System for on-line merchant price setting

Abstract

A method for setting a price for a product sold online by a subject merchant is provided. The method comprises accessing price information of at least one other merchant of the same product by applying a shopping robot to two or more shopping sites, including at least one price comparison site, with other offerings of the same product by other merchants; accessing pricing rules for the subject merchant that cover sales originating from the comparison site; applying the pricing rules to adjust the current product price at which the subject merchant offers the product on the two or more shopping sites to be more competitive; and responsive to a price adjustment that would reduce the product price so as to violate a specified profitability goal, increasing the shipping charges with which the merchant offers the product with the price adjustment on the two or more shopping sites.

1 - 29 . (canceled) 
     
     
         30 . A computer system-implemented method for optimizing a product offering price for online shoppers comprising:
 for a plurality of on-line shoppers that shop with a subject merchant for a subject product, associating with each such shopper a means of identification;   using a test seller module that offers different prices to different shoppers, recognizing on-line shoppers with an associated means of identification, and offering such recognized shoppers the same price a shopper with the same associated means of identification has previously seen;   from market data of the test seller module, determining at least one price-demand curve for the subject product; and   using such price-demand curve, determining at least one optimized price for the subject merchant and offering it to shoppers.   
     
     
         31 . The method of  claim 30  wherein the step of determining at least one optimized price comprises determining an optimized price for the subject product offered by the subject merchant and for shoppers who are grouped based on an attribute selected from the group consisting of: association with a geographical region, association with a channel, association with a demographic, association with a buying pattern, and combinations of the foregoing. 
     
     
         32 . The method of  claim 30  wherein the step of associating with each such shopper a means of identification comprises:
 providing a tagging module for the subject merchant that identifies a plurality of online shoppers by means of a unique or near unique tag; 
 combining the tag with one or more product catalog IDs (“skus”) to obtain a unique or near-unique identifier for the shopper and the products. 
 
     
     
         33 . The method of  claim 30  wherein the step of associating with each such shopper a means of identification comprises identifying that a shopper is associated with at least one geographic region and the step of determining at least one optimized price comprises determining an optimized price for the at least one geographical region. 
     
     
         34 . The method of  claim 30 , wherein the method further comprises:
 controlling a module for discovering an optimized price for a subject product on a channel, by:   defining a range of prices for the subject product;   randomly selecting prices from a range of prices and, using the test seller, offering them to at least a portion of the shoppers on a channel; and   developing a price-demand curve for such channel for the subject product.   
     
     
         35 . The method of  claim 34  wherein defining a range of prices for the subject product comprises using other merchant's prices for the same product. 
     
     
         36 . The method of  claim 30 , wherein the step of determining at least one price-demand curve for the subject product comprises determining a price-demand curve for the subject product in at least two geographical regions or two channels and, responsive the subject merchant's sales or profitability goals, determining an optimized price for each of the at least two geographical regions or two channels, and offering to online shoppers associated with each of the at least two geographical regions or two channels the optimized price for a shopper's associated geographical region or the channel a shopper is using. 
     
     
         37 . A computer system-implemented method for providing a product offering price to an online shopper comprising:
 providing a tagging module that identifies the online shopper by means of a unique or near unique tag;   combining the tag with one or more product catalog IDs (“skus”) to obtain a unique or near-unique identifier for the shopper and the products; and   upon a return visit of the shopper, responsive to the identifier for the shopper and a product selection by the shopper, finding a shopper associated price for the product selection by the shopper.   
     
     
         38 . The method of  claim 37 , wherein the method presents a price to the shopper based on the shopper being grouped by an attribute selected from the group consisting of: association with a geographical region, association with a channel, association with a demographic, association with a buying pattern, and combinations of the foregoing. 
     
     
         39 . The method of  claim 37 , further comprising:
 determining a price-demand curve for a subject product in at least two geographical regions or two channels and, responsive to a subject merchant's sales or profitability goals, determining an optimized price for each of the at least two geographical regions or two channels; and   offering to online shoppers associated with each of the at least two geographical regions or two channels the optimized price for a shopper's associated geographical region or the channel a shopper is using.   
     
     
         40 . The method of  claim 37 , further comprising:
 discovering an optimized price for a product on a channel, comprising:
 defining a range of prices for the product; 
 randomly selecting prices from the range of prices and offering them to shoppers on the channel; 
 tagging the shoppers to whom a selected price offer is made so that a particular shopper who revisits the channel receives the same price offer the shopper received before; 
 developing a price-demand curve using market data from the selected price offers; and 
 adjusting the price of the product using the developed price-demand curve. 
   
     
     
         41 . The method of  claim 40  wherein defining a range of prices for the product includes using other merchant's prices for the same product. 
     
     
         42 . A computer-implemented system for optimizing a product offering price for online shoppers comprising:
 a module for associating a means of identification with each of a plurality of on-line shoppers that shop with a subject merchant for a subject product;   a test seller module that offers different prices to different shoppers, by recognizing on-line shoppers with an associated means of identification, and offering such recognized shoppers the same price a shopper with the same associated means of identification has previously seen; and   a price analyzer module for determining from market data of the test seller module at least one price-demand curve for the subject product and, using such price-demand curve, determining at least one optimized price for the subject merchant and offering it to shoppers.   
     
     
         43 . The system of  claim 42  wherein the price analyzer module determines an optimized price for the subject product offered by the subject merchant and for shoppers who are grouped based on an attribute selected from the group consisting of: association with a geographical region, association with a channel, association with a demographic, association with a buying pattern, and combinations of the foregoing. 
     
     
         44 . The system of  claim 42  wherein the module for associating a means of identification with each of a plurality of on-line shoppers comprises:
 a tagging module for the subject merchant that identifies a plurality of on-line shoppers by means of a unique or near unique tag and combines the tag with one or more product catalog IDs (“skus”) to obtain a unique or near-unique identifier for the shopper and the products. 
 
     
     
         45 . The system of  claim 42  wherein the module for associating a means of identification with each of a plurality of on-line shoppers comprises a module identifying that a shopper is associated with at least one geographic region and the price analyzer determines at least one optimized price for the at least one geographical region. 
     
     
         46 . The system of  claim 42 , wherein the system further comprises:
 a module for discovering an optimized price for a subject product on a channel, by executing instructions:   defining a range of prices for the subject product;   randomly selecting prices from a range of prices and, using the test seller, offering them to at least a portion of the shoppers on a channel; and   developing a price-demand curve for such channel for the subject product.   
     
     
         47 . The system of  claim 46  wherein module executing instructions defining a range of prices for the subject product comprises using other merchant's prices for the same product. 
     
     
         48 . The system of  claim 42 , wherein the price analyzer module determines at least one price-demand curve for the subject product by determining a price-demand curve for the subject product in at least two geographical regions or two channels and, responsive the subject merchant's sales or profitability goals, determines an optimized price for each of the at least two geographical regions or two channels, and offers to online shoppers associated with each of the at least two geographical regions or two channels the optimized price for a shopper's associated geographical region or the channel a shopper is using. 
     
     
         49 . A computer-implemented system for providing a product offering price to an online shopper comprising:
 a tagging module that identifies the online shopper by means of a unique or near unique tag and combines the tag with one or more product catalog IDs (“skus”) to obtain a unique or near-unique identifier for association with the shopper and the products; and   a price analyzer module, responsive to the identifier for the shopper and a product selection by the shopper, for finding upon a return visit of the shopper a shopper associated price for the product selection by the shopper.   
     
     
         50 . The system of  claim 49 , wherein the price analyzer module presents a price to the shopper based on the shopper being grouped by an attribute selected from the group consisting of: association with a geographical region, association with a channel, association with a demographic, association with a buying pattern, and combinations of the foregoing. 
     
     
         51 . The system of  claim 49 , the price analyzer module has executable instructions for:
 determining a price-demand curve for a subject product in at least two geographical regions and, responsive to a subject merchant's sales or profitability goals, determining an optimized price for each of the at least two geographical regions; and   offering to online shoppers associated with each of the at least two geographical regions the optimized price for the shopper's associated geographical region.   
     
     
         52 . The system of  claim 49 , a module for discovering an optimized price for a product on a channel, by executing instructions comprising:
 defining a range of prices for the product;   randomly selecting prices from the range of prices and offering them to shoppers on the channel;   tagging the shoppers to whom a selected price offer is made so that a particular shopper who revisits the channel receives the same price offer the shopper received before;   developing a price-demand curve using market data from the selected price offers; and   adjusting the price of the product using the developed demand curve.   
     
     
         53 . The system of  claim 52  wherein module for discovering an optimized price comprises instructions defining a range of prices for the product that includes other merchant's prices for the same product.