Systems and methods for forecasting book demand

• US 20060149616A1
• Filed: 01/05/2005
• Published: 07/06/2006
• Est. Priority Date: 01/05/2005
• Status: Abandoned Application

• Current Assignee: Peter G. Hildick-Smith
• Original Assignee: Peter G. Hildick-Smith
• Inventors: Hildick-Smith, Peter G.
• Application Number:
  US11/030,725
• Publication Number:
  US 20060149616A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06315 Needs-based resource requirements planning or analysis
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0203 Market surveys; Market polls
• CPC Class Codes: G06Q 30/0204 Market segmentation

Abstract

Systems and methods for forecasting demand for a test book. One method according to the present invention includes dividing books into a plurality of categories with each of the categories having a unifying concept, developing a demand forecast model for each category by selecting a plurality of variables and, for each category, assigning each selected variable a value based upon historical data showing the importance of each selected variable in predicting demand for books in the category. The test book is assigned to one of the plurality of categories based upon a similarity between the test book and the unifying concept of the assigned category. A target audience is provided with the test book and the audience is surveyed to capture data that can be used to calculate a forecasted value for each selected variable in the assigned category. The forecasted value is then used for each selected variable in the demand forecast model for the assigned category to forecast a demand for the test book. Another method according to the invention includes providing and surveying the target audience with all or part of the full text of the test book.

Claims

1. :

A method for forecasting demand for a test book comprising;

(a) dividing books into a plurality of categories with each of the categories having a unifying concept;

(b) developing a demand forecast model for each category by selecting a plurality of variables and, for each category, assigning to each selected variable a value based upon historical data showing the importance of each selected variable in predicting demand for books in that category;

(c) assigning the test book to one of the categories based upon a similarity between the test book and the unifying concept of the assigned category;

(d) providing a target audience with the test book and surveying the audience to capture data that can be used to calculate a forecasted value for each selected variable in the assigned category; and

(e) using the forecasted value for each selected variable in the demand forecast model for the assigned category to forecast a demand for the test book.

2. :

The method as claimed in claim 1, wherein the variables are selected from the group consisting of a prospective consumer'"'"'s purchase intent, author perception, recommendation level, distribution, merchandising support, promotional and publicity support, key audience, awareness, demand, and availability.

3. :

The method as claimed in claim 1, further comprising;

(a) gathering sales data for a published book for which demand had been forecast according to the demand forecast model in the assigned category, and

(b) comparing the demand forecast of the published book with the demand forecast of the test book.

4. :

The method as claimed in claim 3, further comprising calibrating the demand forecast model for each selected variable in the assigned category based on the gathered sales data of the published book.

5. :

The method as claimed in claim 1, wherein the step of assigning the test book to a book category comprises designing and fielding a survey.

6. :

The method as claimed in claim 1, wherein the surveying is conducted over the Internet.

7. :

The method as claimed in claim 1, wherein the surveying is conducted using survey software.

8. :

The method as claimed in claim 1, further comprising providing the target audience with all or part of the full text of the test book and surveying the target audience.

9. :

The method as claimed in claim 1, wherein the variables comprise business input measures, and the method further comprises collecting business input measures and inputting the business input measures into the demand forecast model for the assigned category.

10. :

The method as claimed in claim 9, wherein the business input measures are selected from the group consisting of sales distribution level and channel plans, publicity event type and size, marketing and merchandising spending plans and the related level and incremental sales impact of store merchandising support.

11. :

The method as claimed in claim 1, wherein the demand forecast of the test book is expressed in terms of unit sales.

12. :

The method as claimed in claim 1, wherein the demand forecast of the test book is expressed in terms of dollar sales.

13. :

The method as claimed in claim 1, further comprising utilizing the forecasted demand for the test book to make a demand-based publishing decision.

14. :

The method as claimed in claim 1, further comprising utilizing the forecasted demand for the test book to make a demand-based retailing decision.

15. :

A system for forecasting demand for a test book comprising;

(a) means for dividing books into a plurality of categories with each of the categories having a unifying concept;

(b) means for developing a demand forecast model for each category by selecting a plurality of variables and, for each category, assigning to each selected variable a value based upon historical data showing the importance of each selected variable in predicting demand for books in that category;

(c) means for assigning the test book to one of the categories based upon a similarity between the test book and the unifying concept of the assigned category;

(d) means for providing a target audience with the test book and surveying the audience to capture data that can be used to calculate a forecasted value for each selected variable in the assigned category; and

(e) means for using the forecasted value for each selected variable in the demand forecast model for the assigned category to forecast a demand for the test book.

16. :

The system as claimed in claim 15, wherein the variables are selected from the group consisting of a prospective consumer'"'"'s purchase intent, author perception, recommendation level, distribution, merchandising support, promotional and publicity support, key audience, awareness, demand, and availability.

17. :

The system as claimed in claim 15, further comprising;

(a) means for gathering sales data for a published book for which demand had been forecast according to the demand forecast model in the assigned category, and

(b) means for comparing the demand forecast of the published book with the demand forecast of the test book.

18. :

The system as claimed in claim 17, further comprising means for calibrating the demand forecast model for each selected variable in the assigned category based on the gathered sales data of the published book.

19. :

The system as claimed in claim 15, wherein the means for assigning the test book to a book category comprises means for designing and fielding a survey.

20. :

The system as claimed in claim 15, wherein the surveying is conducted over the Internet.

21. :

The system as claimed in claim 15, wherein the surveying is conducted using survey software.

22. :

The system as claimed in claim 15, further comprising means for providing the target audience with all or part of the full text of the test book and surveying the target audience.

23. :

The system as claimed in claim 15, wherein the variables comprise business input measures, and the system further comprises means for collecting business input measures and means for inputting the business input measures into the demand forecast model for the assigned category.

24. :

The system as claimed in claim 23, wherein the business input measures are selected from the group consisting of sales distribution level and channel plans, publicity event type and size, marketing and merchandising spending plans and the related level and incremental sales impact of store merchandising support.

25. :

The system as claimed in claim 15, wherein the demand forecast of the test book is expressed in terms of unit sales.

26. :

The system as claimed in claim 15, wherein the demand forecast of the test book is expressed in terms of dollar sales.

27. :

The system as claimed in claim 15, further comprising means for utilizing the forecasted demand of the test book to make a demand-based publishing decision.

28. :

The system as claimed in claim 15, further comprising means for utilizing the forecasted demand of the test book to make a demand-based retailing decision.

29. :

A machine-readable medium having stored thereon sequences of instructions, which when executed by a processor cause an electronic system to;

(a) divide books into a plurality of categories with each of the categories having a unifying concept;

(f) develop a demand forecast model for each category by selecting a plurality of variables and, for each category, assigning to each selected variable a value based upon historical data showing the importance of each selected variable in predicting demand for books in that category;

(g) assign the test book to one of the categories based upon a similarity between the test book and the unifying concept of the assigned category;

(h) provide a target audience with the test book and survey the audience to capture data that can be used to calculate a forecasted value for each selected variable in the assigned category; and

(i) use the forecasted value for each selected variable in the demand forecast model for the assigned category to forecast a demand for the test book.