US 7,680,686 B2 · System and methods for business to business price modeling using price change optimization

Abstract

The present invention relates to business to business market price control and management systems. More particularly, the present invention relates to systems and methods for generating price modeling and optimization modules in a business to business market setting wherein price changes are optimized to achieve desired business results.

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Claims9

Dependent claims

A method for determining an optimal set of price changes in an integrated price management system, said method comprising:

setting an optimization goal, said goal maximizing profit, sales or volume;
defining pricing goals and constraints based on said optimization goal, wherein the constraints may be selected from the group of:
a maximum price increase, maximum price decrease for a business segment, or intersection of business segments;
defining a selected business segment, wherein the selected business segment may be at least one of static and dynamic, and wherein the defining the selected business segment includes accessing a pre-defined segmentation library, selecting one or more appropriate pre-defined business segments from the pre-defined segmentation library, and combining the selected one or more appropriate pre-defined business segments to generate the selected business segment;
defining a selected product combination;
receiving, from a database, sales history data and win/loss classification data for the selected product combination;
generating, by a computer, a price elasticity demand model and a win probability model for the selected product combination using the sales history data and win/loss classification data, wherein the price elasticity demand model and the win probability model are generated using a set of multivariate, parametric, non-separable algorithms;
wherein the price elasticity demand model is generated by:
defining an aggregate elasticity range for said selected business segment;
defining a self elasticity for selected products in said selected product combination;
determining a set of current prices for said product combination;
and
defining a single elasticity for each product in said selected product combination, wherein said single elasticity is defined at said current price;
generating, by a computer, optimized price changes for said selected product combination and business segment using the price elasticity demand model and the win probability model, wherein the optimized price changes meet the defined pricing goals and constraints;
and
outputting the optimized price changes to a deal manager for deal negotiations.

13 more elements

A method for determining an optimal set of price changes in an integrated price management system, said method comprising:

setting an optimization goal, said goal maximizing profit, sales or volume;
defining pricing goals and constraints based on said optimization goal, wherein the constraints may be selected from the group of:
a maximum price increase, maximum price decrease for a business segment, or intersection of business segments;
defining a plurality of selected business segments, wherein the selected business segments may be at least one of static and dynamic, and wherein the defining the selected business segment includes accessing a pre-defined segmentation library, selecting one or more appropriate pre-defined business segments from the pre-defined segmentation library, and combining the selected one or more appropriate pre-defined business segments to generate the selected business segments;
defining a plurality of selected product combinations;
generating multiple simultaneous segmentation from said selected business segments;
receiving, from a database, sales history data and win/loss classification data for the selected product combination;
generating, by a computer, a price elasticity demand model and a win probability model for the selected product combination using the sales history data and win/loss classification data, wherein the price elasticity demand model and the win probability model are generated using a set of multivariate, parametric, non-separable algorithms;
wherein the price elasticity demand model is generated by:
defining an aggregate elasticity range for said selected business segment;
defining a self elasticity for selected products in said selected product combination;
determining a set of current prices for said product combination;
and
defining a single elasticity for each product in said selected product combination, wherein said single elasticity is defined at said current price;
generating, by a computer, optimized price changes for said selected product combination and business segment using the price elasticity demand model and the win probability model, wherein the optimized price changes meet the defined pricing goals and constraints;
and
outputting the optimized price changes to a deal manager for deal negotiations.

14 more elements

Dependencies are inferred from the claim text.

Description3,531 words

Summary1,421 words

#The present invention relates to business to business market price control and management systems. More particularly, the present invention relates to systems and methods for optimizing prices in a business to business market setting wherein an optimal price change is determined according to business strategy and objectives.

#There are major challenges in business to business (hereinafter “B2B”) markets which hinder the effectiveness of classical approaches to price optimization.

#For instance, in B2B markets, a small number of customers represent the lion's share of the business. Managing the prices of these key customers is where most of the pricing opportunity lies. Also, B2B markets are renowned for being data-poor environments. Availability of large sets of accurate and complete historical sales data is scarce.

Brief description of the drawings11 figures

#The present invention is illustrated by way of example, and not by way of limitation, in the figures of the accompanying drawings and in which like reference numerals refer to similar elements and in which:

#FIG. 1 is a simple graphical representation of an integrated price management system in accordance with an embodiment of the present invention.

#FIG. 2 is a process flowchart illustrating a method for performing price change optimization in accordance with an embodiment of the present invention.

Detailed description1,809 words

#The present invention will now be described in detail with reference to selected preferred embodiments thereof as illustrated in the accompanying drawings. In the following description, numerous specific details are set forth in order to provide a thorough understanding of the present invention. It will be apparent, however, to one skilled in the art, that the present invention may be practiced without some or all of these specific details. In other instances, well known process steps and/or structures have not been described in detail in order to not unnecessarily obscure the present invention. The features and advantages of the present invention may be better understood with reference to the drawings and discussions that follow.

#I. Overall System

#To facilitate discussion, FIG. 1 is a high level graphical representation of a business to business price control and management system according to an embodiment of the present invention. A framework for comprehensive price optimization along the operational or product segment level of pricing is presented. The instant price optimization system 100 comprises a sales history database 110, a demand modeling module 120, a optimization module 130, a deal manager module 140, and a learning and calibration module 150. Historical sales data is used by the demand modeling module 120 to model demand for a selected product/segment. The demand modeling module 120 is connected to the optimization module 130. The optimization module 130 uses the demand models provided in generating a set of preferred prices for the selected product/segment. The optimization module 130 is connected to the deal manager module 140, where the preferred prices may be used by a sales force in negotiating deals with customers.

Facts

Application

11/468,013Filed 29 Aug 2006

Published

US 2008/0059280 A16 Mar 2008

Granted

16 Mar 2010

Term ends

29 Apr 2027

Estimated · how

20 years from earliest known nonprovisional domestic filing plus recorded patent term adjustment, including 243 days of adjustment. Maintenance-fee lapses, terminal disclaimers and statutory extensions have not been checked. The continuity chain may be incomplete; this is not an enforceability determination.

Classification5 codes

G06Q 30/02
Commerce: marketing; Price estimation or determination; Fundraising
G06Q 30/0202
Market modelling; Market analysis; Collecting market data: market predictions or forecasting for commercial activities
G06Q 30/0206
Market modelling; Market analysis; Collecting market data: price or cost determination based on market factors
G06Q 30/0283
Marketing; Price estimation or determination; Fundraising: price estimation or determination

Timeline

29 Aug 2006Application filedUS 11/468,013
12 Dec 2006Assigned to Vendavo, Inc.assignment of assignor's interest
6 Mar 2008PublishedUS 2008/0059280 A1
16 Mar 2010GrantedUS 7,680,686 B2
17 Oct 2014Assigned to Golub Capital LLCsecurity interest
14 Sep 2021Assigned to Vendavo, Inc.termination and release of patent security agreement
14 Sep 2021Assigned to Golub Capital Markets LLC, AS Collateral Agentpatent security agreement
12 Oct 2026TodayWithin its term
29 Apr 2027Term endsEstimated, includes 243 days of adjustment

System and methods for business to business price modeling using price change optimization

Life of this patent

System and methods for business to business price modeling using price change optimization

Life of this patent

Life of this patent

Abstract

Drawings

Drawings

Claims9

Description3,531 words

Drawings

Classification5 codes

Life of this patent

Description3,531 words