消費者潛藏購買行為分析-以牛奶消費資料庫為例

Abstract

隨著資料庫行銷的發展，商家業者可以從更多管道蒐集消費者的資訊，也擁有更多的統計分析技術來了解消費者的潛藏購買行為，跳脫原先只能了解基本人口統計資訊的限制，而能從根本的去探查顧客的行為模式，更深入的了解顧客的需求與偏好，進而發展更加準確的行銷策略。 因此本研究以顧客活躍度指標以及陳靜怡（2005）層級貝氏潛藏存貨消耗行為模型，透過國內知名超級市場之顧客資料庫的鮮奶品項購買交易紀錄，分析其中的購買熱量、購買期間、購買頻率以及消耗率等變數，以此來剖析消費者的購買行為，並且將其區隔為漸趨活躍型、穩定消費型以及漸趨靜止型。之後再進一步的去探究、深入了解不同區隔之消費者其購買行為以及特性上的差異性，並且配合購買期間的預測結果，以此為基礎提供進一步相關行銷策略的發展方向。

As the Database marketing developing, not only do firms have much more channels to gather customer information, but it also enable them to understand the latent purchasing behavior of customers by using statistical analysis. Different from traditional methods, firms can explore customer from the deep inside, to find out their needs and preferences, and then to develop more precise marketing strategy. As the result, Customer Activity Index and Latent Inventory Model was employed to analyze the transaction data from a noted supermarket in Taiwan in this research. With the database and the combination of two models, we can understand customer behavior by analyze purchase calories quantity, inter-purchase time, purchase frequency and consuming rate. Besides, we also classified customer into three segmentations, active style, stable style and inactive style. The segmentation is helpful for the research to acquire the insights of each style of customer. And combine with the prediction of inter-purchase time, the firm can develop relative marketing strategy based on the heterogeneity.