Claims:WE CLAIM
1. A method for determining an effectiveness of a promotion, the method comprising:
receiving, by a promotion effectiveness analytics engine, data related to sales and promotions for a plurality of products from one or more data sources, wherein the plurality of products comprises a plurality of aggressor products and a plurality of victim products;
analyzing, by the promotion effectiveness analytics engine, the data to determine a set of significant aggressor products for each of the plurality of victim products;
assessing, by the promotion effectiveness analytics engine, an impact of each of the set of significant aggressor products on a respective victim product;
determining, by the promotion effectiveness analytics engine, the effectiveness of the promotion with respect to a product based on the data related to sales of the product under the promotion, and the impact of the product on each of one or more associated victim products.

2. The method of claim 1, wherein the data related to sales and promotions comprises at least one of: sales revenue data, sales volume data, and merchandising data prior to, during, and after one or more promotional events for each of the plurality of products.

3. The method of claim 1, wherein the one or more data sources comprises at least one of: a retailer, a supplier, a sales team, a third-party market research organization, a real-time sales management platform.

4. The method of claim 1, wherein the plurality of aggressor products and the plurality of victim products are identified or fed by a user.

5. The method of claim 1, wherein analyzing the data to determine the set of significant aggressor products comprises:
screening the data to determine a plurality of potential aggressor products for each of the plurality of victim products; and
determining the set of significant aggressor products from among the plurality of potential aggressor products.

6. The method of claim 5, wherein screening the data comprises:
deriving a multicollinearity index between each of the plurality of aggressor products and each of the plurality of victim products; and
selecting the plurality of potential aggressor products from among the plurality of aggressor products based on the corresponding multicollinearity indices.

7. The method of claim 5, wherein determining the set of significant aggressor products comprises determining the set of significant aggressor products from among the plurality of potential aggressor products using back-step filtering multivariate regression.

8. The method of claim 1, wherein assessing the impact comprises estimating impact coefficients using back-step filtering multivariate regression.

9. The method of claim 1, further comprising converting the impact of each of the set of significant aggressor products on a respective victim product as metadata, and storing the metadata for subsequent use.

10. A system for determining an effectiveness of a promotion, the system comprising:
at least one processor; and
a computer-readable medium storing instructions that, when executed by the at least one processor, cause the at least one processor to perform operations comprising:
receiving data related to sales and promotions for a plurality of products from one or more data sources, wherein the plurality of products comprises a plurality of aggressor products and a plurality of victim products;
analyzing the data to determine a set of significant aggressor products for each of the plurality of victim products;
assessing an impact of each of the set of significant aggressor products on a respective victim product; and
determining the effectiveness of the promotion with respect to a product based on the data related to sales of the product under the promotion, and the impact of the product on each of one or more associated victim products.

11. The system of claim 10, wherein analyzing the data to determine the set of significant aggressor products comprises:
screening the data to determine a plurality of potential aggressor products for each of the plurality of victim products; and
determining the set of significant aggressor products from among the plurality of potential aggressor products.

12. The system of claim 11, wherein screening the data comprises:
deriving a multicollinearity index between each of the plurality of aggressor products and each of the plurality of victim products;
selecting the plurality of potential aggressor products from among the plurality of aggressor products based on the corresponding multicollinearity indices.

13. The system of claim 11, wherein determining the set of significant aggressor products comprises determining the set of significant aggressor products from among the plurality of potential aggressor products using back-step filtering multivariate regression.

14. The system of claim 10, wherein assessing the impact comprises estimating impact coefficients using back-step filtering multivariate regression.

15. The system of claim 10, wherein the operations further comprise converting the impact of each of the set of significant aggressor products on a respective victim product as metadata, and storing the metadata for subsequent use.

Dated this 30th day of June, 2017

R Ramya Rao
Of K&S Partners
Agent for the Applicant
, Description:TECHNICAL FIELD
This disclosure relates generally to product promotions, and more particularly to system and method for determining effectiveness of product promotions.