Data mining for individual consumer models and personalized retail promotions

Rayid Ghani, Chad Cumby, Andrew Fano, Marko Krema

Research output: Chapter in Book/Report/Conference proceedingChapter

2 Scopus citations


A major reason that this area has not been more prominent in retail data mining research is that in the past there has been no individual channel to the customer for brick and mortar retailers. Direct mail is coarse grained and not very effective as it requires the attention of customers at times when they are not shopping and may not be actively thinking about what they need. Coupon-based initiatives given at checkout time are seen as irrelevant because they can only be delivered after the point of sale and often discarded by customers right away. However, with the advent of PDAs (personal digital assistants), in-store kiosks, and shopping cart-mounted displays such as the model shown in Figure. 11.1, retailers are in a position now to deliver personalized information to each customer as they navigate through the store.

Original languageEnglish (US)
Title of host publicationData Mining Methods and Applications
PublisherCRC Press
Number of pages24
ISBN (Electronic)9781420013733
ISBN (Print)9780849385223
StatePublished - Jan 1 2007
Externally publishedYes

ASJC Scopus subject areas

  • General Computer Science
  • Economics, Econometrics and Finance(all)
  • General Business, Management and Accounting


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