CREATION AND USAGE OF SYNTHETIC USER IDENTIFIERS WITHIN AN ADVERTISEMENT PLACEMENT FACILITY

• US 20120323674A1
• Filed: 06/29/2012
• Published: 12/20/2012
• Est. Priority Date: 08/14/2009
• Status: Abandoned Application

• Current Assignee: ROKU DX Holdings Incorporated (Roku, Inc.)
• Original Assignee: Dataxu (Roku, Inc.)
• Inventors: Simmons, Willard L., Catanzaro, Sandro N.
• Application Number:
  US13/537,991
• Publication Number:
  US 20120323674A1
• Time in Patent Office: Days
• US Class Current: 705/14.41
• 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 30/0273 Determination of fees for advertising
• CPC Class Codes: G06Q 30/0275 Auctions

Abstract

In embodiments of the present invention, improved capabilities are described for creating and using Synthetic User Identifiers within an advertising analytic platform for the purpose of targeting the placement of advertising within an available channel based at least in part on Synthetic User Identifier information.

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:

creating, at a server facility, a plurality of synthetic user identifiers by associating an advertisement with the advertisement'"'"'s impression data and at least two of user, device, and contextual information as derived from a plurality of users'"'"' interactions with the advertisement;

storing the synthetic user identifiers in a database accessible to the server facility and separate from a client system;

analyzing the plurality of synthetic user identifiers for correlations that indicate an advertisement type may produce a predetermined conversion rate if presented to an advertisement channel; and

recommending a targeted advertisement, which is associated with the advertisement type, to be presented to the advertisement channel.

2. The computer program product of claim 1, wherein the step of recommending involves recommending a bid amount for the targeted advertisement.

3. The computer program product of claim 1, wherein the step of recommending involves recommending a budget allocation for the targeted advertisement.

4. The computer program product of claim 1, wherein the step of recommending involves partitioning an advertisement inventory based on the synthetic user identifier.

5. The computer program product of claim 1, wherein the plurality of users'"'"' interactions with the advertisement derive from a plurality of advertising channels.

6. The computer program product of claim 5, wherein the plurality of advertising channels includes online and offline advertising channels.

7. The computer program product of claim 6, wherein the online advertising channels includes a website.

8. The computer program product of claim 6, wherein the offline advertising channels includes a print medium.

9. The computer program product of claim 1, wherein the contextual information is a device characteristic.

10. The computer program product of claim 1, wherein the contextual information is an operating system.

11. The computer program product of claim 1, wherein the contextual information is an advertising medium type.

12. The computer program product of claim 1, wherein the contextual information is a plurality of contextual information.

13. The computer program product of claim 1, wherein the contextual information is a user demographic.

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:

categorizing a plurality of available advertising channels, wherein each of the available advertising channels is categorized based at least in part on contextual information;

analyzing an advertising impression log relating to prior advertising placements within the plurality of categorized available advertising channels, wherein the analysis produces a quantitative association between a user and at least one of the available advertising channels, the quantitative association expressing at least in part a probability of the user recording an advertising conversion within at least one of the available advertising channels;

storing the quantitative association as a synthetic user identifier; and

selecting an advertisement to present to the user within at least one of the available advertising channels based at least in part on the synthetic user identifier.

15. The computer program product of claim 14, wherein the selected advertisement is presented to a second user that shares an attribute of the user with whom the user synthetic user identifier is associated.

16. The computer program product of claim 14, wherein a failure of the user to register a new impression following presentation of the selected advertisement is used by a learning machine facility to update the quantitative association.

17. The computer program product of claim 14, wherein a plurality of synthetic user identifiers, each bearing a quantitative association with the other, is tagged as a consumer cohort to which advertisers may bid on the opportunity to present advertisements using a real-time bidding machine facility.

18. The computer program product of claim 14, wherein the analysis includes using an economic valuation model that is further based in part on real-time bidding log data.

19. The computer program product of claim 14, wherein the analysis includes using an economic valuation model that is further based in part on historical bidding data.

20. A system for targeting the placement of advertising within an available channel based at least in part on contextual parameters from an advertising impression log, the system comprising:

a computer having a processor;

software which is operable on the processor, the software including an analytics platform facility that includes at least a learning machine and a valuation algorithms facility, wherein the software is adapted to;

create, at a server facility, a plurality of synthetic user identifiers by associating an advertisement with the advertisement'"'"'s impression data and at least two of user, device, and contextual information as derived from a plurality of users'"'"' interactions with the advertisement;

store the synthetic user identifiers in a database accessible to the server facility and separate from a client system;

use the synthetic user identifiers to target advertisements to consumers, wherein at least one of the amount, timing or duration of advertising presented to consumers is varied across available advertising channels based at least in part by use of the synthetic user identifiers;

analyze the plurality of synthetic user identifiers for correlations that indicate an advertisement type may produce a predetermined conversion rate if advertisements are presented through an advertisement channel and with an intensity level, wherein the intensity level is at least one of the amount, timing or duration of the advertising presented; and

recommend, for each specific synthetic user identifier, an adjusted intensity of advertising associated with the advertisement type, to be presented through each advertisement channel.