Versata Development Group, Inc.

Neil C Thier

James Singh

Chris Hyams

Thomas Wyatt Wilbur

Thomas H Dillon

Sherrill J Packebush

Timothy Paul Darr

Jeremy S Wacksman

Michael K Grant

Alex Holm Devine

Nirad Sharma

Jacob D Leffler

A recommendation appliance, system and method are provided for generating and deploying additional web page content or functionality (e.g., retail recommendations) to an existing web page server system. For example, the present invention may be embodied as a reverse proxy server that is inserted as an intermediate network node between a web server and the end users accessing the web server. In this position, the recommendation appliance can introduce recommendation messages to web pages generated by the web server without requiring any modification to the code or architecture of the web server. In addition, the appliance may separately track the transaction activities of end users who receive recommendation messages and the transaction activities of end users who do not receive recommendation messages, so that a comparison of the effectiveness of the recommendations may efficiently be demonstrated without requiring any modification to the code or architecture of the web server.

System and method for integrated recommendations

Method for integrated recommendations

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.

System and method for generating effective recommendations

A data processing system normalizes data sets (such as low-resolution transaction data) into high-resolution data sets by mapping generic information into attribute-based specific information that is stored in a database. By establishing a shared domain model for representing items in the recommendation context, catalog and quote history with common terms and concepts, a recommendation engine operating in the shared domain may process the attribute-based representations to make specific and relevant recommendations to the customer. In addition, when certain attribute values are normalized over time, recommendations derived from past order history can be intelligently applied to current orders. The normalized representation of elements in the shared domain may also be used to generate compelling selling point text for each recommendation that is specific to the marketing objectives of the seller and identifies the objectives of the buyer.

Retail recommendation domain model

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Austin, TX, United States of America

Neil C Thier