Response attribution valuation

• US 8,676,647 B2
• Filed: 07/26/2012
• Issued: 03/18/2014
• Est. Priority Date: 06/14/2010
• Status: Active Grant

• Current Assignee: HCL Technologies Limited
• Original Assignee: International Business Machines Corporation
• Inventors: Crites, Robert, Kennedy, Ruby
• Primary Examiner(s): Weiss, John G
• Assistant Examiner(s): PATEL, DIPEN M
• Application Number:
  US13/559,140
• Publication Number:
  US 20120290385A1
• Time in Patent Office: 600 Days
• Field of Search: 705/14.52, 705/14.45
• US Class Current: 705/14.52
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0246 Traffic

Abstract

A computer-implemented method is described for determining a response attribution value that represents a credit assignment to a communication, for an associated response received from a recipient during a marketing campaign.

Claims

1. A computer-implemented method for determining a response attribution value that represents a credit assignment to a communication, for an associated response received from a recipient during a marketing campaign, the method comprising:

retrieving by one or more computer systems a value for a response rate parameter associated with the communication and a power law parameter that corresponds to a time delay distribution associated with receiving a response from the recipient;

generating by the one or more computer systems a response attribution value according to the retrieved value for the response rate parameter and the retrieved value for the power law parameter;

calculating by the one or more computer systems a subsequent value for the response rate parameter; and

calculating by the one or more computer systems a subsequent value for the power law parameter by applying the generated response attribution value and the time delay distribution to a weighted regression model.

2. The method of claim 1 further comprising:

retrieving by the one or more computer systems the subsequent values for the response rate parameter and the power law parameter; and

generating by the one or more computer systems a subsequent response attribution value according to the retrieved subsequent value for the response rate parameter and the retrieved subsequent value for the power law parameter.

3. The method of claim 2 further comprising:

iteratively, retrieving the subsequent values for the response rate parameter and the power law parameter and generating the subsequent response attribution value according to the retrieved subsequent value of the response rate parameter and the retrieved subsequent value of the power law parameter value.

4. The method of claim 1, further comprising:

terminating generation of the response attribution value when the calculated values of the response rate and power law parameters converge.

5. The method of claim 1, further comprising:

terminating generation of the response attribution value when a threshold number of iterations of generating have occurred.

6. The method of claim 1, further comprising:

terminating generation of the response attribution value when a threshold amount of computing resources have been expended.

7. The method of claim 1 wherein the retrieved values for the response rate and power law parameters are arbitrarily provided values.

8. The method of claim 1 further comprising:

outputting from the one or more computers an identifier corresponding to the communication and associated response, and the determined response attribution value.

9. The method of claim 1 wherein the regression model is a linear weighted regression model.