# US 2010/0169239 A1 · Method for products re-pricing

> Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt

- Number: US 2010/0169239 A1
- Document ID: US20100169239A1
- Status: Published application
- Kind: A1
- Application number: 12/347,448
- Filed: 2008-12-31
- Published: 2010-07-01
- Earliest claimed: 2008-12-31
- Assignees: Lead Digi Corp.
- Inventors: Kuo-Hsiung Weng; Henry Chang
- Web page: https://patentgrep.com/patent/US20100169239A1

## CPC

- G06Q 30/02: Marketing; Price estimation or determination; Fundraising
- G06Q 30/0283: Price estimation or determination
- G06Q: INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR

## Abstract

How to determine the price of a product, which includes any goods or services, is always a challenge task. One of the reasons is the difficulty of finding the prices of competitive products. Thus, most companies simply calculate the price by adding a markup to the cost. The markup is determined by experience, which could be inaccurate, or after an extensively manual survey of the prices of competitive products, which is time-consuming. The present invention allows sellers to automatically determine the price of a product by comparing the competitive products searched from the Internet.

## Claims

### Claim 1

A method for products re-pricing comprising steps:
searching all the competing sellers;
applying static rules to exclude unqualified competing sellers;
applying dynamic rules to select the most competitive product by finding the price of the most competitive product by using the model of representing a product's parameters as the coordinates of a point in a multi-dimensional space, each parameter corresponds to one coordinate of a point;
determining the upper limit of your product's price;
determining the lower limit of your price;
determining the markdown price of the price of the most competitive product;
compute the price of your product.

### Claim 2 (depends on 1)

The method of claim 1, wherein finding the price of the most competitive product by assigning different weights to different parameters of a product.

### Claim 3 (depends on 1)

The method of claim 1, wherein finding the price of the most competitive product by inversing different parameters of a product.

### Claim 4 (depends on 2)

The method of claim 2, wherein finding the price of the most competitive product by inversing different parameters of a product.

### Claim 5 (depends on 1)

The method of claim 1, wherein the distance between points in a multi-dimensional space uses the Euclidean distance to determine which competing product is the most competitive one.

### Claim 6 (depends on 1)

The method of claim 1, wherein the distance between points in a multi-dimensional space uses the Minkowski distance to determine the most competitive product.

### Claim 7 (depends on 1)

The method of claim 1, wherein the distance between points in a multi-dimensional space uses the Mahalanobis distance to determine the most competitive product.

### Claim 8 (depends on 1)

The method of claim 1, wherein the distance between points in a multi-dimensional space uses the Lee distance to determine the most competitive product.

### Claim 9 (depends on 1)

The method of claim 1, wherein the distance between points in a multi-dimensional space uses the Chebyshev distance to determine the most competitive product.

### Claim 10 (depends on 1)

The method of claim 1, wherein the distance between points in a multi-dimensional space uses the Manhattan distance to determine the most competitive product.

### Claim 11 (depends on 3)

The method of claim 3, wherein by inversing one or more parameters of a product, the product that is the closest to the origin on a multi-dimensional space marks the most competitive product.

### Claim 12 (depends on 3)

The method of claim 3, wherein by inversing one or more parameters of a product, the product that is further away from the origin on a multi-dimensional space marks the most competitive product.

### Claim 13 (depends on 4)

The method of claim 4, wherein by inversing and weighting one or more parameters of a product, the product that is the closest to the origin on a multi-dimensional space marks the most competitive product.

### Claim 14 (depends on 4)

The method of claim 4, wherein by inversing and weighting one or more parameters of a product, the product that is further away from the origin on a multi-dimensional space marks the most competitive product.