An Evaluation of Consumer Behavior Prediction Models in E-Commerce: A Study of Online Marketplaces in Benue State
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- 1-5 Chapters
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- Table of Content: Available
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- NGN 5000
Background of the Study
Consumer behavior prediction models are critical for e-commerce businesses aiming to understand and anticipate customer needs, preferences, and buying patterns. These models leverage data-driven techniques such as machine learning, predictive analytics, and behavioral segmentation to personalize marketing strategies and improve customer retention.
In Benue State, online marketplaces are becoming increasingly popular, driven by digital transformation and changing consumer preferences. However, accurately predicting consumer behavior remains a challenge due to diverse customer demographics and dynamic market trends. Studies by Okeke and Adamu (2024) emphasize the importance of robust prediction models in enhancing customer experience and boosting sales in e-commerce. This study evaluates the effectiveness of consumer behavior prediction models used by online marketplaces in Benue State.
Statement of the Problem
E-commerce businesses in Benue State face challenges in predicting consumer behavior due to the complexity of customer preferences and limited adoption of advanced predictive tools. Inaccurate predictions lead to poor customer targeting, reduced sales, and wasted resources.
Despite the availability of sophisticated prediction models, their adoption remains limited in Benue State due to technical, financial, and operational barriers. Research by Ojo and Musa (2023) highlights the potential of these models in improving customer engagement, yet their impact in the local e-commerce context is under-researched. This study addresses this gap by evaluating consumer behavior prediction models in Benue State.
Objectives of the Study
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To evaluate the effectiveness of consumer behavior prediction models in online marketplaces in Benue State.
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To identify the challenges associated with using these models in e-commerce.
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To propose strategies for improving the adoption and utilization of prediction models in e-commerce.
Research Questions
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How effective are consumer behavior prediction models in online marketplaces in Benue State?
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What challenges hinder the adoption of prediction models in e-commerce businesses?
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What strategies can enhance the use of prediction models in e-commerce?
Research Hypotheses
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Consumer behavior prediction models are not significantly effective in online marketplaces in Benue State.
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Challenges significantly hinder the adoption of these models in e-commerce businesses.
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Proposed strategies do not significantly improve the adoption of prediction models in e-commerce.
Scope and Limitations of the Study
This study focuses on online marketplaces in Benue State, examining the effectiveness of consumer behavior prediction models. Limitations include limited access to proprietary data and variations in model implementation across businesses.
Definitions of Terms
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Consumer Behavior Prediction Models: Analytical tools used to forecast customer preferences and purchasing patterns.
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E-Commerce: The buying and selling of goods and services online.
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Online Marketplaces: Platforms that connect buyers and sellers for the exchange of goods and services.
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