The patent badge is an abbreviated version of the USPTO patent document. The patent badge does contain a link to the full patent document.
The patent badge is an abbreviated version of the USPTO patent document. The patent badge covers the following: Patent number, Date patent was issued, Date patent was filed, Title of the patent, Applicant, Inventor, Assignee, Attorney firm, Primary examiner, Assistant examiner, CPCs, and Abstract. The patent badge does contain a link to the full patent document (in Adobe Acrobat format, aka pdf). To download or print any patent click here.
Patent No.:
Date of Patent:
May. 18, 2010
Filed:
Aug. 05, 2004
Nirad Sharma, Austin, TX (US);
Michael K. Grant, Austin, TX (US);
Neil C. Thier, Austin, TX (US);
Alex Devine, Austin, TX (US);
Sherrill J. Packebush, Austin, TX (US);
Thomas H. Dillon, Austin, TX (US);
James Singh, Austin, TX (US);
Jeremy S. Wacksman, Evanston, IL (US);
Chris Hyams, Austin, TX (US);
Timothy P. Darr, Bristow, OK (US);
Nirad Sharma, Austin, TX (US);
Michael K. Grant, Austin, TX (US);
Neil C. Thier, Austin, TX (US);
Alex Devine, Austin, TX (US);
Sherrill J. Packebush, Austin, TX (US);
Thomas H. Dillon, Austin, TX (US);
James Singh, Austin, TX (US);
Jeremy S. Wacksman, Evanston, IL (US);
Chris Hyams, Austin, TX (US);
Timothy P. Darr, Bristow, OK (US);
Versata Development Group, Inc., Austin, TX (US);
Abstract
A data processing system generates recommendations for on-line shopping by scoring recommendations matching the customer's cart contents product page, configuration page, email and/or history using predetermined scoring criteria, such as item availability, item price, relevance of the item to the customer, item clarity, item exposure, total purchase amount in the cart, margin, recommendation confidence and lift, shopper profile matches, seasonality, customer history, time dependency, product marketing emphasis, substitutability, item popularity and/or product attributes associated with the recommended item. The scored recommendations may be ranked and/or filtered to prioritize the recommendations so that the best recommendation is selected for presentation to the customer. In addition, one or more scoring criteria or product attributes for the recommended item may be used to select a specific selling point/message text for inclusion with the selected recommendation.