Abstract:
A server system of an online information system displays advertising items and content items retrieved from storage devices as a stream viewable by a user on a user device. The advertisement items and the content items are ordered in the stream by a ranking score computed for each of the advertisement items and each of the content items. A quality scoring system determines an affinity score between a user and a present content item based on features of the present content item matching user profile parameters associated with the user and identifies post-interaction satisfaction with a prior content item. The quality scoring system determines a quality score based on the affinity score and the post-interaction satisfaction. The quality score is used for ordering items in the stream. The server system transmits a web page including the stream to a user device over a network. In this manner, advertising items and content items compete in a unified marketplace for inclusion in the stream for viewing by the end user.
Abstract:
A system for adjusting reserve price for impressions of non-guaranteed delivery (“NDG”) advertising auctions includes a processor configured to retrieve a reserve price set by a publisher for an impression that is fillable by eligible advertisements to be streamed to users in a display content stream; and to retrieve user engagement information for users that engage the eligible advertisements. A statistical analyzer applies a statistical function to the user engagement information of an identified advertisement of the eligible advertisements, to generate a user engagement statistic for the identified advertisement related to a user engagement level. A reserve price adjuster dynamically adjusts the reserve price for the identified advertisement responsive to a value of the user engagement statistic, where the adjusted reserve price for the identified advertisement is different than the reserve price for at least another of the eligible advertisements based on different user engagement levels for each.
Abstract:
A method for adjusting pricing for advertisements of non-guaranteed delivery (“NDG”) advertising auctions includes retrieving dwell time information for users that engage advertisements streamed to the users in a display content stream. The method aggregates the advertisements into different groups according to display context (such as advertisement category, viewing device, product in which the advertisement is streamed, etc.) and computes short-click ratios of advertisements in each group based on a short-click threshold assigned to the group and the user dwell time information for the group. The method further determines average dwell time by users on advertisements in respective groups. The method adjusts pricing of the advertisements of a group for NGD bidding based on the short-click ratio and average dwell time of the group, to favor groups having higher dwell times and lower short-click ratios. Prices may be dynamically adjusted across different contexts based on user engagement information.
Abstract:
A system can include a processor configured to: receive user session data from a network, identify user session data associated with a creative, and determine user interaction information associated with the creative. The processor may also be configured to determine one or more of a mean, a variance, and a median of a distribution of the user interaction information associated with the creative. Also, the processor can be configured to determine expected user engagement associated with the creative according to one or more of the user interaction information, the mean, the variance and the median. The processor can also be configured to: determine a probability that the expected user engagement will be higher than actual user engagement according to the expected user engagement and determine an expected price associated with the creative according to the probability that the expected user engagement will be higher than actual user engagement.
Abstract:
Methods and apparatuses for delivering advertisements with electronic content provided over a network and, more specifically, to techniques for selecting among advertisements that are competing for a slot associated with electronic content that is to be delivered over a network, are presented herein. Selecting among advertisements that are competing for a slot is based, at least in part, on an estimated latency for each advertisement. The estimated latency of an advertisement is a prediction of what latency will be experienced if the advertisement is served. The estimated latency may be used as one of the parameters for determining which competing advertisement to place in a slot, where advertisements that are associated with low estimated latencies are favored. For example, if all other parameters are equal, a selection mechanism selects advertisement X over advertisement Y, if the estimated latency for advertisement X is less than the estimated latency of advertisement Y.
Abstract:
A server system of an online information system displays advertising items and content items retrieved from storage devices as a stream viewable by a user on a user device. The advertisement items and the content items are ordered in the stream by a ranking score computed for each of the advertisement items and each of the content items. The server system transmits a web page including the stream to a user device over a network. In this manner, advertising items and content items compete in a unified marketplace for inclusion in the stream for viewing by the end user.
Abstract:
A system and method for formulating a bid on an impression for an Internet advertising campaign using market forecast data are provided. The system and method comprise determining a bid policy using an advertiser goal type, an advertiser payment type, and a budget parameter. Historical impression data pertaining to the advertising campaign is sampled using any applicable sampling technique. The sampled data is used to derive forecast data that predicts the future state of the market. The bid policy and the forecast data are used to derive a spend curve, from which an optimal bid is formulated that results in a proper and efficient allocation of the advertiser's budget.
Abstract:
A server system of an online information system displays advertising items and content items retrieved from storage devices as a stream viewable by a user on a user device. The advertisement items and the content items are ordered in the stream by a ranking score computed for each of the advertisement items and each of the content items. A quality scoring system determines an affinity score between a user and a present content item based on features of the present content item matching user profile parameters associated with the user and identifies post-interaction satisfaction with a prior content item. The quality scoring system determines a quality score based on the affinity score and the post-interaction satisfaction. The quality score is used for ordering items in the stream. The server system transmits a web page including the stream to a user device over a network. In this manner, advertising items and content items compete in a unified marketplace for inclusion in the stream for viewing by the end user.
Abstract:
A system for adjusting reserve price for impressions of non-guaranteed delivery (“NDG”) auctions includes a processor to retrieve a publishers' reserve price for an impression that is finable by eligible advertisements (“ads”) streamed to users in a display content stream; and to retrieve dwell time information for users that engage them. A data aggregator aggregates ads into different groups of different display and online campaign contexts. The system computes short-click ratios of ads in each ad group based on short-click threshold and user dwell time information. A statistical analyzer applies a statistical function to the dwell time information of the ads, to generate a dwell time statistic. A reserve price adjuster adjusts pricing of the reserve price of ad groups for bidding in the NGD auction based on the short-click ratio and the dwell time statistic, to favor ad groups having higher dwell times and lower short-click ratios.
Abstract:
A method, system, and computer program product for optimizing bidding over multiple advertising campaigns having a least two campaign types. The optimization is subjected to at least one constraint quantifying a multiple campaign spending limit amount. The method commences by identifying a collection of the multiple advertising campaigns, then evaluating each of the constituent member advertising campaigns to determine its respective optimized spending amount. Then the method calculates (e.g., sums) an aggregate spending amount by aggregating the individual campaign spending amounts. When the aggregate spending amount is greater than the multiple campaign constraint, then the method apportions the multiple campaign spending limit amount to the constituent member advertising campaigns which is in turn used to determine a reduced spending limit. The time period under which the spending is optimized can be any time period suited for forming bids to bid on inventory of impressions into which advertisements can be placed.