Book Image

Data Analysis Using SQL and Excel - Second Edition

By : Gordon S. S. Linoff
Book Image

Data Analysis Using SQL and Excel - Second Edition

By: Gordon S. S. Linoff

Overview of this book

Data Analysis Using SQL and Excel, 2nd Edition shows you how to leverage the two most popular tools for data query and analysis—SQL and Excel—to perform sophisticated data analysis without the need for complex and expensive data mining tools. Written by a leading expert on business data mining, this book shows you how to extract useful business information from relational databases. You'll learn the fundamental techniques before moving into the "where" and "why" of each analysis, and then learn how to design and perform these analyses using SQL and Excel. Examples include SQL and Excel code, and the appendix shows how non-standard constructs are implemented in other major databases, including Oracle and IBM DB2/UDB. The companion website includes datasets and Excel spreadsheets, and the book provides hints, warnings, and technical asides to help you every step of the way. Data Analysis Using SQL and Excel, 2nd Edition shows you how to perform a wide range of sophisticated analyses using these simple tools, sparing you the significant expense of proprietary data mining tools like SAS.
Table of Contents (18 chapters)
Free Chapter
1
Foreword
17
EULA

CHAPTER 8
Customer Purchases and Other Repeated Events

 

Subscription-type customer relationships have well-defined starts and stops. This chapter moves from these types of relationships to those defined by multiple events that take place over time, such as purchases and website visits, donations and handset upgrades. Such relationships do not necessarily have a definite end, because any particular event could be the customer’s last, or it could be just another in a long series of events.

Repeated events require correctly assigning the same customer to events that happen at different times and perhaps through different channels. Sometimes we are lucky and customers identify themselves, perhaps by using an account. Identification of individuals can still be challenging. Consider the example of Amazon.com and a family account. The purchase behavior—and resulting recommendations—might combine a teenage daughter’s music preferences with her mother’...