METHODS AND APPARATUS TO DETERMINE THE EFFECTS OF TRADE PROMOTIONS ON COMPETITIVE STORES

• US 20100063870A1
• Filed: 06/29/2009
• Published: 03/11/2010
• Est. Priority Date: 09/05/2008
• Status: Abandoned Application

• Current Assignee: Nielsen Company (US) LLC (RR Donnelley & Sons Company)
• Original Assignee: Nielsen Company (US) LLC (RR Donnelley & Sons Company)
• Inventors: Duffy, Denise J., Zenor, Mike J., Anderson, Gregory D., Mansour, John P.
• Application Number:
  US12/493,495
• Publication Number:
  US 20100063870A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• 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 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0211 Determining the effectiveness of discounts or incentives
• CPC Class Codes: G06Q 30/0246 Traffic

Abstract

Example methods and apparatus to determine the effects of trade promotions on competitive stores are disclosed. A disclosed example method includes identifying a target product sold at the target store associated with the trade promotion, and identifying a plurality of competitive products having a degree of similarity to the target product. The example method also includes retrieving all commodities volume (ACV) data from a plurality of stores in a geography of interest that sell the plurality of competitive products, calculating a percentage overlap of the ACV data to generate a competitive trading area table of store pairs within a threshold value of the overlap, calculating a brand store switching value by dividing a brand incremental volume by a base equivalent volume for the store pairs, the brand store switching value indicative of the trade promotion store effect; and generating a report including the brand store switching value.

Claims

1. A computer implemented method to identify a competitive store effect in response to a trade promotion at a target store, comprising:

identifying a target product sold at the target store associated with the trade promotion;

identifying a plurality of competitive products having a degree of similarity to the target product;

retrieving all commodities volume (ACV) data from a plurality of stores in a geography of interest that sell the plurality of competitive products;

calculating a percentage overlap of the ACV data to generate a competitive trading area table of store pairs within a threshold value of the overlap;

calculating a brand store switching value by dividing a brand incremental volume by a base equivalent volume for the store pairs, the brand store switching value indicative of the trade promotion store effect; and

generating a report including the brand store switching value.

2. A method as defined in claim 1, further comprising applying an intra brand store switching coefficient to calculate a factor contributive sub volume of the target product at the target store based on the trade promotion at the target store.

3. A method as defined in claim 2, wherein the applied intra brand store switching coefficient is generated via a hierarchical linear modeling technique.

4. A method as defined in claim 2, wherein the applied intra brand store switching coefficient is generated via at least one of a linear regression or a multiple linear regression technique.

5. A method as defined in claim 1, further comprising applying an inter brand store switching coefficient to calculate a factor contributive sub volume of the target product at a competitive store in the plurality of stores in the geography of interest, the inter brand store switching coefficient based on the trade promotion at the target store.

6. A method as defined in claim 5, wherein the applied inter brand store switching coefficient is generated via a hierarchical linear modeling technique.

7. A method as defined in claim 5, wherein the applied inter brand store switching coefficient is generated via at least one of a linear regression or a multiple linear regression technique.

8. A method as defined in claim 1, wherein calculating the brand store switching value further comprises calculating a base volume of sales for the target store during a time period.

9. A method as defined in claim 8, further comprising calculating base factor contributive sub volumes during the time period to identify at least one of a sales increase or a sales decrease.

10. A method as defined in claim 9, wherein the base factor contributive sub volumes are based on at least one of a regular price factor or a distribution factor.

11. A method as defined in claim 9, further comprising calculating a base residual volume indicative of the difference between the base equivalent volume and the base factor contributive sub volumes adjusted by at least one of seasonality factors or trend factors.

12. A method as defined in claim 11, further comprising determining an incremental volume at the target store caused by the trade promotion by calculating the difference between actual sales and the base residual volume.

13. A method as defined in claim 12, wherein the incremental volume is based on a coefficient associated with a combination of the target store and a universal product code (UPC) associated with the target product.

14. A method as defined in claim 13, wherein the coefficient comprises at least one of a promoted price coefficient associated with the UPC, a temporary price reduction coefficient associated with the UPC, a feature coefficient, or a display coefficient.

15. An apparatus to identify a competitive store effect in response to a trade promotion at a target store, comprising:

a product reference interface to identify a target product sold at a target store, the target product associated with the trade promotion;

a target product comparator to identify a plurality of competitive products having a degree of similarity to the target product;

a promotion analysis engine to retrieve all commodities volume (ACV) data from a plurality of stores in a geography of interest;

a trading area competitive activity assessor to calculate a percentage overlap of the ACV data and to generate a competitive trading area table of store pairs within a threshold percentage value, the store pairs containing the identified plurality of competitive products; and

a pre-model data generator to calculate a brand store switching value by dividing a brand incremental volume by a base equivalent volume for the store pairs, the brand store switching value indicative of the trade promotion store effect.

16. An apparatus as defined in claim 15, further comprising a model coefficient estimator to apply an intra brand store switching coefficient to calculate a factor contributive sub volume of the target product at the target store based on the trade promotion at the target store.

17. An apparatus as defined in claim 16, further comprising a hierarchical linear model to generate the intra brand store switching coefficient.

18. An apparatus as defined in claim 16, further comprising at least one of a linear regression model or a multiple linear regression model to generate the intra brand store switching coefficient.

19. An apparatus as defined in claim 15, further comprising a model coefficient estimator to apply an inter brand store switching coefficient to calculate a factor contributive sub volume of the target product at a competitive store in the plurality of stores in the geography of interest, the inter brand store switching coefficient based on the trade promotion at the target store.

22. An apparatus as defined in claim 15, further comprising a trading area sales data store to identify a plurality of census blocks associated with the store pairs of the competitive trading area table.

20. (canceled)

21. (canceled)

23. (canceled)

24. An article of manufacture storing machine accessible instructions that, when executed, cause a machine to:

identify a target product sold at the target store associated with the trade promotion;

identify a plurality of competitive products having a degree of similarity to the target product;

retrieve all commodities volume (ACV) data from a plurality of stores in a geography of interest that sell the plurality of competitive products;

calculate a percentage overlap of the ACV data to generate a competitive trading area table of store pairs within a threshold value of the overlap;

calculate a brand store switching value by dividing a brand incremental volume by a base equivalent volume for the store pairs, the brand store switching value indicative of the trade promotion store effect; and

generate a report including the brand store switching value.

25-33. -33. (canceled)