消費者潛藏購買行為分析─以米消費資料庫為例

Abstract

台灣的超級市場業競爭激烈，不僅要面對同業競爭者的龐大壓力，更是要面對雜貨店、便利商店、量販店、百貨公司甚至是網路購物等多方競爭壓力，因此如何脫穎而出並鞏固市場地位，便需要仰賴消費者的購買資料庫分析與顧客關係管理，現今電腦設備的發展，強大的資訊處理與計算能力加強了行銷人員洞悉消費者的能力，傳統的產品導向的經營方式已無法滿足消費者的需求，透過資料庫的分析，了解顧客的購買需求與下次可能再購時點，能幫助超市業者管理消費者與庫存之能力。 本研究使用台灣一知名連鎖超級市場之資料庫，取其2009至2010之會員交易紀錄，並針對「米」該項商品進行購買期間與購買量之分析，計算出個別顧客對該項產品的購買量之活躍性趨勢，購買期間之預測能幫助業者判斷行銷手段之執行時點，而購買量之分析能提供業者決定庫存與進貨量之依據，並利用陳靜怡(2005)建置之層級貝氏潛藏行為模型整合購買量與購買期間，同時利用傳統統計之最小平方法做出估計，將兩者之結果做出比較，再統整結果以供行銷人員做為訂定行銷計劃之參考，最後列出本研究進行時所遭遇的限制，與未來的研究方向

Considering the varieties of shopping channels like grocery stores, convenient stores, discount stores, and department stores, supermarkets in Taiwan are facing more competitions than just its competitors in the same industry. Therefore, how to stand out from the competitors and consolidate its market share are the most important goals for supermarket practitioners. The development of computing equipment and the powerful capability of calculating and data processing make marketing practitioners know their customers better. Traditional product-oriented sales strategies will not win the customers’ trust or satisfy their needs anymore. Using the database analysis, knowing customers' purchasing needs and when they might re-purchase can help supermarket companies managing their customers and controlling their inventory. This study tries to understand the purchasing behavior of the supermarket members one of the famous chain supermarkets in Taiwan. Using the members' purchasing records between 2009 and 2010, we can analyze purchasing time and quantity of the product 'rice' . We still can calculate customer's activity index. The forecast of inter-purchase time helps supermarket practitioners deciding the time to exercise the marketing strategies. Prediction of purchase quantity is helpful for supermarket practitioners to control their inventory and purchase volume. Latent hierarchical Bayes model developed by Chen (2005) was employed to integrate the purchase quantity and inter-purchase time to generate inventory consumption estimators. and we can compare it to that of traditional OLS method to offer a reference in scheduling marketing activities.