METHODS AND APPARATUS TO CREATE MODELING GROUPS FOR USE IN TRADE PROMOTION RESPONSE MODELS

• US 20100063869A1
• Filed: 03/31/2009
• Published: 03/11/2010
• Est. Priority Date: 09/05/2008
• Status: Abandoned Application

• Current Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Original Assignee: The Nielsen Company LLC (MOOD Media Corporation)
• Inventors: Kriss, Mitchel
• Application Number:
  US12/414,822
• Publication Number:
  US 20100063869A1
• 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 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0251 Targeted advertisements

Abstract

Methods and apparatus to create modeling groups for use in trade promotion response models are disclosed. An example computer implemented method to generate a modeling group for use in a trade promotion response model includes generating products groups, each of which includes one or more product codes corresponding to substantially similar products; generating advertisement identifiers, each of which corresponds to an advertisement and one or more product codes associated with one or more products in the advertisement; selecting a first product group from the product groups; selecting one of the advertisement identifiers corresponding to one or more product codes that are also in the first product group; and generating a modeling group for a trade promotion response model by grouping together ones of the product groups that include the product codes corresponding to the selected one of the advertisement identifiers.

Claims

1. A computer implemented method to generate a modeling group for use in a trade promotion response model, comprising:

generating products groups, each of which includes one or more product codes corresponding to substantially similar products;

generating advertisement identifiers, each of which corresponds to an advertisement and one or more product codes associated with one or more products in the advertisement;

selecting a first product group from the product groups;

selecting one of the advertisement identifiers corresponding to one or more product codes that are also in the first product group; and

generating a modeling group for a trade promotion response model by grouping together ones of the product groups that include the product codes corresponding to the selected one of the advertisement identifiers.

2. A computer implemented method as defined in claim 1, further comprising splitting the modeling group into one or more final modeling groups according to brand aggregation levels.

3. A computer implemented method as defined in claim 2, wherein splitting the modeling group includes determining a first brand aggregation level at which the product groups of the modeling group become dissimilar with respect to brand name.

4. A computer implemented method as defined in claim 1, further comprising qualifying the products of the advertisement by comparing base prices to advertised prices.

5. A computer implemented method as defined in claim 1, wherein selecting the first product group comprises determining which of the product groups is associated with a highest dollar importance.

6. A computer implemented method as defined in claim 5, wherein the highest dollar importance is determined by referencing point-of-sale data.

7. A computer implemented method as defined in claim 1, wherein selecting the one of the advertisement identifiers further comprises identifying which of the advertisement identifiers corresponding to the one or more product codes that are also in the first product group is a most populated advertisement identifier.

8. A computer implemented method as defined in claim 1, wherein generating the modeling group further comprises determining which of the products featured in the selected one of the advertisement identifiers are of a substantially similar type.

9. A computer implemented method as defined in claim 1, wherein the product codes comprise universal product codes.

10. A computer implemented method as defined in claim 1, wherein generating products groups, each of which includes one or more product codes corresponding to substantially similar products comprises determining whether products are substantially similar by referencing one or more product characteristics of description strings associated with the product codes.

11. A computer implemented method as defined in claim 10, wherein the product characteristics include at least one of a base description, a base size, or a base pack size.

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20. A modeling group generator for use in a trade promotion response model, comprising:

a unit definer to generate products groups, each of which includes one or more product codes corresponding to substantially similar products;

a feature identifier generator to generate advertisement identifiers, each of which corresponds to an advertisement and one or more product codes associated with one or more products in the advertisement;

a unit selector to select a first product group from the product groups;

a feature selector to select one of the advertisement identifiers corresponding to one or more product codes that are also in the first product group; and

a unit grouper to generate a modeling group for a trade promotion response model by grouping together ones of the product groups that include the product codes corresponding to the selected one of the advertisement identifiers.

21. A modeling group generator as defined in claim 20, further comprising a group splitter to split the modeling group into one or more final modeling groups according to brand aggregation levels.

22. A modeling group generator as defined in claim 21, wherein the group splitter is to split the modeling group by determining a first brand aggregation level at which the product groups of the modeling group become dissimilar with respect to brand name.

23. A modeling group generator as defined in claim 20, further comprising a feature qualifier to qualify the products of the advertisement by comparing base prices to advertised prices.

24. A modeling group generator as defined in claim 20, wherein the unit selector is to select the first product group by determining which of the product groups is associated with a highest dollar importance.

25. A modeling group generator as defined in claim 24, wherein the highest dollar importance is determined by referencing point-of-sale data.

26. A modeling group generator as defined in claim 20, wherein the feature selector is to select the one of the advertisement identifiers by identifying which of the advertisement identifiers corresponding to the one or more product codes that are also in the first product group is a most populated identifier.

27. A modeling group generator as defined in claim 20, wherein the unit grouper is to generate the modeling group by determining which of the products featured in the selected one of the advertisement identifiers are of a substantially similar type.

28. A trade promotion response modeling system, comprising:

a promotion detection system to collect information related to a plurality of advertisements;

a product characteristic source including product characteristics associated with a plurality of products of a marketplace;

a sales trend data source including financial information related to the plurality of products; and

a modeling group generator comprising

a plurality of product groups, each of which includes one or more product codes corresponding to substantially similar products; and

a plurality of advertisement identifiers, each of which corresponds to an advertisement and one or more product codes associated with one or more products in the advertisement, wherein the modeling group generator is configured to select a first one of the advertisements based on a first code of a first one of the product groups, and wherein the modeling group generator is configured to generate a modeling group for a trade promotion response model by grouping together ones of the product groups that include the product codes corresponding to the selected one of the advertisement identifiers.