IP Library Granted Patent US 11,216,840
Granted Patent B2
US 11,216,840 · App. 16/953,775 · Granted Jan 4, 2022

Systems and methods for optimization of data element utilization according to multi-touch attribution

Inventors: Amir Cory (Palo Alto, CA); Katherine Krzoska (Palo Alto, CA); Shubo Liu (Belmont, CA); Garett Badeau (Redwood City, CA)
Assignee: ADAP.TV, Inc.
G06Q30/0244G06Q30/0277
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,216,840
App. No.
16/953,775
Granted
Jan 4, 2022
Kind
B2
Abstract

Systems and methods are disclosed for optimizing distribution of resources to data elements, comprising receiving a designation of one or more data elements for distribution; receiving a designation of a plurality of electronic event types detectable over a network, the plurality of electronic event types being associated with receipt or electronic display of at least one data element of the one or more data elements, to be tracked; forecasting a return on investment, associated with distribution of the one or more data elements, based on a forecast of occurrences of the plurality of electronic event types; and optimizing distribution of resources to the one or more data elements based on the forecasted return on investment.

Claims (51)

1. A computer-implemented method for optimizing distribution of resources for data elements to a user device, the method comprising:

receiving, at the one or more computers, a designation of a plurality of electronic event types detectable over a network to be tracked, the plurality of electronic event types being associated with one or more key performance indicators associated with receipt or electronic display of the one or more data elements;

receiving, at the one or more computers, a designation of a hierarchical prioritization of the one or more key performance indicators;

forecasting, at the one or more computers, a future distribution performance of the one or more key performance indicators;

optimizing, at the one or more computers, distribution of the one or more data elements by increasing resources to a first data element of the one or more data elements, based on a determination that the first data element is associated with a higher forecasted future distribution performance than another one or more other data elements for distribution; and

transmitting, at the one or more computers, the one or more data elements based on the optimized distribution, to the user device.

2. The computer-implemented method of claim 1 , further comprising:

receiving, at the one or more computers, tracking data associated with actual occurrences of each of the designated plurality of electronic event types associated with the one or more data elements; and

determining, by the one or more computers, an actual return on investment, associated with the one or more data elements, based on the tracking data.

3. The computer-implemented method of claim 2 , further comprising:

updating, by the one or more computers, a forecasted return on investment based, at least in part, upon the determined actual return on investment.

4. The computer-implemented method of claim 2 , further comprising:

updating, by the one or more computers, a forecasted return on investment in a recurring manner based upon an updated actual return on investment and the forecasted return on investment.

5. The computer-implemented method of claim 1 , wherein the one or more key performance indicators comprise one or more of a click count, a completion count, and a conversion count.

6. The computer-implemented method of claim 1 , wherein the tracking data comprises multi-touch attribution data.

7. The computer-implemented method of claim 1 , wherein the higher future performance indicator is a higher return on investment.

8. A system for optimizing distribution of resources for data elements to a user device, the system comprising:

a data storage device storing instructions; and

a processor configured to execute the instructions to perform a method including:

receiving, at one or more computers, a designation of one or more data elements for distribution;

receiving, at the one or more computers, a designation of a plurality of electronic event types detectable over a network to be tracked, the plurality of electronic event types being, associated with one or more key performance indicators associated with receipt or electronic display of the one or more data elements;

receiving, at the one or more computers, a designation of a hierarchical prioritization of the one or more key performance indicators;

forecasting, at the one or more computers, a future distribution performance of the one or more key performance indicators;

optimizing, at the one or more computers, distribution of the one or more data elements by increasing resources to a first data element of the one or more data elements, based on a determination that the first data element is associated with a higher forecasted future distribution performance than one or more other data elements for distribution; and

transmitting at the one or more computers, the one or more data elements based on the optimized distribution, to the user device.

9. The system of claim 8 , wherein the method further includes:

receiving tracking data associated with actual occurrences of each of the designated plurality of electronic event types associated with one or more data elements; and

determining an actual return on investment, associated with the one or more data elements, based on the tracking data.

10. The system of claim 9 , wherein the method further includes:

updating a forecasted return on investment based, at least in part, upon the determined actual return on investment.

11. The system of claim 9 , wherein the method further includes:

updating a forecasted return on investment in a recurring manner based upon an updated actual return on investment and the forecasted return on investment.

12. The system of claim 8 , wherein the one or more key performance indicators comprises one or more of a click count, a completion count, and a conversion count.

13. The system of claim 8 , wherein the tracking data comprises multi-touch attribution data.

14. The system of claim 8 , wherein the higher future performance indicator is a higher return on investment.

15. A non-transitory computer-readable medium storing instructions that, when executed by a processor, cause the processor to perform a method of optimizing distribution of resources for data elements to a user device, the method including:

receiving, at one or more computers, a designation of one or more data elements for distribution;

receiving, at the one or more computers, a designation of a plurality of electronic event types detectable over a network to be tracked, the plurality of electronic event types being associated with one or more key performance indicators associated with receipt or electronic display of the one or more data elements;

receiving, at the one or more computers, a designation of a hierarchical prioritization of the one or more key performance indicators;

forecasting, at the one or more computers, a future distribution performance of the one or more key performance indicators;

optimizing, at the one or more computers, distribution of the one or more data elements by increasing resources to a first data element of the one or more data elements, based on a determination that the first data element is associated with a higher forecasted future distribution performance than one or more other data elements for distribution; and

transmitting, at the one or more computers, the one or more data elements based on the optimized distribution, to the user device.

16. The non-transitory computer-readable medium of claim 15 , wherein the method further includes:

receiving tracking data associated with actual occurrences of each of the designated plurality of electronic event types associated with the one or more data elements; and

determining an actual return on investment, associated with the one or more data elements, based on the tracking data.

17. The non-transitory computer-readable medium of claim 16 , wherein the method further includes:

updating a forecasted return on investment based, at least in part, upon the determined actual return on investment.

18. The non-transitory computer-readable medium of claim 16 , wherein the method further includes:

updating a forecasted return on investment in a recurring manner based upon an updated actual return on investment and the forecasted return on investment.

19. The non-transitory computer-readable medium of claim 15 , wherein the one or more key performance indicators comprises one or more of a click count, a completion count, and a conversion count.

20. The non-transitory computer-readable medium of claim 15 , wherein the higher future performance indicator is a higher return on investment.

Assignments (3)
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 1, 2026
From: ADAP.TV LLC
To: YAHOO AGGREGATION HOLDINGS LLC
Reel/Frame 075313/0798 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 1, 2026
From: YAHOO AGGREGATION HOLDINGS LLC
To: YAHOO IP HOLDINGS LLC
Reel/Frame 075314/0306 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Nov 20, 2020
From: CORY, AMIR; KRZOSKA, KATHERINE; LIU, SHUBO; BADEAU, GARRETT
To: ADAP.TV, INC.
Reel/Frame 054430/0872 →