SYSTEMS AND METHODS FOR OPTIMIZING IMPRESSION FREQUENCY

• US 20150242907A1
• Filed: 02/26/2014
• Published: 08/27/2015
• Est. Priority Date: 02/26/2014
• Status: Abandoned Application

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Wray, Nicholas B.
• Application Number:
  US14/191,274
• Publication Number:
  US 20150242907A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0249 based upon budgets or funds
• CPC Class Codes: G06Q 30/0275 Auctions

Abstract

Systems and methods for optimizing impression frequency for content presented on a client device are provided. A content distribution system selects a subset of available impressions on which to place bids such that a predetermined content distribution budget is spent and the bids are placed on impressions associated with a minimum number of unique user identifiers. The content distribution system receives a notification of an available impression for presenting content on a client device and identifies a user identifier associated with the client device. The content distribution system calculates a hash value for the user identifier as a function of the user identifier and compares the hash value with an impression probability threshold. The content distribution system determines whether to bid on the available impression based on a result of the comparison.

Claims

1. A method for optimizing impression frequency for content presented on a client device, the method comprising:

receiving, at a computing system, a notification of an available impression for presenting content on a client device;

identifying, by the computing system, a user identifier associated with the available impression;

mapping, by the computing system, the user identifier to a calculated value within a normalized range, wherein the calculated value is a function of the user identifier;

comparing, by the computing system, the calculated value with an impression probability threshold; and

determining, by the computing system, whether to bid on the available impression based on a result of the comparison.

2. The method of claim 1, wherein the calculated value is a hash value calculated for the user identifier as a function of the user identifier;

wherein the hash value is uniformly distributed with respect to a plurality of different hash values within the normalized range;

wherein each of the plurality of different hash values is calculated as a function of a different user identifier.

3. The method of claim 1, wherein the calculated value is a function of both the user identifier and a campaign identifier associated with a content distribution campaign.

4. The method of claim 1, wherein the impression probability threshold is associated with a content distribution campaign, the method further comprising:

calculating the impression probability threshold as a function of a content distribution budget for the campaign.

5. The method of claim 4, wherein calculating the impression probability threshold comprises:

using content distribution parameters of the campaign to estimate a non-throttled spending rate for the campaign; and

using the content distribution budget and the non-throttled spending rate to determine a proportion of impressions which satisfy the content distribution parameters and on which bids can be placed without exceeding the content distribution budget.

6. The method of claim 4, further comprising:

determining whether the identified user identifier has previously received content associated with the content distribution campaign; and

increasing the impression probability threshold in response to a determination that the identified user identifier has previously received content associated with the content distribution campaign.

7. The method of claim 1, wherein determining whether to bid on the available impression comprises:

determining to bid on the available impression in response to a determination that the calculated value is less than the impression probability threshold; and

determining to not bid on the available impression in response to a determination that the calculated value is not less than the impression probability threshold.

8. The method of claim 1, further comprising:

classifying the user identifier as a throttled user identifier or a non-throttled user identifier with respect to a content distribution campaign based on a result of the comparison;

delivering content associated with the campaign to the client device in response to classifying the user identifier as a non-throttled user identifier; and

preventing content associated with the campaign from being delivered to the client device in response to classifying the user identifier as a throttled user identifier.

9. A system for optimizing impression frequency for content presented on a client device, the system comprising:

a computing system configured to receive notifications of available impressions for presenting content on a client device;

wherein the computing system is configured to identify, for each of the available impressions, a user identifier associated with the available impression;

wherein the computing system is configured to select a subset of the available impressions on which to place bids such that a predetermined content distribution budget is spent on winning bids and the bids are placed on impressions associated with a minimum number of unique user identifiers.

10. The system of claim 9, wherein the computing system is configured to calculate, for each of the available impressions, a hash value for the associated user identifier as a function of the user identifier and to compare the hash value with an impression probability threshold;

wherein the computing system selects the subset of the available impressions based on a result of the comparison.

11. The system of claim 10, wherein calculating the hash value for the user identifier comprises normalizing the function of the user identifier to a value within a normalized range;

wherein the hash values for each of the user identifiers are uniformly distributed within the normalized range.

12. The system of claim 10, wherein the hash value for the user identifier is a function of both the user identifier and a campaign identifier associated with a content distribution campaign.

13. The system of claim 9, wherein the computing system is configured to calculate, for each of the available impressions, a first hash value for the associated user identifier with respect to a first content distribution campaign and a second hash value for the associated user identifier with respect to a second content distribution campaign;

wherein the first hash value and the second hash value are functions of the user identifier and have different values.

14. The system of claim 10, wherein the impression probability threshold is associated with a content distribution campaign;

wherein the computing system is configured to calculate the impression probability threshold as a function of a content distribution budget for the campaign.

15. The system of claim 14, wherein calculating the impression probability threshold comprises:

using content distribution parameters of the campaign to estimate a non-throttled spending rate for the campaign; and

using the content distribution budget and the non-throttled spending rate to determine a proportion of impressions which satisfy the content distribution parameters and on which bids can be placed without exceeding the content distribution budget.

16. The system of claim 10, wherein the computing system selects an available impression for inclusion in the subset of available impressions in response to a determination that the hash value for the user identifier associated with the available impression is less than the impression probability threshold.

17. The system of claim 10, wherein the computing system is configured to classify, for each of the available impressions, the associated user identifier as a throttled user identifier or a non-throttled user identifier with respect to a content distribution campaign based on a result of the comparison;

wherein the computing system is configured to deliver content associated with the campaign to a client device associated with the available impression in response to classifying the user identifier as a non-throttled user identifier.

18. A system for optimizing impression frequency for content presented on a client device, the system comprising:

a computing system configured to receive a notification of an available impression for presenting content on a client device and to identify a user identifier associated with the available impression;

wherein the computing system is configured to map the user identifier to a calculated value within a normalized range and to compare the calculated value with an impression probability threshold, wherein the calculated value is a function of the user identifier;

wherein the computing system is configured to determine whether to bid on the available impression based on a result of the comparison.

19. The system of claim 18, wherein the calculated value is a hash value calculated for the user identifier as a function of the user identifier;

wherein the hash value is uniformly distributed with respect to a plurality of different hash values within the normalized range;

wherein each of the plurality of different hash values is calculated as a function of a different user identifier.

20. The system of claim 18, wherein determining whether to bid on the available impression comprises:

determining to bid on the available impression in response to a determination that the calculated value is less than the impression probability threshold; and

determining to not bid on the available impression in response to a determination that the calculated value is not less than the impression probability threshold.