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Improving the Decision-Making Mechanism When Forming a Product Range

Authors

Abdukhalilova Laylo Tokhtasinovna

Rubric:Marketing
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The formation of a product range is a critical business function that significantly influences competitiveness in dynamic markets. This study evaluates decision-making mechanisms, emphasizing data-driven strategies, market analysis, and structured frameworks. Utilizing a mixed-methods approach, the research identifies key challenges such as reliance on outdated methods and intuition. Decision-tree models and SWOT analysis were employed to propose a three-step decision-making framework incorporating market analysis, scenario planning, and feedback integration. The findings highlight improvements in product alignment, overstocking reduction, and customer satisfaction when data-driven methodologies are adopted. The study provides actionable insights for optimizing product decisions in volatile markets.

Keywords

Product range
decision-making
data-driven analysis
market dynamics
SWOT analysis
scenario planning
consumer behavior
product alignment.

Authors

Abdukhalilova Laylo Tokhtasinovna

References:

1.    Kotler, P., & Keller, K. L. (2020). Marketing Management. Pearson Education.
2.    Smith, J. (2019). Data-Driven Decision Making in Retail. Journal of Business Analytics, 45(3), 112-129.
3.    Brown, T., & Johnson, R. (2018). Advances in Consumer Behavior Analysis. Cambridge University Press.
4.    Chen, Y., & Lu, Y. (2021). Leveraging Big Data for Strategic Product Decisions. International Journal of Market Research, 63(4), 523-541.
5.    Davis, S., & Goliath, R. (2022). Real-Time Analytics in Product Management. Harvard Business Review, 100(5), 45-52.
6.    Wang, X., & Zhang, H. (2020). Machine Learning Applications in Retail Product Selection. Journal of Retail Analytics, 58(2), 78-94.
7.    Johnson, P., & Clark, K. (2019). Consumer Trends and Their Impact on Product Range Optimization. European Journal of Marketing Studies, 54(6), 345-362.
 

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