Abstract: A method is provided for dynamically controlling the pace of online impression delivery among multiple geographic regions in a real-time bidding (RTB) system. Target geographic locations associated with a campaign are identified, and target geographic regions associated with each target geographic location are identified. A pacing score is determined for each target geographic region. The bidding system makes bidding decisions regarding RTB bid requests received from an RTB exchange based at least on whether the respective bid request is associated with a target geographic region, and if so, the pacing score for that target geographic region. A campaign-related impression is delivered for each winning bid, and impression delivery data is stored for each target geographic region. The bidding system automatically adjusts the pacing score for each target geographic region based on the stored impression delivery data for that geographic region, and uses the adjusted pacing scores for subsequent bidding decisions.

Abstract: A method for automated control of bid pricing for bidding on online placements in an automated real-time online auction system during the loading or rendering of network-based digital content. Historical bid result data regarding a particular placement is collected by a bidding system, which segments the bid result data into multiple categories and generates multiple pricing curves for the particular placement based on the segmented bid result data. The bidding system then uses the multiple pricing curves for making bidding decisions in real-time. The bidding system receives a series of bid requests, each identifying a placement in digital content being loaded or rendered. For each received bid request, the bidding system, in real-time, identifies segmenting characteristic(s) associated with the bid request, and performs a bidding analysis—including whether to submit a bid and determining a bid price—based on the identified segmenting characteristic(s) associated with the bid request.

Abstract: A method and system for recommending advertisement placements based on scoring is disclosed. According to one embodiment, a computer-implemented method comprises receiving a real-time bidding (RTB) request for placing an online advertisement campaign. For each of a plurality of advertisement placements, a performance score is determined based on an estimated feedback parameter. The estimated feedback parameter is calculated from observed performance of the online advertisement campaign and similarity measures of other online advertisement campaigns. A first advertisement placement having a higher performance score is given more weight than a second advertisement placement having a lower performance score. A set of advertisement placements having their performance scores equal to or greater than the target rating is selected from the plurality of advertisement placements and provided for advertisement placements.

Abstract: A system and method for advertisement impression volume estimation is herein disclosed. According to one embodiment, the computer-implemented method includes identifying a plurality of advertisement placements for an advertisement campaign based on a campaign parameter and a specified performance level for a past advertisement campaign, determining a first plurality of advertisement impressions from the plurality of advertisement placements based on a target geographic region, and estimating a second plurality of advertisement impressions from the first plurality of advertisement impressions based on a discount rate.

Abstract: A method for controlling a purchasing pace in a real-time bidding environment is provided. A pacing parameter is dynamically adjusted using a multi-loop control algorithm including an outer control loop and an inner control loop, wherein the outer control loop outputs a control parameter, and the inner control loop uses this control parameter as an input and outputs a current value of the pacing parameter, which is adjusted over time by the multi-loop control algorithm. A series of bid requests generated by a real-time bidding exchange are received, each identifying a respective available ad placement in a respective webpage being loaded. For each received bid request, a decision is made in real-time, during the loading of the respective webpage, whether to submit a bid to purchase the respective ad placement based at least on the current value of the dynamically adjusted pacing parameter.

Abstract: A method and system for pricing advertisement placements online in a real-time bidding (RTB) environment is disclosed. According to one embodiment, a computer-implemented method includes receiving a plurality of responses from a plurality of real-time bidding (RTB) requests for an advertisement placement and determining a first data set from the plurality of responses, where the first data set includes prices paid for winning the advertisement placement. The computer-implemented method further includes determining a second data set from the plurality of responses, where the second data set includes losing bid prices, and estimating a price distribution curve based on one or more of the first data set and the second data set.

Abstract: A method and system for controlling real-time bidding for online advertisements is disclosed. According to one embodiment, a computer-implemented method comprises receiving a real-time bidding (RTB) request from a bidder. The RTB request contains a campaign target. An online advertisement campaign corresponding to the RTB request is placed. Campaign performance data is received from an impression server and/or an event server. The campaign performance data is compared to the campaign target. Based on the result of comparison, it is determined whether to enable or disable the online advertisement campaign.

Abstract: A method and system for controlling real-time bidding for online advertisements is disclosed. According to one embodiment, a computer-implemented method comprises communicating with a bidder and an impression server and an event tracking server. The bidder receives a real-time bidding (RTB) request containing an available impression from an exchange and places a bid corresponding to the RTB request. The impression server receives impression requests from a browser and responds to the impression requests from the browser. The event tracking server receives event requests from the browser and responds to event requests from the browser. Campaign performance data is retrieved from one or more of the impression server and the event tracking server and compared to the campaign target. The bidder is notified whether to bid for online advertisement impressions based on the campaign performance data.

Abstract: A computer-implemented method for managing purchasing of online advertisements in a real-time bidding system is provided. A setpoint profile defining one or more changes in a setpoint value over time is accessed, wherein the setpoint value indicates a target number of advertisement purchases in a particular time period. A controller executes a control loop feedback algorithm intended to produce actual advertisement purchase results that track the setpoint profile over time. The actual advertisement purchase results may experience time lags when encountering changes in the setpoint value due to the operation of the control loop feedback algorithm. Thus, the method further includes executing a profile modification algorithm to modify the setpoint profile to account for such time lags associated with the actual advertisement purchase results.

Abstract: A computer-implemented method includes receiving a series of bid requests from a real-time bidding exchange, each corresponding to an available advertisement placement, determining whether to bid on each bid request based on a current value of a pacing threshold, and dynamically adjusting the value of the pacing threshold over time using a control loop feedback algorithm, such as a PID controller, a PI controller, or a PD controller, for example. The method may also include determining a score for each received bid request that represents an attractiveness of the advertisement placement associated with that bid request for a particular advertising campaign, and determining whether to bid on that bid request based at least on the determined bid request score and the current value of the pacing threshold. The control loop feedback algorithm may be designed to produce actual advertisement purchase results that track a defined setpoint profile over time.

Abstract: A method and system for optimizing real-time bidding on online advertisement placements is disclosed. According to one embodiment, a computer-implemented method comprises receiving a real-time bidding (RTB) request from a RTB partner who is selling an impression on behalf of a publisher. Several probability scores are predetermined based on various criterion. During the processing of a real-time bid request, a combined probability score and threshold are calculated based on these probability scores. The decision to bid on and price to bid for the impression is determined by the RTB system. Campaign targets are based on the combined probability score. A RTB bid response indicating the selected campaign targets and the bid prices are returned to the RTB partner.

Abstract: A system and method for controlled purchasing of online advertisements in a real time bidding environment is herein disclosed. According to one embodiment, the computer-implemented method includes receiving a real-time bidding request for an online advertisement campaign and determining a score of the real-time bidding request. The score elicits desirability for the online advertisement campaign. The computer-implemented method further includes determining a pacing threshold for the online advertisement campaign and bidding on the real-time bidding request based on the score of the real-time bidding request and the pacing threshold. A bidding pace of the online advertisement campaign is monitored based on a number of impressions won for a given time period, and the pacing threshold is dynamically adjusted based on the bidding pace.

Abstract: A system and method for combining past user events with real-time user events to respond to advertising opportunities is disclosed. According to one embodiment, a computer-implemented method includes receiving a first plurality of user events that occurred within a first prior time period, receiving a second plurality of user events that has occurred within seconds of real-time, and providing a plurality of desirable user events for consideration of a real-time bidding request based on processing the first plurality of user events and the second plurality of user events.

Abstract: A system and method for generating a customized advertisement creative is herein disclosed. According to one embodiment, a computer-implemented method includes receiving a uniform resource locator of a web page, detecting a plurality of assets based on a web document that describes the web page specified by the uniform resource locator, where assets of the plurality of assets are of a common asset type, ranking the assets, providing layout template settings based on a suggested asset from the ranked assets, receiving configured layout template settings, and providing a creative based on the configured layout template settings.

Abstract: A system for handling multiple simultaneous campaigns that improves advertisement performance through shape based targeting and real-time impression acquisition is disclosed. According to one embodiment, a computer-implemented method comprises receiving a bid request, creating a possible advertisement set based on the bid request, filtering the possible advertisement set to produce a reduced advertisement set, creating one or more tradezones. Creating a tradezone comprises clustering data sets according to one or more of offline data, online data, and geographic distribution of a plurality of IP addresses to form custom shapes, and mapping the custom shapes to the plurality of IP addresses. Remaining advertisements are targeted in the reduced advertisement set, wherein remaining advertisements are targeted based on a selected tradezone, and wherein the selected tradezone is selected based upon a set of parameters representative of a desired audience.

Abstract: A system for improving shape-based targeting by using interest level data is disclosed. According to one embodiment, a computer-implemented method comprises creating one or more trade zones, wherein creating a trade zone comprises grouping a set of parameters to deliver custom shapes, clustering the custom shapes according to offline data and geographic distribution of IP addresses, and mapping clusters of the custom shapes to IP addresses. Data indicating consumption of a content source is received, the content source having a plurality of tokens. The plurality of tokens is organized according to the one or more trade zones, wherein the one or more trade zones consume the tokens at a calculated rate and the calculated rate is analyzed to determine an interest associated with each trade zone. Targeting is based on a selected trade zone, wherein the selected trade zone is selected based upon a desired interest representative of a desired audience.

Abstract: A method and system for audience targeting is disclosed. According to one embodiment, a computer-implemented method comprises logging content consumed by a first group of users. The content is categorized into a set of topics. The set of topics are mapped to a plurality of users in a trade zone. Based on profile matching and according to a topic of an advertisement campaign, a second group of users are identified from the plurality of users.

Abstract: A system for improving shape-based targeting by using interest level data is disclosed. According to one embodiment, a computer-implemented method includes creating one or more trade zones, wherein creating a trade zone includes grouping a set of parameters to deliver custom shapes, clustering the custom shapes according to offline data and geographic distribution of IP addresses, and mapping clusters of the custom shapes to IP addresses. Data indicating consumption of a content source is received by one or more trade zones at a calculated rate and the calculated rate is analyzed to determine an interest associated with each trade zone. Targeting is based on a selected trade zone, wherein the selected trade zone is selected based upon a desired interest representative of a desired audience. A targeting request is transmitted including instructions or information associated with a target action, and the target action is performed.

Abstract: A system for handling multiple simultaneous campaigns that improves advertisement performance through shape based targeting and real-time impression acquisition is disclosed. According to one embodiment, a computer-implemented method comprises receiving a bid request, creating a possible advertisement set based on the bid request, filtering the possible advertisement set to produce a reduced advertisement set, creating one or more tradezones. Creating a tradezone comprises clustering data sets according to one or more of offline data, online data, and geographic distribution of a plurality of IP addresses to form custom shapes, and mapping the custom shapes to the plurality of IP addresses. Remaining advertisements are targeted in the reduced advertisement set, wherein remaining advertisements are targeted based on a selected tradezone, and wherein the selected tradezone is selected based upon a set of parameters representative of a desired audience.

Abstract: A method and system for controlling real-time bidding for online advertisements is disclosed. According to one embodiment, a computer-implemented method comprises receiving a real-time bidding (RTB) request from a bidder. The RTB request contains a campaign target. An online advertisement campaign corresponding to the RTB request is placed. Campaign performance data is received from an impression server and/or an event server. The campaign performance data is compared to the campaign target. Based on the result of comparison, it is determined whether to enable or disable the online advertisement campaign.