Post-COVID-19 Online Shopping Behavior Analysis of Thai Consumers: Using FP-Growth
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This research analyzes customer purchasing patterns on a Thai e-commerce platform using association rule mining. The study employed the FP-Growth algorithm on a dataset of 39,149 transactions from January to August 2023, with a minimum confidence level of 0.7. The analysis yielded 16 significant association rules, revealing complex cross-category purchasing behaviors. Key findings include a 68.6% likelihood of supplement purchases when sports and gift items are bought together, and a 72.9% chance of cosmetics purchases when supplements, appliances, and books are combined. These insights offer valuable guidance for targeted marketing strategies and sales promotion planning in Thailand’s online retail sector. The study contributes to the understanding of e-commerce behavior in the Thai market, with implications for personalized recommendations, user interface optimization, and inventory management.
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