PASSIVE PARAMETER BASED DEMOGRAPHICS GENERATION

• US 20100070621A1
• Filed: 09/18/2008
• Published: 03/18/2010
• Est. Priority Date: 09/18/2008
• Status: Active Grant

• Current Assignee: John L. Williams, Jonathan M. Urdan
• Original Assignee: John L. Williams, Jonathan M. Urdan
• Inventors: Williams, John L., Urdan, Jonathan M.
• Granted Patent: US 8,549,163 B2
• Time in Patent Office: Days
• US Class Current: 709/224
• CPC Class Codes: G06Q 10/0639 Performance analysis of employees; Performance analysis of enterprise or organisation operations
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: H04L 43/04 Processing captured monitoring data, e.g. for logfile generation

Abstract

A method for characterizing website visitors based on visitor passive parameters and using the characterization to select and/or market website content. The passive visitor parameters include data in the browser agent, time of a website visit, IP address, etc. Such visitor passive parameters are available each time a visitor visits a website. In a first step, a first embodiment of the method anonymously compares the visitor passive parameters with known demographics, for example, at financial websites, to create a statistical mapping between the visitor passive parameters and the demographics. In a second step, the mapping is used to estimate demographics data for future website visitors and then site content provided to the future website visitors is based on the estimated demographics.

Claims

1. A method for selecting website content, the method comprising:

obtaining a multiplicity of anonymous first website visitor passive parameters from a first website for a multiplicity of first website visitors visiting the first website, wherein the anonymous first website visitor passive parameters are commonly available whenever a website is visited;

obtaining corresponding first website visitor active parameters of the first website visitors from the first website, wherein the first website visitor active parameters are correlatable to a value of website content presentable to future website visitors;

generating anonymous statistical mappings between the first website visitor passive parameters of the first website visitors and the corresponding first website visitor active parameters of the first website visitors, wherein the statistical mappings do not rely on any data identifying an individual website visitor;

providing the statistical mappings to at least one of website operators, website publishers, search engine operators and Internet advertisers;

using the statistical mappings to establish an expected value of future website content provided to the future website visitors, based on future website visitor passive parameters of each of the future website visitors; and

providing future website content to the future website visitors based on the expected value of the future website content.

2. The method of claim 1, wherein the first website visitor passive parameters are selected from data in a browser agent, time of day when visiting websites, and IP address for the first website visitors.

3. The method of claim 2, wherein the first website is a financial website and the first website visitor active parameters are demographics parameters.

4. The method of claim 2, wherein the first website is an e-commerce website and the first website visitor active parameters are transaction data.

5. The method of claim 1, wherein generating anonymous statistical mappings comprises using direct mapping including statistical techniques to estimate the likelihood that the website visitor has a specific characteristic to generate the anonymous statistical mappings.

6. The method of claim 1, wherein generating anonymous statistical mappings comprises using direct mapping including regression to estimate the likelihood that the website visitor has a specific characteristic to generate the anonymous statistical mappings.

7. The method of claim 1, wherein generating anonymous statistical mappings comprises using Multi-Factor Mapping to estimate the likelihood that the website visitor has a specific characteristic to generate the anonymous statistical mappings.

8. A method for marketing Internet advertising, the method comprising:

obtaining a multiplicity of anonymous first website visitor passive parameters from a financial website for a multiplicity of financial website visitors visiting the financial website, wherein the anonymous first website visitor passive parameters are commonly available whenever a website is visited;

obtaining corresponding financial website visitor demographics of the financial website visitors, wherein a value of website content presentable to future website visitors is correlatable to the financial website visitor demographics;

anonymously generating statistical mappings between the first website visitor passive parameters and the financial website visitor demographics of the financial website visitors, wherein the statistical mappings do not rely on any data identifying an individual website visitor;

marketing the statistical mappings to at least one of website publishers, Internet advertisers, and second website operators; and

using the statistical mappings to perform at least one of;

identifying future website visitors having demographics desirable to the website publishers and Internet advertisers; and

demonstrating demographics of the second website visitors visiting second websites operated by the second website operators.

9. A method for marketing Internet advertising, the method comprising:

obtaining anonymous first website visitor passive parameters from a e-commerce website for a multiplicity of e-commerce website visitors visiting the e-commerce website, wherein the anonymous first website visitor passive parameters are commonly available whenever a website is visited;

obtaining transaction data from the e-commerce website corresponding to the first website visitor passive parameters for the e-commerce website visitors;

generating statistical mappings from the first website visitor passive parameters to the transaction data, wherein the statistical mappings do not rely on any data identifying an individual website visitor;

marketing the statistical mappings to website publishers and Internet advertisers;

estimating expected values of Internet advertising to future website visitors based on future website visitor passive parameters of the future website visitors and the statistical mappings; and

allocating the Internet advertising to the future website visitors based on the expected values of the advertising.

10. The method for marketing Internet advertising of claim 9, further comprising:

collecting additional transaction data for the Internet advertising directed to the future website visitors; and

generating improved statistical mappings based on the additional transaction data.