METHODS AND SYSTEMS FOR USING CONSUMER ALIASES AND IDENTIFIERS

• US 20140046777A1
• Filed: 10/18/2013
• Published: 02/13/2014
• Est. Priority Date: 08/14/2009
• Status: Abandoned Application

• Current Assignee: ROKU DX Holdings Incorporated (Roku, Inc.)
• Original Assignee: Dataxu (Roku, Inc.)
• Inventors: Catanzaro, Sandro N., Markey, Adam, Foldes, Robert, Simmons, Willard Lennox
• Application Number:
  US14/057,188
• Publication Number:
  US 20140046777A1
• Time in Patent Office: Days
• US Class Current: 705/14.66
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0241 Advertisements
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0243 Comparative campaigns
• CPC Class Codes: G06Q 30/0249 based upon budgets or funds
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising
• CPC Class Codes: G06Q 30/0275 Auctions

Abstract

Systems and methods are disclosed for creating a digital consumer profile that may be dynamically and transiently generated, drawing upon attribute data that is available at time of the digital consumer profile creation. The digital consumer profile may further provide for dynamic and transient generations of a plurality of user profiles to fit definitions and use cases not anticipated at the outset of targeting or attribution efforts and attribute data collection. Regulatory conditions, privacy policies, enterprise rules and the like may determine, at least in part, the collection, analysis, and auditing of attribute data, and the merging of such data to form aliases that may be associated with consumers. The digital consumer service may comprise binding expression syntax to dynamically, and transiently, identify profiles to give flexibility and extensibility beyond having a flat match table.

Claims

1. A computer program product embodied in a non-transitory computer readable medium that, when executing on one or more computers, performs the steps of:

acquiring a first alias, wherein the first alias is comprised of a first plurality of attributes, wherein each of the first plurality of attributes is comprised of at least one of a first device identifier datum, a first behavioral datum, and a first demographic datum;

acquiring a second alias, wherein the second alias is comprised of a second plurality of attributes, wherein each of the second plurality of attributes is comprised of at least one of a second device identifier datum, a second behavioral datum, and a second demographic datum;

dynamically and transiently linking the first alias and the second alias to form a Master ID, wherein the dynamic linking of the first and second aliases is based at least in part on analysis of the first and the second pluralities of attributes using a binding expression that expresses a statistical confidence threshold required for grouping aliases; and

targeting advertising to a consumer device based at least in part on the Master ID.

2. The computer program product of claim 1, wherein the computer program product further performs the alias acquiring and dynamically linking steps iteratively over a plurality of aliases so that a plurality of attributes are merged into a single Master ID.

3. The computer program product of claim 1, wherein the computer program product further performs a step of analyzing at least one of an advertising campaign targeted to the Master ID, consumer behavior associated with the Master ID, and consumer traits associated with the Master ID.

4. The computer program product of claim 1, wherein at least one of the first alias and the second alias is acquired from at least one of a consumer database of an organization and a third party database.

5. The computer program product of claim 1, wherein at least one of the first device identifier datum and the second device identifier datum comprises at least one of an IP address and a device ID.

6. The computer program product of claim 1, wherein dynamic linking of aliases is further based at least in part on a rules engine.

7. The computer program product of claim 6, wherein the rules engine includes rules for dynamic linking of aliases based at least in part on at least one of a regulatory constraint, a business agreement, a privacy policy, and a consumer preference.

8. The computer program product of claim 7, wherein dynamic linking of aliases prohibits linking aliases based on an identification of an IP address in certain predetermined geographical locations.

9. The computer program product of claim 1, wherein dynamic linking of aliases is performed based on a link type including at least one of self, household, and friend.

10. The computer program product of claim 1, wherein the first and the second aliases are linked only for a predetermined time period.

11. The computer program product of claim 1, wherein the aliases are stored in memory and include additional attributes time.

12. The computer program product of claim 1, wherein advertising is targeted to a plurality of linked consumer computing devices based on the Master ID.

13. The computer program product of claim 1, wherein the statistical confidence threshold varies depending on the alias attributes that are linked.

16. The computer program product of claim 1, wherein dynamic linking is achieved by matching attributes of aliases including at least one of an IP address, a device ID, an e-mail address, and cookie tracking information.

17. The computer program product of claim 16, wherein dynamic linking of alias is based on a rules engine and the rules engine includes rules for dynamic linking of aliases based at least in part on at least one of a regulatory constraint, a business agreement, a privacy policy, and a consumer preference.

18. The computer program product of claim 17, wherein the rules engine includes different rules for different geographic locations.

14. A computer program product embodied in a non-transitory computer readable medium that, when executing on one or more computers, performs the steps of:

acquiring a first alias, wherein the first alias is comprised of a first plurality of attributes, wherein each of the first plurality of attributes is comprised of at least one of a first device identifier datum, a first consumer datum, a first behavioral datum, and a first demographic datum;

acquiring a second alias, wherein the second alias is comprised of a second plurality of attributes, wherein each of the second plurality of attributes is comprised of at least one of a second device identifier datum, a second consumer datum, a second behavioral datum, and a second demographic datum;

dynamically and transiently linking the first alias and the second alias to form a Master ID, wherein the dynamic linking of the first and second aliases is based at least in part on analysis of the first and the second pluralities of attributes using a binding expression that expresses a statistical confidence threshold required for grouping aliases,

wherein the alias acquiring and dynamically linking steps are performed iteratively over a plurality of aliases so that a plurality of attributes are merged into a single Master ID;

targeting an advertising campaign to a consumer device based at least in part on the Master ID; and

analyzing results of the advertising campaign targeted to the Master ID.

15. The computer program product of claim 14, wherein at least one of the first alias and the second alias is acquired from at least one of a consumer database of an organization and a third party database.

19. A computer program product embodied in a non-transitory computer readable medium that, when executing on one or more computers, performs the steps of:

acquiring a first alias, wherein the first alias is comprised of a first plurality of attributes, wherein each of the first plurality of attributes is comprised of at least one of a first device identifier datum, a first consumer datum, a first behavioral datum, and a first demographic datum;

acquiring a second alias, wherein the second alias is comprised of a second plurality of attributes, wherein each of the second plurality of attributes is comprised of at least one of a second device identifier datum, a second consumer datum, a second behavioral datum, and a second demographic datum;

dynamically and transiently linking the first alias and the second alias to form a first Master ID, wherein the dynamic linking of the first and second aliases is based at least in part on analysis of the first and the second pluralities of attributes using a first binding expression that expresses a statistical confidence threshold required for grouping aliases;

acquiring a third alias, wherein the third alias is comprised of a third plurality of attributes, wherein each of the third plurality of attributes is comprised of at least one of a third device identifier datum, a third consumer datum, a third behavioral datum, and a third demographic datum;

acquiring a fourth alias, wherein the fourth alias is comprised of a fourth plurality of attributes, wherein each of the fourth plurality of attributes is comprised of at least one of a fourth device identifier datum, a fourth consumer datum, a fourth behavioral datum, and a fourth demographic datum;

dynamically and transiently linking the third alias and the fourth alias to form a second Master ID, wherein the dynamic linking of the third and fourth aliases is based at least in part on analysis of the first and the second pluralities of attributes using a second binding expression that expresses a statistical confidence threshold required for grouping aliases;

merging the first Master ID and the second Master ID to form a circle set, the merging based on a recognition that the Master IDs are related to each other by one of a type of self, household, and friend; and

targeting an advertising campaign to multiple consumer devices based at least in part on the circle set.

20. The computer program product of claim 19, wherein dynamic linking is achieved by matching attributes of aliases including at least one of an IP address, a device ID, an e-mail address, and cookie tracking information.