METHOD AND SYSTEM FOR GENERATION OF ANONYMOUS PROFILES FROM A TRI-LEVEL MAPPING OF MOBILE NETWORK MARKETING ECONOMETRICS

1 . A processor-based method of generating an anonymous profile, the method comprising:

receiving by a processor operating on a server a mobile device identifier, wherein the mobile device identifier is unique to a mobile computing device;

determining by the processor a location of the mobile computing device within a marketing environment;

associating by the processor the location of the mobile computing device with a location of a product within the marketing environment;

obtaining by the processor interaction data indicative of an engagement of the mobile computing device with the product; and

storing the interaction data in a profile associated with the mobile device identifier.

2 . The processor-implemented method of claim 1 , wherein the interaction data are selected from the group consisting of a speed at which the mobile computing device passed the location of the product, an amount of time the mobile computing device remained at the location of the product, a scan by the mobile computing device of a code associated with the product, a scan by the mobile computing device of an object associated with the product, a number of visits to the location of the product by the mobile computing device, a purchase of the product and a scan by the mobile computing device of an object representing another product related to the product.

3 . The processor-implemented method of claim 1 further comprising determining by the processor a behavior of the user of the mobile computing device from the interaction data, wherein the behavior is selected from the group consisting of a pre-planned purchase, browsing, and a purchase inspired by marketing materials presented in the shopping environment.

4 . The processor-implemented method of claim 1 further comprising determining by the processor a measure of interest in the product using the interaction data.

5 . The processor-implemented method of claim 4 further comprising:

aggregating by the processor interaction data of the user of the mobile computing device and interaction data of other users of other mobile computing devices with the product;

determining by the processor an aggregated measure of interest in the product from the interaction data of the user and the interaction data of other users; and

measuring by the processor an effectiveness of product marketing materials related to the product from the aggregated measure of interest.

6 . The processor-implemented method of claim 4 further comprising:

aggregating by the processor interaction data of the user of the mobile computing device and interaction data of other users of other mobile computing devices with the product;

determining by the processor an aggregated measure of interest in the product from the interaction data of the user and the interaction data of other users; and

measuring by the processor an effectiveness of a configuration of the marketing environment from the aggregated measure of interest.

7 . The processor-implemented method of claim 4 further comprising:

aggregating by the processor interaction data of the user of the mobile computing device and interaction data of other users of other mobile computing devices with the product;

determining by the processor an aggregated measure of interest in the product from the interaction data of the user and the interaction data of other users; and

measuring by the processor an effectiveness of a marketing strategy implemented at a particular time of day or on a particular day of the week from the aggregated measure of interest.

8 . The processor-implemented method of claim 5 , wherein the marketing materials are selected from the group consisting of a display within the marketing environment, displays outside of the marketing environment, advertisements for the product provided in print media, advertisements for the product in video media, web-based advertisements for the product, a social networking campaign for the product, and coupons for the product.

9 . The processor-implemented method of claim 1 , wherein products in the marketing environment have known locations and determining by the processor a location of the mobile computing device within a marketing environment comprises determining the location of the mobile computing device from engagements between the mobile computing device and one or more products.

10 . The processor-implemented method of claim 1 , wherein determining by the processor the location of the mobile computing device comprises:

obtaining by the processor sensor data indicative of the proximity of the mobile computing device to a known location; and

determining by the processor the location of the mobile computing device using the sensor data.

11 . The processor-implemented method of claim 1 , wherein the mobile computing device is selected from the group consisting of a smartphone, a tablet and a personal data assistant.

12 . A system for generating an anonymous profile, the system comprising:

a memory, wherein the memory comprises software executable instructions;

a profile management server, wherein the profile management server comprises a processor, a memory comprises software executable instructions, and wherein the first processor is configured with the software executable instructions from the memory to cause the profile management server to perform operations comprising:

receiving a mobile device identifier, wherein the mobile device identifier is unique to a mobile computing device;

determining by the processor a location of the mobile computing device within a marketing environment;

associating by the processor the location of the mobile computing device with a location of a product within the marketing environment;

obtaining by the processor interaction data indicative of an engagement of the mobile computing device with the product; and

storing the interaction data in a profile associated with the mobile device identifier.

13 . The system of claim 1 , wherein the interaction data are selected from the group consisting of a speed at which the mobile computing device passed the location of the product, an amount of time the mobile computing device remained at the location of the product, a scan by the mobile computing device of a code associated with the product, a scan by the mobile computing device of an object associated with the product, a number of visits to the location of the product by the mobile computing device, a purchase of the product and a scan by the mobile computing device of an object representing another product related to the product.

14 . The system of claim 12 , wherein the processor is configured with the software executable instructions to cause profile management server to perform operations further comprising determining a behavior of the user of the mobile computing device from the interaction data, wherein the behavior is selected from the group consisting of a pre-planned purchase, browsing, and a purchase inspired by marketing materials presented in the shopping environment.

15 . The system of claim 12 wherein the processor is configured with the software executable instructions to cause profile management server to perform operations further comprising determining by the processor a measure of interest in the product using the interaction data.

16 . The system of claim 15 , wherein the processor is configured with the software executable instructions to cause profile management server to perform operations further comprising:

aggregating interaction data of the user of the mobile computing device and interaction data of other users of other mobile computing devices with the product;

determining an aggregated measure of interest in the product from the interaction data of the user and the interaction data of other users; and

measuring an effectiveness of product marketing materials related to the product from the aggregated measure of interest.

17 . The system of claim 15 , wherein the processor is configured with the software executable instructions to cause profile management server to perform operations further comprising:

aggregating interaction data of the user of the mobile computing device and interaction data of other users of other mobile computing devices with the product;

determining an aggregated measure of interest in the product from the interaction data of the user and the interaction data of other users; and

measuring an effectiveness of a configuration of the marketing environment from the aggregated measure of interest.

18 . The system of claim 15 , wherein the processor is configured with the software executable instructions to cause profile management server to perform operations further comprising:

aggregating interaction data of the user of the mobile computing device and interaction data of other users of other mobile computing devices with the product;

determining an aggregated measure of interest in the product from the interaction data of the user and the interaction data of other users; and

measuring an effectiveness of a marketing strategy implemented at a particular time of day or on a particular day of the week from the aggregated measure of interest.

19 . The system of claim 5 , wherein the marketing materials are selected from the consisting of a display within the marketing environment, displays outside of the marketing environment, advertisements for the product provided in print media, advertisements for the product in video media, web-based advertisements for the product, a social networking campaign for the product, and coupons for the product.

20 . The system of claim 1 , wherein products in the marketing environment have known locations and the operation determining a location of the mobile computing device within a marketing environment comprises determining the location of the mobile computing device from engagements between the mobile computing device and one or more products.

21 . The system of claim 1 , wherein the operation determining the location of the mobile computing device comprises:

obtaining sensor data indicative of the proximity of the mobile computing device to a known location; and

determining the location of the mobile computing device using the sensor data.

22 . The system of claim 12 , wherein the mobile computing device is selected from the group consisting of a smartphone, a tablet and a personal data assistant.