The Effect of Inter-Visit Time to Inter-purchase Time－An Example of Amazon.com.

本研究嚐試以資料庫行銷技術剖析消費者於網路上的瀏覽與購買行為，將顧客視為獨立且異質性的個體，並運用顧客過去的歷史交易資料分析出個別顧客的特定網路行為模式。研究主旨在於深入探究網路消費者的購買期間（Inter-purchase Time）與其網站造訪期間（Inter-visit Time）之關聯性，進而也定義了另外5項自變數以衡量各項變數與顧客購買期間之關係。 本研究以顧客於網站中的購買期間為依變數，而自變數則分別為：平均造訪期間（Average Inter-visit Time）、網站造訪次數（Visit Time）、網站造訪次數顧客活躍性指標（Customer Activity Index of Visit Time）、網站停留時間顧客活躍性指標（Customer Activity Index of Duration Time）、網站瀏覽頁數顧客活躍性指標（Customer Activity Index of Pages Viewed）以及總交易金額（Basket Total）。再設定人口統計變數資料做為第二層自變數，並運用層級貝式統計分析以探究以下兩個主題：（1）顧客的購買期間會受到哪些網路瀏覽行為影響？以及（2）顧客在購買期間與造訪期間之行為模式是否在不同的人口統計變數上有顯著差異？最後在實證分析上亦透過因素與集群分析以探究具高度相關性之消費者網路瀏覽行為。 本研究運用美國ComScore資料庫擷取2006年與2007年之消費者網路資料，並以顧客於Amazon網站上所被記錄之行為資料為例做分析。然而，本研究或可提供企業與行銷人員一個資料庫行銷之分析架構，但在顧客行為之探索上各個網站未必相同，因此行銷人員可依循本研究之方法以了解消費者之網路行為。This study attempts to analyze the consumer database marketing techniques on the Internet browsing and purchasing behavior, the customer as a separate and individual heterogeneity, and the use of customer data analysis of the past transactions of individual customers of a specific network behavior. Theme is explored in-depth online consumer’s Inter-purchase Time and Inter-visit Time’s relationship, in turn also defined another five variables to measure the variables and customer buying period relations. This study attempts to Inter-purchase Time as dependent variable, while independent variables were: the Average Inter-visit Time), Visit Time, Customer Activity Index of Visit Time, Customer Activity Index of Duration Time, Customer Activity Index of Pages Viewed and the Basket Total. Information on demographic variables and then set as the second independent variable, and the use of hierarchical Bayesian statistical analysis to explore the following two themes: (1) Will customers during the purchase be subject to browsing behavior affected? And (2) whether the customers purchase during the visit period behavior are significant differences in demographic variables? Finally, through empirical analysis and cluster analysis to explore the factors highly associated with Internet browsing behavior of consumers. In this study, ComScore database using the United States in 2006 and 2007 acquisition of consumer Internet information and to customers on the Amazon Web site are recorded by the example of the behavioral data to do analysis. However, this study may provide business and marketing personnel a framework for database marketing analysis, customer behavior in the exploration of various sites may not be the same, so marketers can follow the method of this study was to understand consumer online behavior