System and method for increasing the accuracy of forecasted consumer interest in products and services

• US 20040064357A1
• Filed: 09/26/2002
• Published: 04/01/2004
• Est. Priority Date: 09/26/2002
• Status: Abandoned Application

• Current Assignee: Jeffrey D. Hunter, Sharon M. Hoeting
• Original Assignee: Jeffrey D. Hunter, Sharon M. Hoeting
• Inventors: Hunter, Jeffrey D., Hoeting, Sharon M.
• Application Number:
  US10/255,547
• Publication Number:
  US 20040064357A1
• 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: G06Q 30/0203 Market surveys; Market polls

Abstract

For new and experimental products for which no actual purchasing behavior is measurable, consumer behavior forecasting data is collected and then corrected based on a comparison of forecasted versus actual measured behavioral data for existing, “similar” products. The illustrative embodiment selects products or services that are (a) “similar” (based on various objective and subjective criteria) to the new product or service, and (b) are at a stage where actual consumer behavior can be measured. A computer then analyzes predicted consumer behavior forecasts for this “similar” product(s) or service(s) versus actual measured consumer behavior to determine a correction factor. This correction factor is then applied to correct predicted consumer behavior forecasts for a new product or service for which no actual consumer behavior can yet be measured. The resulting corrected forecasts more accurately reflect likely actual consumer behavior by taking into account errors inherent in the potential consumer survey process.

Claims

1. A method for modifying or correcting data collected from consumer panels or other test participants to provide for a more accurate forecasting tool for product or concept launches, comprising:

collecting first data forecasting purchasing behavior for a particular product and/or demographic;

collecting second data showing actual purchasing habits for similar products/demographics;

determining a ratio between said first and second data; and

using said ratio to adjust the forecast provided by the first data to generate a corrected representation of forecasted purchasing behavior.

2. A method for modifying or correcting data as recited in claim 1, wherein the product or concept launches are food products.

3. A system for accurately predicting consumer demand for a product or service comprising:

a data collection arrangement that collects data indicating whether consumers are likely to exhibit predetermined behavior with respect to products or services;

a consumer behavior measuring arrangement that measures actual consumer behavior; and

a calculation arrangement that compares predicted likely consumer behavior with actual measured consumer behavior to generate a correction factor for application to predicted consumer behavioral data with respect to which no actual consumer behavior can yet be measured.

4. The system of claim 3 wherein said data collection arrangement includes a web server.

5. The system of claim 3 wherein said data collection arrangement includes a telephonic interviewing subsystem.

6. The system of claim 3 wherein said data collection arrangement includes a document scanner.

7. The system of claim 3 wherein said consumer behavior measuring arrangement includes a point of sale purchase data acquisition system.

8. The system of claim 3 wherein said calculation arrangement calculates an average of claimed and actual consumer behavior for a plurality of products, generates a ratio based on said averages, and applies said ratio to correct predicted consumer behavioral data.

9. The system of claim 3 wherein said calculation arrangement provides for removal of anomalous data.

10. The system of claim 3 wherein said system is used to accurately predict consumer demand for food products.

11. A method of predicting consumer behavior comprising:

(a) collecting data forecasting consumer purchasing behavior for a plurality of consumer offerings;

(b) measuring actual consumer purchasing behavior for said plurality of consumer offerings;

(c) calculating the divergence between said forecasting data and said actual behavioral data;

(d) collecting data forecasting consumer behavior with respect to an offering for which no or inadequate measurement of actual consumer behavior is available; and

(e) correcting said collected data referred to in said last-mentioned step based on said calculated divergence.

12. A method of predicting consumer behavior as recited in claim 11, wherein said consumer offerings are food products.

13. A method of predicting consumer behavior comprising:

(1) selecting products or services that are (a) “

similar”

to a new product or service, and (b) are at a stage where actual consumer behavior can be measured;

(2) using a computer to analyze predicted consumer behavior forecasts for this “

similar”

product(s) or service(s) versus actual measured consumer behavior to determine a correction factor; and

(3) applying said correction factor to correct predicted consumer behavior forecasts for a new product or service for which no actual consumer behavior can yet be measured.

14. A method of predicting consumer behavior as recited in claim 13, wherein said new product or service is a food offering.