Abstract: A system and method for placing an advertisement in a digital environment based upon a user's choice, subject to certain predetermined parameters, is disclosed. Through the method, a user is assigned a rating based upon, for example, his performance in a game. A list of advertisements which correspond to that rating is displayed to the user, who may then select a desired advertisement from the list. The selected advertisement is then displayed in the digital environment. Reports may be generated based upon the advertisements selected and the number of selections and/or impressions (e.g., uses or viewings) by the user, which may be sent to advertisers.

Abstract: A system for delivering advertisement units that interact with each other on a webpage is disclosed. The system includes a web browser, a web server, and an advertisement server. The web browser is configured to generate a request for a webpage. The web server is communicatively connected to the web browser and is configured to receive the request for a webpage from the web browser and send the requested webpage to the browser in response to the request. The webpage includes an ad unit request script that is configured to direct the web browser to generate a request for an advertisement unit. The advertisement server is communicatively connected to the web browser and the web server. The advertisement server is configured to receive advertisement unit requests and send a first ad unit and a second ad unit to the web browser in response to those requests. The first and second ad units are rendered by the web browser onto the webpage.

Abstract: A campaign is received, at a micro-segmentation system, from an offer provider. The micro-segmentation system is a third-party system. The campaign indicates a set of target attributes and one or more offers corresponding to the set of target attributes. A set of user attributes pertaining to each of the plurality of users is received at the micro-segmentation system. The set of attributes is defined by an attribute knowledge structure. Permission is received at the micro-segmentation system from each of the plurality of users to receive an offer from the micro-segmentation system. Data associated with the micro-segment classification is provided from the micro-segmentation system without user information to the offer provider.

Abstract: A system and method are provided for initiating a text message communication session between a merchant and a consumer. An advertisement may be transmitted to a mobile device associated with the consumer, a signal may be received from the mobile device indicating that the consumer has activated a link associated with the advertisement, and the signal may also include contextual information associated with the consumer's use of the mobile device. A text message communication session may be initiated between the mobile device and a merchant representative; whereby a text message alert may be provided to the merchant representative, comprising the contextual information associated with the consumer.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting thumbnail images to display with text advertisements. In one aspect, a method includes identifying landing page non-textual content items from a landing page to which the textual content item links and which a user device requests when the textual content item is selected at the user device; for each landing page non-textual content item, determining a relevance measure that measures the relevance of the landing page non-textual content item to the content of the landing page; selecting one or more of the landing page non-textual content items for display with the textual content item based on the relevance measures of the landing page non-textual content items; and storing, in a data storage system, data associating the selected landing page non-textual contents with the textual content items.

Abstract: In accordance with the teachings described herein, systems and methods are provided for optimizing distribution of advertisement information. In one example, call tracking data may be generated from a plurality of telephone calls made to a business entity, where the call tracking data includes geographical information to identify locations from which the plurality of telephone calls originated. A call distribution may be determined from the call tracking data, where the call distribution groups the call tracking data based at least in part on distances between the business entity and the locations from which the plurality of telephone calls originated. A probability density function may be generated from the call distribution and used in the generation of the advertisement distribution plan.

Abstract: Systems and methods for placing ads in a block on a webpage are disclosed. Generally, two ranking models are trained using a first and second ads data set. The first model predicts a first click probability for each ad in the first ads data and rank the ads based on the eCPM. The second model is trained using the second ads data set comprising a subset of the first ads data set and interaction features related to ad position in the block. The second model predicts a second click probability for each ad in the second ads data set. An overall expected revenue for each arrangement of ads in the second ads data set is then calculated. The computer system selects the arrangement with maximum computed overall expected revenue and places the ads in the block on the webpage according to the selected arrangement.

Abstract: A method of delivering targeted on-line advertising to an end user of a computer network system comprises creating an advertisement campaign having a plurality of dimensions associated therewith, obtaining end user data based upon engagement of the end user with the network system, profiling advertisement content available on the network system to identify specific items of advertisement content that are compatible with the advertising campaign, for each item of compatible advertisement content, utilizing the end user data and metrics associated with the plurality of dimensions associated with the advertisement campaign to develop an effectiveness measurement, and utilizing the effectiveness measurements to select at least one item of compatible advertisement content for display to the end user.

Abstract: Systems and methods for allocating and providing advertisements in response to impression events (e.g., a request for a placement of an advertisement) corresponding to forecasted impressions (e.g., a forecast of a request for a placement of an advertisement). The advertisements are allocated according to solution data that includes two disjoint solution sets, with each solution set identifying an advertisement that can be allocated to a forecasted impression.

Abstract: Display space on web page may be allocated by bids. In one embodiment, the display space system receives bids indicating a bid amount and an advertisement. When providing a web page with the display space, the display space system selects a bid. The display space system adds the advertisement of the selected bid to the web page. The bid may specify web pages on which the advertisement may be placed, the users to whom the advertisement may be presented, and time when the advertisement may be placed. The bid amount may be in an established currency or in advertising points. Activities for which advertising points may be awarded may include listing an auction, auction bidding, or purchasing of an item. When a user advertisement is placed, the display space system reduces user advertising points. The display space system may also place bids for display space on behalf of the user.

Abstract: In some embodiments, there is provided a technique for detecting a consumer's skipping habits at a given time and determining the consumer's current preferences based at least in part on those skipping habits. Skipping habits are determined by detecting which content is skipped (or not skipped) during presentation of content. Skipping habits, indicating trends in the consumer's consuming or skipping of content, that are detected during presentation of content may be used to determine a consumer's current preferences. Selection of content for presentation may be based on current preferences of the consumer. In this way, a consumer's interactions with the content, including the consumer's skipping habits, can be used to alter a selection of content to be presented to the consumer.

Abstract: Systems (490), methods (100, 200), and computer-readable and executable instructions (324, 424) are provided for estimating costs of behavioral targeting. Estimating costs of behavioral targeting can include scoring a topic with a behavioral targeting model (101, 201). Estimating costs of behavioral targeting can also include obtaining a plurality of data items including geographic location information (102, 202). Estimating costs of behavioral targeting can also include detecting (104, 204) and scoring (209) a sentiment from filtered data items regarding a topic within a region (104, 204). Estimating costs of behavioral targeting can include computing a penalty score for the topic in the region in response to the scored sentiment exceeding a threshold (213), (106, 206). Estimating costs of behavioral targeting can include adjusting the topic score in the region according to the penalty score (108, 208).

Abstract: Techniques are described herein for combining segments of users into super-segments. The interests of the segments in online ad campaigns in which they participate are compared to determine subsets of the segments whose interests are correlated to an extent that exceeds a designated threshold. The segments in each subset are combined to provide a respective super-segment. Each online ad campaign corresponds to a specified category, such as telecommunications, auto, finance, retail, entertainment, travel, etc. For each super-segment, the cumulative interest of the segments therein for each category are determined The cumulative interests for each super-segment are used to determine which super-segment(s) are to be targeted for receiving a specified online advertisement.

Abstract: Promotion systems and related methods are disclosed. In one embodiment, a system includes: at least one computing device configured to manage a promotion for an organization by performing actions including: providing the promotion to a user, the promotion including: an enticement to purchase a product or a service at a local location of the organization; and a unique identifier for the user and the promotion; tracking whether the user utilizes the promotion to purchase the product or the service at the local location; and providing data about the purchase of the product or the service to the organization in response to the user executing the purchase, the data about the purchase of the product including data about the promotion, data about the user, and data about the local location.

Abstract: A contextual advertising system depends on embedded decision-influence algorithms to parse the keywords in web-user searches to identify the public search-engine networks best able to respond with the most relevant advertisement results. Marketing managers control which kind of advertisements get automatically selected by planting product/service, price, place and promotion (4P) keywords which correlate to each of the four traditional Marketing Mix categories. Language-independent, proximity pattern matching algorithms are used to increase matching accuracy and customer click-through-rates (CTR) and their ultimate purchase decisions. Each 4P Marketing Mix contextual smart-advertisement can be independently displayed in full, or linked to an existing online advertisement to enhance match accuracy and the CTR.

Abstract: The present invention provided techniques that may be used, for example, in online advertising. Techniques are provided that include centralized and aggregated advertisement performance data tracking, which can be used in advertisement selection. Advertisement performance data may be obtained by a central server, such as from many advertisement servers. The central server may aggregate the performance data, and may generate a performance snapshot spanning many advertisements. The snapshot may be used in generating a performance prediction model, which may in turn be used in advertisement selection, or monitoring or tracking associated with advertising. Elements or actions, such as obtaining of performance data, aggregation, generation of the snapshot, and generation of the model, may include frequent or real time updating of such elements or actions.

Abstract: A method, system, and computer program product for using advertising campaign allocation optimization results to calculate bids. The method commences by receiving a candidate impression opportunity corresponding to an advertising campaign that has both branding objectives and performance-based objectives. Contracts that can be satisfied by serving the candidate impression opportunity use advertising campaign allocation optimization results to determine a set of matching contracts. Given the matching contracts, the method continues to calculate bids for those matching contracts, then selects a target contract from among the matching contracts. The method then bids on the candidate impression opportunity using the calculated bid of the selected target contract. The method optimizes for overall campaign performance even when the campaign includes both branding campaign objectives and performance-based campaign objectives.

Abstract: A method and system is disclosed for creating additional advertising space by sensing the position of an element on a web page or other client viewer, and upon interaction of a user with that element positioning the appearance of additional web page elements not limited by the boundary of the initial element.

Abstract: The efficient allocation of advertisements, also known as creatives, on one or more web sites is provided for while ensuring that guarantees to advertisers are honored. In one embodiment, a linear program solver allocates creatives to advertising slots according to an optimizing function designed to maximize revenue for the site. The linear program solver takes as input a set of creatives, creative performance data, constraints, and slot identifiers. The output of the linear program solver is an optimized schedule not violative of any of the input constraints.

Abstract: A system and method is provided for recommending a grammar for a message campaign used by a message optimization system. A user specifies parameters for a new campaign, from which a set of statistical design budgets is calculated. The user selects a grammar structure, recommended based on the statistical design budgets, for the campaign. The n-most relevant past campaigns are identified. Semantic tags, associated with each previously used value from the n-most relevant past campaigns and each of a plurality of untested values, are identified and ranked based on past performance. The previously used values are ordered by ranked tag group and then within each tag group, while the untested values are ordered by ranked tag group and then randomly within the tag group. Recommended values are selected from the ranked list of previously used values and untested values depending on the degree of exploration/conservatism indicated by the user.

Abstract: Apparatus, methods, etc. for mood-based searching and/or advertising. Some methods comprise receiving a mood-based search request including the requestor's mood. The requestor mood is limited to a predetermined mood set. A database is searched for activities subjectively suitable for the requestor mood. Such methods also comprise outputting the suitable activities. Some methods comprise receiving feedback regarding the activity ambience. If desired, some methods comprise adjusting an initial activity ambience responsive thereto. Moreover, some methods comprise adjusting variables used to derive the initial ambience markings. Furthermore methods comprise targeting advertising based on a path associated with the activities. Furthermore, some methods comprise limiting the targeted advertising to activities suitable for the requestor mood (which can comprise multiple moods and/or a mood recipe).

Abstract: Methods, systems, and apparatus, including computer programs encoded on computer storage media, for companion ad auctions. One of the methods includes conducting an online auction that allows bidders to bid on companioned advertisement slots on a web page. The method also includes determining a winning bidder for each of the companioned advertisement slots on the web page. The method also includes determining a price that each winning bidder pays for their respective advertisement slot or slots.

Abstract: A “General Click Model” (GCM) is constructed using a Bayesian network that is inherently capable of modeling “tail queries” by building the model on multiple attribute values that are shared across queries. More specifically, the GCM learns and predicts user click behavior towards URLs displayed on a query results page returned by a search engine. Unlike conventional click modeling approaches that learn models based on individual queries, the GCM learns click models from multiple attributes, with the influence of different attribute values being measured by Bayesian inference. This provides an advantage in learning that enables the GCM to achieve improved generalization and results, especially for tail queries, than conventional click models. In addition, most conventional click models consider only position and the identity of URLs when learning the model. In contrast, the GCM considers more session-specific attributes in making a final prediction for anticipated or expected user click behaviors.

Abstract: Suppliers of goods and/or services subject to shifts in capacity utilization design and implement marketing campaigns around utilization forecasts, targeting marketing expenditures on periods of excess capacity rather than periods without excess capacity, and in some embodiments also to alter variables such as pricing, consumer targeting, or even the intensity of the campaign itself on a dynamic basis in response to changing market conditions.

Abstract: Method for automatically monitoring and verifying advertising content during a campaign, delivered over a data network. Accordingly, one or more advertisers submit, via a user interface, a list (that may be generated manually or by the mapping crawlers) of sites or of sections per site, on which the advertising content should be placed according to a desired insertion order (the insertion order information may modified at any time point). In addition, one or more mapping crawlers are activated to visit these sites and locate pages with advertisements that belong to required sections, pages that do not belong to the required sections or pages with high probability for incidents. A list of pages to visit per every site is generated and autonomous or Plug-in visual crawlers are allowed to visit the list of pages, according to a predetermined site visiting plan. A crawlers' manager allocates the pages between visual crawlers, for obtaining required adequate incident coverage and load on the visual crawlers.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, are described for frequency optimization of advertisement streams. The methods and systems described in this specification may enable determination of an optimal presentation frequency of an ad stream, or a number of times the ad stream is to be broadcast and/or rebroadcast, prior to the audience becoming interested in the ad, or acting on the ad to generate a conversion event.

Abstract: A method, apparatus, and computer-readable medium estimate media performance on advertising space inventory. The method selects at least one media cell that shares one or more common attributes with a target media cell. The method subsequently estimates mean revenue per impression (RPI) of the selected media cell, and then defines an initial estimate of a RPI of the target media cell based on the estimated RPI of the selected cell. The method computes the RPI of the target media cell by combining the initial RPI estimate for the target media cell with performance data associated with the target media cell.

Abstract: A system and method for scaling causal lift is disclosed. Randomized experimental study data and observational data related to an advertising campaign is obtained. Response lift data from the randomized experimental study data and response lift data from the observational data are determined using regression discontinuity analysis. A model which includes an estimated response rate that corresponds to the randomized experimental study is created from the observational data using regression discontinuity analysis.

Abstract: Techniques are provided that can be used in experimentation in online advertising. In an experiment, a short, recurring time interval during a period may be divided into a set of segments. Serving opportunities to users occurring during each of the segments may be associated with a particular specified experimental treatment. The short duration of the interval and segments may aid in reducing experimental bias by reducing variation in non-experimental variables between different treatment groups. User behavior following experimental treatment may be tracked and utilized in measurement of user response associated with the treatment. Results of the experiment may be utilized in optimizing aspects of an online advertising campaign.

Abstract: Selecting an advertisement is disclosed. A preference event associated with a first advertisement is received from a first user. A quality score for the first advertisement is determined based at least in part on the received preference event. An advertisement fulfillment request is received. The request is responded to by selecting an advertisement based at least in part on the quality score of the first advertisement.

Abstract: A method and apparatus for delivering advertising via a mobile device are disclosed. Receivable codes are captured by the mobile device, for example by a camera. The codes may be QR codes, codes with fiduciary markers, or the like. Plural interactive value offers are generated, each directed toward a product or service associated with at least one code. The interactive value offers are adjusted in response to each other, and presented via a user interface. Other features include: providing navigation directions from a current location to a location where a value offer can be fulfilled, processing location information to gauge an effect of the interactive value offer on the user and adjusting the offer based on said effect, adjusting the offer based on a current interest in the offer, and providing social networking opportunities in conjunction with the offer.

Abstract: Strategies are described for conducting an advertising campaign using a cost-per-transaction (CPT) pricing model. In this model, the advertiser is charged when an end-user takes some express action in response to viewing the advertisement, such as by clicking on the advertisement, purchasing the advertised asset, performing a registration procedure, and so forth. Various solutions allow for the computation of the expected value of a CPT advertisement when there is a scarcity of data pertaining to the actual performance of the CPT advertisement.

Abstract: A system and method is described herein that selects advertisements for two or more regions of a web page based on rankings of the advertisements generated using different models. By ranking advertisements separately for each region of a web page, and choosing highest ranked advertisements for each region, advertisements can be selectively chosen such that a user is more likely to select an advertisement in each region of the web page. As a result, the user experience can be enhanced and the advertising revenue can be correspondingly increased.

Abstract: Techniques are described herein for combining segments of users into super-segments. The interests of the segments in online ad campaigns in which they participate are compared to determine subsets of the segments whose interests are correlated to an extent that exceeds a designated threshold. The segments in each subset are combined to provide a respective super-segment. Each online ad campaign corresponds to a specified category, such as telecommunications, auto, finance, retail, entertainment, travel, etc. For each super-segment, the cumulative interest of the segments therein for each category are determined. The cumulative interests for each super-segment are used to determine which super-segment(s) are to be targeted for receiving a specified online advertisement.

Abstract: Techniques are provided that utilize online advertising traffic patterns at multiple geographically distributed data centers to make predictions about future traffic at the data centers, and use the predicted patterns in optimizing proportioning or allocation of an advertising budget between each of the data centers. For each of multiple geographically distributed data centers, a set of traffic data may be obtained, relating to past online advertising traffic at the data center. For each of the data centers, the set of traffic data is used in determining a prediction of online advertising traffic at the data center of a future period of time, which may include determining and utilizing a traffic pattern function for the data center. Using the prediction for each of the data centers, an optimized allocation is performed of an advertiser's online advertising budget over a future period of time between each of the data centers.

Abstract: The present disclosure provides a method and an apparatus of providing picture related information in order to address the problem of wasting storage resources of a server under existing technologies. The server establishes a correspondence relationship between information published by a first user and a picture that is referenced when publishing the information, and upon detecting that a second user performs a specified operation on the information, the server finds the picture that has the correspondence relationship with the information, records operation information of the operation action performed by the second user and stores the recorded operation information as related information of the found picture to be provided to the first user. Through the foregoing method, the first user can select a picture to be deleted according to related information of respective pictures and delete the selected picture from a storage space provided by the server.

Abstract: The usefulness, and consequently the performance, of advertisements are improved by allowing businesses to better target their ads to a responsive audience. For example, location information may be used in ad relevancy determination, and in attribute (e.g., position) arbitration. Such location information may be associated with price information, such as a maximum price bid, and/or with ad performance information. Ad performance information may be tracked on the basis of location information. The content of an ad creative, and/or of a landing page may be selected and/or modified using location information. Tools may be provided to enter and/or modify location information, such as location-dependent targeting information and price information. The location information used to target and/or score ads may be, include, or define an area. The area may be defined by at least one geographic reference point (e.g., defined by latitude and longitude coordinates) and perhaps additional information.

Abstract: Systems and methods for optimizing viral marketing efforts are disclosed in which a trial a viral marketing trial program is presented to a user. The viral marketing trial program includes a user incentive as well as a plurality of user tasks that needs to be completed to receive the user incentive. One or more user reactions to the plurality of user tasks are monitored; user feedback in accordance with the one or more user reactions is collected, the user feedback is analyzed using one or more metrics and the viral marketing trial program is adjusted in accordance with the analyzed user feedback.

Abstract: Embodiments of the present invention may allow selling agents to create a marketing campaign analysis, and associated marketing campaign recommendations, for a prospective seller of a saleable in an interactive fashion with the prospective seller. Embodiments of the present invention may utilize historical marketing and/or sales data for comparable properties (that have either been sold or for which sale has, or is currently, being attempted) in order to identify successful advertising campaigns. The relative ‘success’ of an advertising campaign can be determined by reference to certain predefined performance metrics. Based upon the results of these performance metrics (which can be customized to meet a seller's desired selling strategy), embodiments of the present invention may allow a selling agent to present the seller with one or more optimized marketing campaigns, from which a final marketing campaign can be selected for the listing of the subject property.

Abstract: Systems, methods, and computer-readable medium allow incorporation of delayed feedback in performance-based content delivery. A computer-implemented method includes receiving historical data indicative of performance of at least one first content item, determining a statistical distribution of the performance over time, applying the statistical distribution to a second content item to obtain an estimated performance of a second content item over time, and determining a pricing value of the second content item based on the estimated performance.

Abstract: Methods, articles, and systems for determining a bidding strategy for on-line query answer set or contextual advertisement positions for marketing options is described herein.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for creating experiment content distribution campaigns (“experiment campaign”) and allocating content in accordance with the experiment campaign. In one aspect, a control campaign or an experiment campaign are selected as an available campaign for providing content in response to receiving a content request. The selection can be a probability constrained selection where the probability with which the experiment campaign is selected is specified as a portion of a total number of requests received during an experiment period for which the experiment campaign is available to provide content. Content is provided in response to the request, where the provided content being content corresponding to the selected campaign.

Abstract: Disclosed is a data processing system including a plurality of terminals and a server connected to the terminals via a communication network. Each of the terminals includes a display unit, a layout modifier which modifies the layout data of the POP advertisement in response to a user operation, and an improvement-report-data transmitter which transmits the improvement report data to the server. The server includes an improvement analyzer which stores the linked analytical result and the improvement report data in a storage unit, and an analysis transmitter which transmits at least the POP advertisement of before and after the modification and the analytical result of the modification among the improvement report data stored in the storage unit in response to a request from any one of the terminals.

Abstract: A method of improving a traffic pattern through web page nodes of a website is provided, including selecting web page nodes. The traffic pattern includes a sequence of nodes. Each node represents a first page having a link to a second page in a subsequent node. A visitor to a node prior to a conversion node either navigates to a subsequent node or fails to progress to a subsequent node. The method also includes, for each web page, identifying display elements on the web page node that are associated with a decreased probability that the user progresses through the traffic pattern to a subsequent web page node in the predetermined traffic pattern, determining a metric representing an impact on a conversion attributable to the display elements, ranking the plurality of web page nodes based on the metrics for each web page node.

Abstract: A method and apparatus for dynamically adjusting the user interface of a search engine in order to effectively communicate the improved relevancy achieved through real-time implicit re-ranking of search results is described. Real-time implicit re-ranking occurs without delay after every user action as the search is being conducted, so finding methods of immediately altering the search page without disrupting the user experience is important. Graphical icons next to search results are employed to enable generating and removing re-ranked results, referred to as “recommended” search results. Clusters based on the real-time user model are also displayed to facilitate query reformulations. Sponsored links are selected using the real-time user model along with a combination of RPC and CTR information and are displayed in a manner similar to the organic results, or used to replace the initial sponsored links altogether.

Abstract: A publication evaluation subsystem generates publication scores for publications. Each publication score is indicative of an expected performance for content that is presented with the publication. The publication scores are generated relative to a baseline performance measure. The baseline performance measure has a value that is indicative of an expected performance of any selected content presented with any publication in the content network. More than one publication score can be generated for each publication, with each publication score being indicative of the performance of a sub-group of content items that are presented with the publication. The sub-group of content items can include content items that each share a common characteristic. For example, a publication score can be generated for a sub-group of content items that are associated with common targeting criteria (e.g., keywords).

Abstract: Systems and methods for adjusting online ads delivery pace derive, in a computer system, a current impression delivery for an ads display contract. A plurality of estimation bands are delivered corresponding to over delivery and under delivery for the ads display contract. A relative distance is determined between the current impression delivery and the plurality of estimation bands. An adjustment factor is selected according to the relative distance. The adjustment factor is sent to a database.

Abstract: A system and method for conducting randomized trials on ad exchanges are disclosed. A list of all cookies on an advertising exchange may be compiled, and a random sample of cookies may be drawn from the list of cookies for each of one or more test groups and a control group. One or more users from each of the one or more test groups may be targeted if each of the one or more users satisfy predetermined targeting criteria of an advertising campaign and if each of the one or more users satisfy one or more predetermined test criteria. One or more users from the control group may be targeted if each of the one or more users satisfy the predetermined targeting criteria. Audience reactions from each of the test groups and the control may be compared.

Abstract: The present invention is directed to systems, articles, and computer-implemented methods for assessing effectiveness of communication content and optimizing content distribution to enhance business objectives. Embodiments of the present invention are directed to computer-implemented methods for a computer-implemented method, comprising conducting an experiment using experimental content to determine effectiveness of communication content and executing, while conducting the experiment, a machine learning routine (MLR) using MLR content to enhance an effectiveness metric.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for creating experiment content distribution campaigns (“experiment campaign”) and allocating content in accordance with the experiment campaign. In one aspect, a control campaign or an experiment campaign are selected as an available campaign for providing content in response to receiving a content request. The selection can be a probability constrained selection where the probability with which the experiment campaign is selected is specified as a portion of a total number of requests received during an experiment period for which the experiment campaign is available to provide content. Content is provided in response to the request, where the provided content being content corresponding to the selected campaign.