IP Library Patent Application 11444314
Patent Application
App. No. 11/444,314

Target pricing method

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Quick Facts
Patent No.
US None
App. No.
11/444,314
Abstract

A method and process of target pricing a value, such as a bid, or other price which includes the steps of pricing the value using stored list prices in a product model, costing the value using stored costs in the product model, calculating. an equivalent competitor net price for the value using a competitor net price model, calculating. the probability of winning the value as a function of price using parameters from a market response model, and calculating a target price for the value. The preferred target price maximizes expected contribution using an optimization model that determines competitive response to any potential value, or bid. The method and process further preferably include the steps of calculating one or more benefits of target pricing in comparison to a pre-existing pricing approach, determining a target range for the target price to be within, and determining strategic objects that constrain the target price of the value or bid.

Claims (79)

1 - 34 . (canceled)

35 . A computer-readable medium comprising computer executable instructions for executing a method for determining a target price for an auction item, the method comprising the steps of:

pricing the auction item using list price data in an electronically stored product model;

costing the auction item using cost data in the product model;

determining an equivalent competitor net price for the auction item using an electronically stored competitor net price model;

processing of said auction item pricing, said auction item costing, and said equivalent competitor net price to calculate a plurality of bids as a function of prices using the parameters from an electronically stored market response model that calculates winning probabilities for each of the prices; and

processing of said optimal bids to calculate a target price for the auction item, wherein the processing of said optimal bids comprises accessing an electronically stored optimization model that calculates a separate expected contribution value for each of the bids and selecting an optimal bid associated with a maximum expected contribution, wherein the expected contribution for a selected bid comprises a product of a marginal contribution for the selected bid and the winning probability for the selected bid, wherein the marginal contribution comprises revenues from winning the auction item at the selected bid minus immediately incurred costs from winning the auction item at the selected bid.

36 . The computer-readable medium target price determining method of claim 35 , wherein the market response model calculates the probability of winning auction item at a select price using an expediential distribution comprising price-independent terms reflecting a relative brand preference for the auction item and price-dependent terms reflecting price sensitivity.

37 . The computer-readable medium target price determining method of claim 35 , wherein the method further comprises comprising the step of the calculating a target price range for the auction item.

38 . The computer-readable medium target price determining method of claim 37 wherein the step of processing, of said auction item pricing, said auction item costing, and said equivalent competitor net price to calculate a plurality of bids fiber comprises:

comparing the equivalent competitor net price to the target price range, and

if the an equivalent competitor net price falls outside the target price range, overriding the equivalent competitor net price with a predefined price within said target range prices.

39 . The computer-readable medium target price determining method of claim 35 , wherein the product and competitor price models are n-dimensional with stored data reflective of at least price and cot and wherein the pricing the auction item, the costing the auction item, and the determining an equivalent competitor net price each comprises an iterative linear interpolation of the stored data.

40 . A computer-readable medium comprising computer executable instructions for executing a process of method for target pricing an auction item, the process comprising the steps of:

pricing the auction item using stored list prices in an electronically stored product model;

costing the auction item using stored costs in the product model;

determining an equivalent competitor net price for the auction item using an electronically stored competitor net price model;

processing of said auction item pricing, said auction item costing, and said equivalent competitor net price to calculate a probability of winning the auction item as a function of price using parameters from an electronically stored market response model; and

processing of said probability of wing to calculate a target price for the auction item that maximizes an expected contribution value using an electronically stored optimization model that determines competitive response to any potential price for the auction item, wherein the expected contribution the target price comprises a product of a marginal contribution for the target price and the winning probability for the target price, wherein the marginal contribution the target price comprises revenues from winning the auction item at the target price minus immediately incurred costs from winning the auction item at the target price.

41 . The computer-readable medium target pricing method of claim 40 , wherein the market response model calculates the probability of winning auction item at a select price using an expediential distribution comprising price-independent terms reflecting a relative brand preference for the auction item and price-dependent terms reflecting price sensitivity.

42 . The computer-readable medium target pricing method of claim 41 , wherein the electronically stored market response model includes coefficients for market response predictors based upon historical data, and

wherein the step of processing to calculate the probability of winning includes evaluating price-independent predictors and generating a market response curve reflecting a probability of winning the auction item as a function of a net price.

43 . The computer-readable medium target pricing method of claim 42 , wherein the step of evaluating the price-independent predictors comprises evaluating price independent predictors for at least a customer, a order, and a product.

44 . The computer-readable medium target pricing method of claim 40 , wherein the electronically stored product and competitor price models are n-dimensional with stored data reflective of at least price and cost, and wherein each of the steps of the computer automatically pricing the auction item, costing the auction item, and determining an equivalent competitor net price comprises iterative linear interpolations of the stored data.

45 . The computer-readable medium target pricing method of claim 40 , wherein the step of calculating an equivalent competitor net price further includes the steps of:

retrieving a reference price from a the product model for a specific auction item; and

applying an electronically stored discounting model to the reference price to determine a competitor net price for the specific auction item.

46 . The computer-readable medium target pricing method of claim 40 , wherein the method further comprises comprising the step of the calculating a target price range for the auction item.

47 . The computer-readable medium target pricing method of claim 46 , wherein the step of processing of said auction item pricing, said auction item costing, and said equivalent competitor net price to calculate a plurality of bids further comprises:

comparing the equivalent competitor net price to the target price range, and

if the an equivalent competitor net price falls outside the target price range, overriding the equivalent competitor net price with a predefined price within said target range prices.

48 . The target price determining method of claim 36 , wherein the market response model uses an equation:

probability

of

winning

=

1

1

+

j

J

k

j

+

m

j

wherein, for J competitors, k j is a sum of price-independent terns for competitor j and m j is a sum of price-dependent terms for the competitor j.

49 . The target pricing method of claim 41 , wherein the market response model uses. an equation:

probability

of

winning

=

1

1

+

j

J

k

j

+

m

j

wherein, for J competitors,, k j is a sum of price-independent terms for competitor j and m j is a sum of price-dependent terms for the competitor j.

Assignments (14)
RELEASE OF SECURITY INTEREST IN PATENTS PREVIOUSLY RECORDED AT REEL/FRAME (053383/0117) Recorded Nov 3, 2021
From: U.S. BANK NATIONAL ASSOCIATION, AS COLLATERAL AGENT
To: BLUE YONDER GROUP, INC.
Reel/Frame 058794/0776 →
RELEASE OF SECURITY INTEREST Recorded Sep 16, 2021
From: JPMORGAN CHASE BANK, N.A.
To: BLUE YONDER GROUP, INC.; BLUE YONDER, INC.; JDA SOFTWARE SERVICES, INC.; I2 TECHNOLOGIES INTERNATIONAL SERVICES, LLC; MANUGISTICS SERVICES, INC.; MANUGISTICS HOLDINGS DELAWARE II, INC.; REDPRAIRIE COLLABORATIVE FLOWCASTING GROUP, LLC; JDA SOFTWARE RUSSIA HOLDINGS, INC.; REDPRAIRIE SERVICES CORPORATION; BY BOND FINANCE, INC.; BY NETHERLANDS HOLDING, INC.; BY BENELUX HOLDING, INC.
Reel/Frame 057724/0593 →
SECURITY AGREEMENT Recorded Aug 3, 2020
From: BLUE YONDER GROUP, INC.
To: U.S. BANK NATIONAL ASSOCIATION
Reel/Frame 053383/0117 →
RELEASE OF SECURITY INTEREST IN PATENTS AT REEL/FRAME NO. 29556/0697 Recorded Oct 12, 2016
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: JDA SOFTWARE GROUP, INC.
Reel/Frame 040337/0053 →
RELEASE OF SECURITY INTEREST IN PATENTS AT REEL/FRAME NO. 29556/0809 Recorded Oct 12, 2016
From: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
To: JDA SOFTWARE GROUP, INC.
Reel/Frame 040337/0356 →
SECURITY AGREEMENT Recorded Oct 12, 2016
From: RP CROWN PARENT, LLC; RP CROWN HOLDING LLC; JDA SOFTWARE GROUP, INC.
To: JPMORGAN CHASE BANK, N.A., AS COLLATERAL AGENT
Reel/Frame 040326/0449 →
CHANGE OF NAME Recorded May 24, 2016
From: TALUS SOLUTIONS, INC.
To: MANUGISTICS ATLANTA, INC.
Reel/Frame 038804/0554 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 24, 2016
From: BOYD, DEAN; GUARDINO, THOMAS; PHILLIPS, ROBERT L.
To: TALUS SOLUTIONS
Reel/Frame 038699/0946 →
MERGER Recorded May 24, 2016
From: MANUGISTICS ATLANTA, INC.
To: MANUGISTICS, INC.
Reel/Frame 038800/0876 →
FIRST LIEN PATENT SECURITY AGREEMENT Recorded Jan 2, 2013
From: JDA SOFTWARE GROUP, INC.
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 029556/0697 →
FIRST LIEN PATENT SECURITY AGREEMENT Recorded Jan 2, 2013
From: JDA SOFTWARE GROUP, INC.
To: CREDIT SUISSE AG, CAYMAN ISLANDS BRANCH
Reel/Frame 029556/0809 →
RELEASE OF SECURITY INTEREST IN PATENT COLLATERAL Recorded Dec 21, 2012
From: WELLS FARGO CAPITAL FINANCE, LLC
To: JDA SOFTWARE GROUP, INC.
Reel/Frame 029538/0300 →
PATENT SECURITY AGREEMENT Recorded Apr 4, 2011
From: JDA SOFTWARE GROUP, INC.
To: WELLS FARGO CAPITAL FINANCE, LLC, AS AGENT
Reel/Frame 026073/0392 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Oct 10, 2006
From: MANUGISTICS, INC.
To: JDA SOFTWARE GROUP
Reel/Frame 018367/0074 →