PREDICTION OF ADVERTISEMENT REACH BASED ON ADVERTISER SPECIFIED BID AND/OR BUDGET AMOUNTS

• US 20150332310A1
• 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: Cui, Xinyi, Fu, Wenjie, Yu, Haomin, Jin, Ou, Shay, Eitan, Sim, Richard Bill, Yang, Jun
• Application Number:
  US14/279,131
• Publication Number:
  US 20150332310A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0206 Price or cost determination based on market factors
• CPC Class Codes: G06Q 30/0242 Determining effectiveness of advertisements
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0246 Traffic
• CPC Class Codes: G06Q 30/0275 Auctions
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 50/01 Social networking

Abstract

An advertising system predicts advertisement reach for a received advertisement request based on an advertiser-specified bid amount and a specification of a target audience. The system samples the target audience, and for each sampled user of the target audience, accesses a recent impression history to obtain costs or bids associated with recent advertisement impressions. The system compares the advertiser-specified bid amount in the received advertisement request to costs or bid values associated with successful advertisement impressions, for each sampled user, in order to determine whether the received advertisement request would have won a bid auction for each given sampled user to successfully reach each given sampled user. An estimated aggregate reach for the sampled users is computed and extrapolated to the targeted user population to estimate a total reach of the advertisement content for the target audience.

Claims

1. A method comprising:

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

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;

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

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

2. The method of claim 1, 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.

3. The method of claim 2, 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.

4. The method of claim 3, 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.

5. The method of claim 1, wherein the total reach of the advertisement content for the target audience is estimated by extrapolating the estimated aggregate reach of the advertisement content for the subset of users, to the target audience.

6. The method of claim 1, further comprising:

computing, for the subset of users, a number of impressions for the advertisement content by;

reviewing an advertisement impression history for each sampled 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 an impression count for each impression in the reviewed impression history; and

recording a positive impression count for a given impression if the bid amount in the advertisement request is greater than a computed normalized measure of the retrieved cost for the given impression, and a zero impression count for the given impression if the bid amount in the advertisement request is lower than the computed normalized measure of the retrieved cost for the given impression; and

estimating a number of impressions for the advertisement content for the subset of users as an aggregation of impression counts for the impressions in the impression history.

7. The method of claim 6, further comprising:

estimating a total number of impressions for the target audience by extrapolating the estimated number of impressions for the subset of users to the target population.

8. The method of claim 7, further comprising:

computing, for the target audience, an expected conversion outcome based on the estimated total number of impressions for the target audience and an empirical conversion rate for the advertisement content.

9. The method of claim 8, wherein the empirical conversion rate for the advertisement content is determined based on a likelihood of one or more users of the target audience performing a conversion event after being presented with the advertisement content.

10. The method of claim 8, wherein the empirical conversion rate for the target audience is extrapolated from a statistical measure of conversion outcomes for the subset of users.

11. The method of claim 8, wherein the empirical conversion rate is determined based on previously recorded conversion outcomes for the advertisement content.

12. The method of claim 11, wherein the previously recorded conversion outcomes are adjusted based on conversion types for the recorded conversion outcomes to adjust the conversion outcomes for degrees of conversion interactions performed by social networking system users when presented with the advertisement content.

13. The method of claim 8, wherein the empirical conversion rate for the target audience is determined based on conversion outcomes for one or more advertisements having content that shares one or more attributes with the advertisement content in the received advertisement request.

14. The method of claim 13, wherein the one or more shared attributes correspond to a common advertisement group, a common advertisement campaign, a common advertiser, or any combination thereof.

15. The method of claim 7, further comprising:

computing, for the target audience, an expected number of clicks based on the estimated total number of impressions for the target audience and an empirical click through rate for the advertisement content.

16. The method of claim 1, wherein:

the advertisement request further comprises indicated specification of a budget that limits an amount of compensation the advertiser provides to the social networking system for presenting the advertisement content to users of the social networking system; and

the total reach of the advertisement content for the target audience is adjusted based on the budget specified in the advertisement request to limit a total price charged to the advertiser for the adjusted total reach to the advertiser-specified budget.

17. The method of claim 1, wherein:

the subset of users from the target audience are sampled based on a predetermined sampling criterion, the predetermined sampling criterion comprising a predetermined sampling rate and a predetermined threshold; and

the total reach of the advertisement content for the target audience is estimated based on the estimated aggregate reach of the advertisement content for the subset of users and the predetermined sampling criterion by;

responsive to the estimated aggregate reach for the subset of users exceeding the predetermined threshold, extrapolating a portion of the estimated aggregate reach for the subset of users that exceeds the predetermined threshold, using the predetermined sampling rate, to obtain the total reach of the advertisement content for the target audience.

18. 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, a bid amount for presenting the advertisement content to users of the social networking system, and a specification of a target audience for the advertisement content;

sample 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;

estimate 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

estimate a total reach of the advertisement content for the target audience by extrapolating the aggregate reach for the subset of users to the target audience.

19. 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, a bid amount for presenting the advertisement content to users of the social networking system, and a specification of a target audience for the advertisement content;

sample 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;

estimate 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

estimate a total reach of the advertisement content for the target audience by extrapolating the aggregate reach for the subset of users to the target audience.