In recent years, businesses have found it more and more useful to analyze the transactions they undertake with their customers. In some cases, such an analysis can provide the business with the information it needs to fine tune the transactions to shape customer behavior to improve performance of the business.
For example, an electronic commerce company may want to analyze the “clickstream” of individual customers visiting the company's web page to find associations between customer actions, such as the customer clicking on a particular image on the web page, and desired customer actions, such as the customer making a purchase. With this information, the company may tune its web page to increase the likelihood that a customer will click on the image, with the hoped-for result that sales will increase. A method and apparatus for performing this analysis, called “association” or “affinity analysis,” using a massively parallel processing (MPP) computer system is described in co-pending U.S. patent application Ser. No. 09/410,528, entitled SQL-BASED ANALYTIC ALGORITHM FOR ASSOCIATION, filed on Oct. 1, 1999, and assigned to the same assignee as the present application.
This analytical approach can be useful in analyzing other forms of data, such as retail or financial data. The owners of a grocery store, for example, may find it useful in designing the layout of the store to know that customers are more likely to purchase cheese when they purchase grapes. Similarly, a bank may find it useful to know that customers who contract for certain banking services, such as a checking account, are more likely to acquire other banking services, such as automobile loans. The bank could use such information to design the mailing materials it includes with its statements.
It is sometimes important to isolate the actions of individual customers to properly perform affinity analysis. For example, in the web page context, in which a log is maintained containing customer transactions with the web page, it may be useful to associate transactions with individual customer “sessions” in order to allow a meaningful analysis of the transactions. A method and apparatus for performing such an analysis is described in co-pending U.S. patent application Ser. No. 09/752,355, entitled IDENTIFYING WEB-LOG DATA REPRESENTING A SINGLE USER SESSION, filed on Dec. 29, 2000, and assigned to the same assignee as the present application.
Understanding the order of transactions may also be important. For example, a web page owner may be interested to know that a customer that clicks on a first image on the web page followed by a second image may be more likely to make a purchase than a customer that clicks on the second image before the first image. Making such a determination adds an extra degree of complexity to an affinity analysis.