Systems and methods for price and promotion response analysis

• US 8,010,404 B1
• Filed: 10/31/2007
• Issued: 08/30/2011
• Est. Priority Date: 12/22/2000
• Status: Expired due to Term

• Current Assignee: Acoustic, L.P.
• Original Assignee: DemandTec Inc. (International Business Machines Corporation)
• Inventors: Valentine, Suzanne Noel, Wu, Howard Yihzan, Kervin, Sean, Desai, Paritosh, Gunnink, Jason Lee
• Primary Examiner(s): CAMPBELL, SHANNON S
• Application Number:
  US11/933,395
• Time in Patent Office: 1,399 Days
• Field of Search: 705/1.1
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements

Abstract

A system and method for price and promotion response analysis is provided. Such a system is useful for a business to analyze the forecasted lifts associated with changes in price and promotion activity. The system sets the configuration of the response report, which includes price change and promotion change intervals. Promotions include temporary price reductions, displays, ads and multiples. Modeling data is received for the products. Forecasts, both non-cannibalistic and cannibalistic, are generated for the sales of the products dependent upon the price change and promotion change intervals. Forecasts include at least one of product forecasts, demand group forecasts, line level forecasts and category level forecasts. Suspect forecasts below a minimum confidence may be flagged. Confidence matrices may be generated which reflect accuracy of the forecasts. The response report may be generated by collecting the forecasts and the confidence matrices according to the configuration of the response report.

Claims

1. A computer implemented method for generating response data for a plurality of products to changes in at least one of pricing and promotions, useful in conjunction with a price optimization system, the method comprising:

setting configuration of a response report where the configuration includes price change and promotion change intervals, and wherein the response report includes the response data;

receiving modeling data for the plurality of products;

generating forecasts, using a computer processor, for the sales of the products for the price change and promotion change intervals;

generating confidence matrices, where the confidence matrices reflect accuracy of the generated forecasts, and wherein the confidence matrices includes calculating minimum and maximum price change, number of price changes, number of price changes in a demand group, and frequency of promotions; and

generating the response report by collecting the forecasts and the confidence matrices according to the set configuration of the response report.

2. The computer implemented method, as recited in claim 1, wherein the promotions include at least one of temporary price reductions, displays, ads and multiples.

3. The computer implemented method, as recited in claim 1, wherein the forecasts include non-cannibalistic forecasts.

4. The computer implemented method, as recited in claim 1, wherein the forecasts include cannibalistic forecasts.

5. The computer implemented method, as recited in claim 1, wherein the forecasts include product forecasts, demand group forecasts, line level forecasts and category level forecasts.

6. The computer implemented method, as recited in claim 1, wherein the modeling data is generated during product price optimization.

7. The computer implemented method, as recited in claim 2, wherein the frequency of the promotions includes at least one of temporary price reduction count, ad count, display count, and multiple count.

8. The computer implemented method, as recited in claim 1, further comprising flagging suspect forecasts which include forecasts that have below a minimum level of confidence.

17. The computer implemented method, as recited in claim 1, wherein the demand group is a group of highly substitutable products.

19. The computer implemented method, as recited in claim 1, wherein the forecasts include determining lift for temporary price reductions, in store displays, advertisements, mail in rebates, and multiples promotions.

21. The computer implemented method, as recited in claim 1, wherein the confidence matrices further includes determining a range between the minimum and the maximum price change, and when lift is forecasted for price changes outside of the range reducing confidence in the forecast.

9. A price and promotion response analyzer for generating response data for a plurality of products to changes in at least one of pricing and promotions, useful in conjunction with a price optimization system, the apparatus comprising:

a user interface configured to set configuration of a response report where the configuration includes price change and promotion change intervals, and wherein the response report includes the response data;

a forecaster configured to receive modeling data for the plurality of products, and further to generate forecasts for the sales of the products for the price change and promotion change intervals;

a confidence analyzer configured to generate confidence matrices, where the confidence matrices reflect accuracy of the generated forecasts, and wherein the confidence matrices includes calculating minimum and maximum price change, number of price changes, number of price changes in a demand group, and frequency of promotions; and

a report generator configured to generate the response report by collecting the forecasts and the confidence matrices according to the set configuration of the response report.

10. The price and promotion response analyzer of claim 9, wherein the promotions include at least one of temporary price reductions, displays, ads and multiples.

11. The price and promotion response analyzer of claim 9, wherein the forecaster is configured to generate non-cannibalistic forecasts.

12. The price and promotion response analyzer of claim 9, wherein the forecaster is configured to generate cannibalistic forecasts.

13. The price and promotion response analyzer of claim 9, wherein the forecaster is configured to generate product forecasts, demand group forecasts, line level forecasts and category level forecasts.

14. The price and promotion response analyzer of claim 9, wherein the forecaster receives modeling data that is generated during product price optimization.

15. The price and promotion response analyzer of claim 10, wherein the frequency of the promotions includes at least one of temporary price reduction count, ad count, display count, and multiple count.

16. The price and promotion response analyzer of claim 9, further comprising a flagger configured to identify suspect forecasts which include forecasts that have below a minimum level of confidence.

18. The price and promotion response analyzer of claim 9, wherein the demand group is a group of highly substitutable products.

20. The price and promotion response analyzer of claim 9, wherein the forecasts include determining lift for temporary price reductions, in store displays, advertisements, mail in rebates, and multiples promotions.

22. The price and promotion response analyzer of claim 9, wherein the confidence matrices further includes determining a range between the minimum and the maximum price change, and when lift is forecasted for price changes outside of the range reducing confidence in the forecast.