AUTOMATIC RESOURCE ADJUSTMENT BASED ON RESOURCE AVAILABILITY

• US 20200134663A1
• Filed: 10/31/2018
• Published: 04/30/2020
• Est. Priority Date: 10/31/2018
• Status: Abandoned Application

• Current Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Original Assignee: Microsoft Technology Licensing LLC (Microsoft Corporation)
• Inventors: Gao, Yuan, Pardoe, David, Peng, Lijun, Yan, Jinyun
• Application Number:
  US16/177,379
• Publication Number:
  US 20200134663A1
• Time in Patent Office: Days
• CPC Class Codes: G06Q 30/0249 based upon budgets or funds

Abstract

Techniques are provided for automatically adjusting a resource reduction amount based on resource availability and other factors. The following are determined for a content delivery campaign: a winning distribution for a target audience of the content delivery campaign, a through rate distribution of the content delivery campaign, a resource allocation of the content delivery campaign, and an estimated number of content item selection events in which the content delivery campaign will participate in a future time period. Based on these values, a resource reduction amount is determined. An example of a resource reduction amount is an effective cost per impression. The resource reduction amount is used in one or more subsequent content item selection events in which the content delivery campaign participates.

Claims

1. A method comprising:

determining a winning distribution for a target audience of a particular content delivery campaign;

determining a through rate distribution for the particular content delivery campaign;

determining a resource allocation of the particular content delivery campaign;

determining an estimated number of content item selection events in which the particular content delivery campaign will participate in a future time period;

based on the winning distribution, the through rate distribution, the resource allocation, and the estimated number of content item selection events, determining, for the particular content delivery campaign, a resource reduction amount;

using the resource reduction amount in one or more content item selection events in which the particular content delivery campaign participates;

wherein the method is performed by one or more computing devices.

2. The method of claim 1, wherein the winning distribution is based on one or more content item selection events in which the particular content delivery campaign did not participate.

3. The method of claim 1, wherein the through rate distribution of the particular content delivery campaign is based on a plurality of content item selection events in which the particular content delivery campaign was a candidate.

4. The method of claim 1, wherein the through rate distribution of the particular content delivery campaign is based on a plurality of content item selection events that one or more members in the target audience of the particular content delivery campaign initiated, wherein the particular content delivery campaign has not yet been activated.

5. The method of claim 1, wherein the resource reduction amount is a second resource reduction amount, the method further comprising:

prior to determining the second resource reduction amount, determining, for the particular content delivery campaign, a first resource reduction amount that is different than the second resource reduction amount;

wherein the first resource reduction amount was used for one or more content delivery campaigns in which the particular content delivery campaign participated prior to determining the second resource reduction amount.

6. The method of claim 1, further comprising:

calculating a first lambda value offline, wherein the resource reduction amount is based on the first lambda value for a first period of time;

using the resource reduction amount for the particular content delivery campaign in multiple content item selection events in which the particular content delivery campaign participates in the first period of time;

after using the resource reduction amount, calculating a second lambda value offline, wherein an updated resource reduction amount for the particular content delivery campaign is based on the second lambda value for a second period of time that is subsequent to the first period of time.

7. The method of claim 1, wherein the resource reduction amount is a first resource reduction amount that is based on a first lambda value, the method further comprising:

conducting a plurality content item selection events in which the particular content delivery campaign participates based on the resource reduction amount;

wherein conducting comprises a first machine conducting a first subset of the plurality of content item selection events and a second machine conducting a second subset of the plurality of content item selection events;

receiving, by a server, (1) first events generated by the first machine based on conducting the first subset and (2) second events generated by the second machine based on conducting the second subset;

determining, by the server, a second lambda value based on the first events and the second events;

sending, by the server, the second lambda value to the first machine and the second machine for subsequent content item selection events in which the particular content delivery campaign will participate.

8. The method of claim 1, further comprising:

conducting a plurality of content item selection events in which the particular content delivery campaign participates;

wherein conducting comprises a first machine conducting a first subset of the plurality of content item selection events based on a first through rate distribution and a second machine conducting a second subset of the plurality of content item selection events based on a second through rate distribution that is different than the first through rate distribution;

updating, by the first machine, the first through rate distribution based on the first subset to generate a third through rate distribution;

updating, by the second machine, the second through rate distribution based on the second subset to generate a fourth through rate distribution;

determining, by a server, based on a third through rate distribution and the fourth through rate distribution, a fifth through rate distribution;

sending, by the server, to the first machine and the second machine, the fifth through rate distribution;

determining, by the first machine, based on the fifth through rate distribution, a first updated resource reduction amount;

determining, by the second machine, based on the fifth through rate distribution, a second updated resource reduction amount.

9. A method comprising:

determining an actual remaining resource allocation of a particular content delivery campaign;

determining a projected remaining resource allocation of the particular content delivery campaign;

determining a ratio of the actual remaining resource allocation to the projected remaining resource allocation;

identifying a current cost given a current resource reduction amount of the particular content delivery campaign;

based on the ratio, identifying a new cost;

based on the new cost, identifying a new resource reduction amount of the particular content delivery campaign;

wherein the method is performed by one or more computing devices.

10. The method of claim 9, wherein:

determining the projected remaining resource allocation comprises;

determining a current projected resource allocation based on projected resource usage curve and determining a total resource allocation for the particular content delivery campaign;

subtracting the current projected resource allocation from the total resource allocation;

determining the actual remaining resource allocation comprises;

determining a current actual resource allocation and determining the total resource allocation for the particular content delivery campaign;

subtracting the current actual resource allocation from the total resource allocation.

11. The method of claim 9, further comprising:

generating an expected cost per content item selection event curve based on a history of content item selection events in which the particular content delivery campaign was a candidate content delivery campaign;

wherein identifying the current cost comprises using the current resource reduction amount of the particular content delivery campaign and the expected cost per content item selection event curve to identify the current cost.

12. The method of claim 9, wherein the new resource reduction amount is a first resource reduction amount, wherein the first resource reduction amount is determined during a resource usage period, the method further comprising, prior to the resource usage period expiring:

determining a second projected remaining resource allocation of the particular content delivery campaign, wherein the second projected remaining resource allocation is less than the projected remaining resource allocation;

determining a second actual remaining resource allocation of the particular content delivery campaign, wherein the second actual remaining resource allocation is less than the actual remaining resource allocation;

determining a second ratio of the second projected remaining resource allocation to the second actual remaining resource allocation;

identifying a second current cost given the first resource reduction amount of the particular content delivery campaign;

based on the second ratio, identifying a second new cost;

based on the second new cost, identifying a second resource reduction amount, of the particular content delivery campaign, that is different than the first resource reduction amount.

13. One or more storage media storing instructions which, when executed by one or more processors, cause:

determining a winning distribution for a target audience of a particular content delivery campaign;

determining a through rate distribution for the particular content delivery campaign;

determining a resource allocation of the particular content delivery campaign;

determining an estimated number of content item selection events in which the particular content delivery campaign will participate in a future time period;

based on the winning distribution, the through rate distribution, the resource allocation, and the estimated number of content item selection events, determining, for the particular content delivery campaign, a resource reduction amount;

using the resource reduction amount in one or more content item selection events in which the particular content delivery campaign participates.

14. The one or more storage media of claim 13, wherein the winning distribution is based on one or more content item selection events in which the particular content delivery campaign did not participate.

15. The one or more storage media of claim 13, wherein the through rate distribution of the particular content delivery campaign is based on a plurality of content item selection events in which the particular content delivery campaign was a candidate.

16. The one or more storage media of claim 13, wherein the through rate distribution of the particular content delivery campaign is based on a plurality of content item selection events that one or more members in a target audience of the particular content delivery campaign initiated, wherein the particular content delivery campaign has not yet been activated.

17. The one or more storage media of claim 13, wherein the resource reduction amount is a second resource reduction amount, wherein the instructions, when executed by the one or more processors, further cause:

prior to determining the second resource reduction amount, determining, for the particular content delivery campaign, a first resource reduction amount that is different than the second resource reduction amount;

wherein the first resource reduction amount was used for one or more content delivery campaigns in which the particular content delivery campaign participated prior to determining the second resource reduction amount.

18. The one or more storage media of claim 13, wherein the instructions, when executed by the one or more processors, further cause:

calculating a first lambda value offline, wherein the resource reduction amount is based on the first lambda value for a first period of time;

using the resource reduction amount for the particular content delivery campaign in multiple content item selection events in which the particular content delivery campaign participates in the first period of time;

after using the resource reduction amount, calculating a second lambda value offline, wherein an updated resource reduction amount for the particular content delivery campaign is based on the second lambda value for a second period of time that is subsequent to the first period of time.

19. The one or more storage media of claim 13, wherein the resource reduction amount is a first resource reduction amount that is based on a first lambda value, wherein the instructions, when executed by the one or more processors, further cause:

conducting a plurality content item selection events in which the particular content delivery campaign participates based on the resource reduction amount;

wherein conducting comprises a first machine conducting a first subset of the plurality of content item selection events and a second machine conducting a second subset of the plurality of content item selection events;

receiving, by a server, (1) first events generated by the first machine based on conducting the first subset and (2) second events generated by the second machine based on conducting the second subset;

determining, by the server, a second lambda value based on the first events and the second events;

sending, by the server, the second lambda value to the first machine and the second machine for subsequent content item selection events in which the particular content delivery campaign will participate.

20. The one or more storage media of claim 13, wherein the instructions, when executed by the one or more processors, further cause:

conducting a plurality of content item selection events in which the particular content delivery campaign participates;

wherein conducting comprises a first machine conducting a first subset of the plurality of content item selection events based on a first through rate distribution and a second machine conducting a second subset of the plurality of content item selection events based on a second through rate distribution that is different than the first through rate distribution;

updating, by the first machine, the first through rate distribution based on the first subset to generate a third through rate distribution;

updating, by the second machine, the second through rate distribution based on the second subset to generate a fourth through rate distribution;

determining, by a server, based on a third through rate distribution and the fourth through rate distribution, a fifth through rate distribution;

sending, by the server, to the first machine and the second machine, the fifth through rate distribution;

determining, by the first machine, based on the fifth through rate distribution, a first updated resource reduction amount;

determining, by the second machine, based on the fifth through rate distribution, a second updated resource reduction amount.