System and method of message selection and target audience optimization

• US 20040153360A1
• Filed: 09/26/2003
• Published: 08/05/2004
• Est. Priority Date: 03/28/2002
• Status: Abandoned Application

• Current Assignee: Douglas F. Schumann
• Original Assignee: Douglas F. Schumann
• Inventors: Schumann, Douglas F.
• Application Number:
  US10/473,377
• Publication Number:
  US 20040153360A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: H04H 20/28 Arrangements for simultaneous broadcast of plural pieces of information
• CPC Class Codes: H04H 2201/70 characterised in that receivers can be addressed
• CPC Class Codes: H04H 60/63 for services of sales data processing systems or methods specially adapted for electronic commerce G06Q30/00
• CPC Class Codes: H04H 60/66 for using the result on distributors' side
• CPC Class Codes: H04H 60/82 the transmission system being the Internet
• CPC Class Codes: H04N 21/25891 being end-user preferences retrieval of video data in a video database based on user preferences G06F16/739; arrangements for recognizing users' preferences H04H60/46; user profiles in network data switching protocols H04L67/306; processing of user preferences or user profiles in wireless networks H04W8/18
• CPC Class Codes: H04N 21/2668 Creating a channel for a dedicated end-user group, e.g. insertion of targeted commercials based on end-user profiles information retrieval from the Internet by querying with filtering and personalisation G06F16/9535; arrangements for replacing or switching information during the broadcast H04H20/10; push services over packet-switching network H04L12/1859; adaptation of message content in packet-switching networks H04L51/063
• CPC Class Codes: H04N 21/44222 Analytics of user selections, e.g. selection of programs or purchase activity monitoring of user selections in data processing systems G06F11/34; arrangements for monitoring the user's behaviour or opinions in broadcast systems H04H60/33
• CPC Class Codes: H04N 21/6582 Data stored in the client, e.g. viewing habits, hardware capabilities, credit card number arrangements where receivers interact with the broadcast H04H20/38
• CPC Class Codes: H04N 7/17318 Direct or substantially direct transmission and handling of requests

Abstract

A method and system that uses electronic message delivery combined with data collection techniques and data-mining methods to determine and enhance the effectiveness of a given communication and to optimize the target audience of the given communication. One embodiment of the system utilized in practicing the method also includes a means for collecting real-time, synchronized survey audience response data with respect to the videos presented and a data-mining tool for analyzing the data collected and the streaming videos presented. One embodiment of the system includes an audience manager (12), and invitation manager (14), and order manager (16), and a message manager (18). In one embodiment, the message manager (18) includes a testing process (20), a scoring process (22), a ranking process (24), and a response analysis process (26).

Claims

1. A method for selecting an optimal target audience, said method comprising the steps of

selecting a reference audience pool;

selecting a survey audience from said reference audience pool;

presenting information to said survey audience;

collecting survey audience response data with respect to said information;

training a data-mining tool with said response data collected;

scoring said audience pool using said trained tool;

selecting said target audience from said audience pool based on said scores; and

presenting said information to said target audience.

2. A method for optimizing a target audience, comprising the steps of:

selecting a reference audience pool;

selecting a survey audience from said reference audience pool;

presenting a video to said survey audience;

collecting real-time, synchronized survey audience response data with respect to said video;

training a data-mining tool with said data collected;

scoring said audience pool using said trained tool;

selecting said target audience based on said scores; and

presenting said video to said target audience.

3. A method for optimizing a target audience, comprising the steps of:

selecting a reference audience pool;

selecting a survey audience from said reference audience pool;

presenting a streaming video to said survey audience using electronic means;

collecting real-time, synchronized survey audience response data with respect to said video;

training a data-mining tool with said data collected;

scoring said audience pool using said trained tool;

selecting said target audience based on said scores; and

presenting said streaming video to said target audience using electronic means.

4. A method for optimizing at least one target audience, comprising the steps of:

selecting at least one reference audience pool;

selecting at least one survey audience from said at least one reference audience pool;

presenting at least one streaming video to said at least one survey audience using electronic means;

collecting real-time, synchronized survey audience response data with respect to said at least one video;

training a data-mining tool with said data collected;

scoring said at least one audience pool using said trained tool;

selecting said at least one target audience based on said scores; and

presenting said at least one streaming video to said at least one target audience using electronic means.

5. The method for optimizing at least one target audience in claim 4, further comprising the step of selecting said at least one streaming video based on said scores, wherein said at least one streaming video selected is presented to said at least one target audience using electronic means.

6. A method for video communication testing and optimization for at least one target audience, comprising the steps of:

selecting at least one reference audience pool;

selecting at least one survey audience from said at least one reference audience pool;

presenting at least one streaming video to said at least one survey audience using electronic means;

collecting real-time, synchronized survey audience response data with respect to said at least one video;

training a data-mining tool with said data collected;

scoring said at least one audience pool using said trained tool;

selecting said at least one target audience based on said scores;

selecting said at least one streaming video based on said scores; and

presenting said at least one streaming video selected to said at least one target audience using electronic means.

7. A method for video communication testing, comprising the steps of:

selecting at least one reference audience pool;

selecting at least one survey audience from said at least one reference audience pool;

presenting at least one streaming video to said at least one survey audience using electronic means;

collecting real-time, synchronized survey audience response data with respect to said at least one streaming video;

training a data-mining tool with said data collected;

scoring said at least one audience pool using said trained tool; and

selecting said at least one streaming video based on said scores.

8. A system for video communication testing and optimization of at least one target audience, the system comprising:

a means for presenting at least one streaming video to said at least one target audience, wherein said at least one target audience is selected from at least one reference audience pool;

a means for collecting real-time, synchronized survey audience response data with respect to said at least one video; and

a data-mining tool for analyzing said data collected and said at least one streaming videos presented.

9. A message management system to test and optimize a message for a test audience, the system comprising

an audience manager;

an invitation manager;

an order manager; and

a message manager.

10. The message management system of claim 9, wherein said message manager further comprises

a testing processor;

a scoring processor;

a ranking processor; and

a response analysis processor.