the impact of AI applications on product pricing strategies in Plateau State’s retail markets.

  2. To analyze the role of AI in dynamic pricing and demand forecasting.

  3. To recommend AI-driven solutions for improving pricing efficiency in retail markets.

Research Questions

  1. How do AI applications improve product pricing strategies in retail markets?

  2. What is the role of AI in enhancing demand forecasting and competitor analysis?

Research Hypothesis

  1. AI significantly improves the accuracy of product pricing strategies.

  2. The use of AI in pricing decisions enhances market competitiveness.

  3. Dynamic pricing driven by AI leads to increased profitability in retail markets.

Significance of the Study

The study contributes to the understanding of AI’s role in pricing strategies, offering insights for retail businesses in Plateau State and beyond to enhance their profitability and competitiveness.

Scope and Limitation of the Study

The study focuses on retail markets in Plateau State and their adoption of AI in pricing strategies. Limitations include variability in AI adoption and access to proprietary pricing data.

Definition of Terms

  1. Product Pricing Strategies: Approaches used by businesses to set prices for their products.

  2. Dynamic Pricing: A pricing strategy that adjusts prices based on real-time market conditions.

  3. Artificial Intelligence (AI): Technology that enables systems to make data-driven decisions.





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