Applying Data Mining Techniques in Product Recommendations to Support Marketing Strategies- A Case of IC Design Industry
|關鍵字:||資料探勘;推薦模型;分群;關聯規則;IC設計;Data mining;Recommendation Model;Clustering;Association Rule;IC Design Industry|
Facing the industrial era moving ahead rapidly, the competitive environment of business becomes more complex and volatile. The high-tech industries are tending to diversified and customized. Swift changes of customer market spur enterprise to focus on improving time sensitivity. Keeping the traditional marketing thinking, enterprises will encounter a great challenge in the competitive environment. Enterprises could get the strategy to meet market change, if they could provide customized products; otherwise, customers would transfer to competitors and enterprises would gradually lose their competitive edge. In this study, we propose a product recommendation approach by using consumer IC design industry as a case study. The proposed approach is based on the concept of association rule-based recommendation. The EM clustering method is applied to cluster customers into groups of customers with similar characteristics and product needs. Moreover, association rule mining is applied to extract the associations of products for recommendations by analyzing customer transactions. The proposed product recommendation model could support marketing sales to obtain more clear decision strategy by realizing the relationship between products and customers. Consequently, enterprises can improve marketing effectiveness and earn value.
|Appears in Collections:||Thesis|