GENERATION OF AN ADVERTISEMENT BID-REACH LANDSCAPE

• US 20150332317A1
• Filed: 05/15/2014
• Published: 11/19/2015
• Est. Priority Date: 05/15/2014
• Status: Abandoned Application

• Current Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Original Assignee: Meta Platforms, Inc. (f/k/a Facebook, Inc.)
• Inventors: Fu, Wenjie, Shay, Eitan, Sim, Richard Bill, Yang, Jun, Cui, Xinyi, Yu, Haomin, Jin, Ou
• Application Number:
  US14/279,149
• Publication Number:
  US 20150332317A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0246 Traffic
• CPC Class Codes: G06Q 30/0247 Calculate past, present or future revenues
• CPC Class Codes: G06Q 30/0275 Auctions
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

An advertising system receives from an advertiser at a social networking system an advertisement request, the advertisement request comprising advertisement content and a specification of a target audience for the advertisement content. The advertising system defines a plurality of bid values for the advertisement request. For each of the plurality of bid values, the advertisement system estimates a corresponding value of advertisement reach for the target audience, for example, by estimating a number of users of the target audience for each of whom the given bid value is expected to have resulted in at least one successful impression. The advertiser is provided a visual representation of a bid-reach landscape representing the estimated plurality of advertisement reach values as a function of the plurality of bid values. The advertising system provides, to the advertiser, one or more recommendations for bid values for which corresponding return-on-investment metrics exceed a specified threshold.

Claims

1. A method comprising:

receiving from an advertiser at a social networking system an advertisement request, the advertisement request comprising advertisement content and a specification of a target audience for the advertisement content;

defining a plurality of bid values for the advertisement request;

for each of the plurality of bid values, estimating a corresponding value of advertisement reach for the target audience; and

providing to the advertiser, a visual representation of a bid-reach landscape representing the estimated plurality of advertisement reach values as a function of the plurality of bid values.

2. The method of claim 1, wherein estimating a corresponding value of advertisement reach for the target audience comprises, for each given bid value of the plurality of bid values:

estimating a number of users of the target audience for each of whom the given bid value is expected to have resulted in at least one successful impression in a corresponding bid auction in a recent impression history.

3. The method of claim 2, wherein estimating a number of users of the target audience for whom the given bid value is expected to have resulted in at least one successful impression in a corresponding bid auction comprises:

estimating a number of users of the target audience for each of whom the given bid value is expected to have been greater than a context-adjusted cost associated with at least one impression in the recent impression history, resulting in the at least one successful impression.

4. The method of claim 2, further comprising:

defining a plurality of budget values for the advertisement request resulting in a plurality of bid-budget value pairs; and

for each resulting bid-budget value pair, adjusting a corresponding reach value for the target audience to a maximum number of users for each of whom the given bid value is expected to have resulted in at least one successful impression in a bid auction and for whom a total reach price is expected to have been lower than the corresponding budget value.

5. The method of claim 1, further comprising:

defining a return-on-investment metric for the bid landscape, the return-on-investment metric representing incremental increases in reach values for corresponding increases in bid values.

6. The method of claim 5, further comprising:

receiving a selection, from the advertiser, of a specified bid value of the plurality of defined bid values;

evaluating an efficacy of the specified bid value based on the return-on-investment metric and the specified bid value; and

providing to the advertiser one or more suggestions for modifying the specified bid value based on the evaluated efficacy of the specified bid value.

7. The method of claim 5, further comprising:

providing, to the advertiser, one or more recommendations for bid values for which corresponding return-on-investment metrics exceed a specified threshold.

8. The method of claim 1, wherein for each given bid value of the plurality of bid values, estimating corresponding values of advertisement reach for the target audience comprises:

sampling a subset of users from the target audience to determine a reach count for each user in the subset, a particular reach count for a particular user in the subset indicating whether the advertisement content would have reached the particular user based on the given bid value;

estimating an aggregate reach of the advertisement content for the subset of users as an aggregation of reach counts for the users in the subset; and

estimating a total reach of the advertisement content for the target audience for the given bid value by extrapolating the aggregate reach for the subset of users to the target audience.

9. The method of claim 8, wherein determining a reach count for each given user in the subset comprises:

reviewing an advertisement impression history for the given user based on a recency criterion to retrieve costs associated correspondingly with a plurality of impressions in the reviewed impression history;

computing normalized measures of the retrieved costs associated with each of the plurality of impressions in the reviewed impression history;

comparing the bid amount in the advertisement request to each of the computed normalized measures of the retrieved costs, in order to determine a reach count for the given user; and

recording a positive reach count for the given user if the bid amount in the advertisement request is greater than at least one of the computed normalized measures of the retrieved costs, and a zero reach count for the given user if the bid amount in the advertisement request is lower than each of the computed normalized measures of the retrieved costs.

10. The method of claim 9, wherein computing normalized measures of the retrieved costs associated with each of the plurality of impressions in the reviewed impression history comprises:

scaling the retrieved costs associated with each of the plurality of impressions in the reviewed impression history for the given user by a corresponding scaling constant indicative of;

one or more attributes of the given user, a given presentation context for presenting the advertisement content to the given user for a given impression, or a combination thereof.

11. The method of claim 12, wherein the corresponding scaling constant is determined for the given user for the given impression by:

presenting a set of advertisements to the given user under the given presentation context;

for each given presented advertisement of the set of advertisements;

computing a user-context dependent expected click through rate for the given presented advertisement based on the given presentation context and the given user,

retrieving a user-context independent expected click through rate for the given presented advertisement, and

computing a scaling constant for the given presented advertisement by normalizing the user-context dependent expected click through rate by the user-context independent expected click through rate; and

computing the corresponding scaling constant as a median of computed scaling constants for the set of advertisements.

12. The method of claim 1, further comprising:

for each given bid value of the plurality of bid values, estimating corresponding impression counts for the target audience; and

providing to the advertiser, a visual representation of a bid-impression landscape representing the estimated plurality of impression counts as a function of the plurality of bid values.

13. The method of claim 12, further comprising:

for each given bid value of the plurality of bid values, estimating corresponding conversion measures for the target audience based on the corresponding estimated impression counts and an expected conversion rate; and

providing to the advertiser, a visual representation of a bid-outcome landscape representing the estimated plurality of conversion measures as a function of the plurality of bid values.

14. A computer system comprising:

a processor;

memory coupled to the processor, the memory having encoded thereon instructions that, when executed by the processor, cause the processor to;

receive from an advertiser at a social networking system an advertisement request, the advertisement request comprising advertisement content and a specification of a target audience for the advertisement content;

define a plurality of bid values for the advertisement request;

for each of the plurality of bid values, estimate a corresponding value of advertisement reach for the target audience; and

provide to the advertiser, a visual representation of a bid-reach landscape representing the estimated plurality of advertisement reach values as a function of the plurality of bid values.

15. The computer system of claim 14, wherein the instructions that cause the processor to estimate a corresponding value of advertisement reach for the target audience comprises, for each given bid value of the plurality of bid values, cause the processor to:

estimate a number of users of the target audience for each of whom the given bid value is expected to have resulted in at least one successful impression in a corresponding bid auction in a recent impression history.

16. The computer system of claim 15, wherein the instructions that cause the processor to estimate a number of users of the target audience for whom the given bid value is expected to have resulted in at least one successful impression in a corresponding bid auction, cause the processor to:

estimate a number of users of the target audience for each of whom the given bid value is expected to have been greater than a context-adjusted cost associated with at least one impression in the recent impression history, resulting in the at least one successful impression.

17. The computer system of claim 15, further comprising instructions that cause the processor to:

define a plurality of budget values for the advertisement request resulting in a plurality of bid-budget value pairs; and

for each resulting bid-budget value pair, adjust a corresponding reach value for the target audience to a maximum number of users for each of whom the given bid value is expected to have resulted in at least one successful impression in a bid auction and for whom a total reach price is expected to have been lower than the corresponding budget value.

18. A computer program product comprising a non-transitory computer-readable storage medium including instructions that, when executed by a processor, cause the processor to:

receive from an advertiser at a social networking system an advertisement request, the advertisement request comprising advertisement content and a specification of a target audience for the advertisement content;

define a plurality of bid values for the advertisement request;

for each of the plurality of bid values, estimate a corresponding value of advertisement reach for the target audience; and

provide to the advertiser, a visual representation of a bid-reach landscape representing the estimated plurality of advertisement reach values as a function of the plurality of bid values.

19. The computer program product of claim 18, wherein the instructions that cause the processor to estimate a corresponding value of advertisement reach for the target audience comprises, for each given bid value of the plurality of bid values, cause the processor to:

estimate a number of users of the target audience for each of whom the given bid value is expected to have resulted in at least one successful impression in a corresponding bid auction in a recent impression history.

20. The computer program product of claim 19, wherein the instructions that cause the processor to estimate a number of users of the target audience for whom the given bid value is expected to have resulted in at least one successful impression in a corresponding bid auction, cause the processor to:

estimate a number of users of the target audience for each of whom the given bid value is expected to have been greater than a context-adjusted cost associated with at least one impression in the recent impression history, resulting in the at least one successful impression.