Abstract: An apparatus, method, and computer program product are provided for the improved and automatic prediction and modeling of one or more channels and relevant conditions through which resources may be directed to users in an environment where resource demand, utility, and perceived value vary over time. Some example implementations employ predictive, machine-learning modeling to facilitate the use of multiple disparate and unrelated data sets to extrapolate and otherwise predict the future needs for certain resources and identify the channels and conditions that may be employed to meet such future needs. An apparatus, method, system, and computer program product are provided for improved generating, adjusting, and/or facilitating approval of a resource offer set. Some example implementations employ one or more predictive models.

Abstract: A processor-implemented method is disclosed.

Abstract: An online system receives financial account information for a user, such as debit card information, from a merchant system with which the user places an order. From the financial account information, the online system selects a virtual credit card providing one or more rewards, such as cashback, to the user. Based on characteristics of the order by the user, the online system identifies one or more offers, such as discounts or rebates, applicable to the order. The online system provides the virtual credit card information to the merchant system and stores the virtual credit card information, as well as information describing one or more identified offers for the order in association with the user and the virtual credit card, in an account maintained for the user. Rewards may be stored in the user's account at the online system for application when using the virtual credit card associated with the user.

Abstract: Methods, apparatus, and processor-readable storage media for automatically generating context-based alternative text using artificial intelligence techniques are provided herein. An example computer-implemented method includes generating text captions for an image derived from a web page by processing the image using an artificial intelligence-based image captioning model; determining context information pertaining to the image by processing the image using an artificial intelligence-based context and emotion recognition library; generating context-based alternative text for at least a portion of the image by processing, using at least one artificial intelligence-based alternative text generation model, at least a portion of one or more of the generated text caption(s) for the image and the determined context information pertaining to at least a portion of the image; and performing one or more automated actions based on the generated context-based alternative text.

Abstract: Determining and hiding a replaceable period of a MP (Media Presentation). A method for determining includes receiving a first MPD (Media Presentation Description) that identifies a predetermined period and at least one media segment of the MP to be presented during the predetermined period. A determination is made as to whether the first MPD includes additional data to be resolved by an application. The additional data is provided to the application when the first MPD is determined to include the additional data. Additional period information is received from the application. A second MPD is generated based on the received additional period information. The MP is output for display to a user based on the second MPD. Each of a subset of the at least one media segment for a replaceable sub-period of the MP is replaceable with an alternate media segment.

Abstract: A method and system of matching a first product with a second product. The method including converting first product metadata with image metadata and textual data to a first product feature vector. Further, determining a distance between the first product feature vector and a second product feature vector of the second product, the second product feature vector stored in a database of product feature vectors. The distance is compared to a threshold distance, and if the distance is within the threshold distance, validating a match between the first product feature vector and the second product feature vector. The validating further includes geometrically verifying the image metadata of the first product corresponds to image metadata of the second product.

Abstract: In some examples, a system comprises at least one programmable processor; and a machine-readable medium having instructions stored thereon which, when executed by the at least one programmable processor, cause the at least one programmable processor to execute operations comprising: receiving a first request from at least one user device to execute an instance of an application; transmitting a graphical user interface (GUI) to the at least one user device to be rendered on a display of the at least one user device; receiving a second request, via the GUI, from the at least one user device, to deploy a digital advertisement, the second request including a set of platforms of a plurality of platforms of a multi-platform integration system, a set of settings, a set of parameters, and a set of allocation data; interfacing with each one of the platforms in the set of platforms; and integrating a digital advertisement directly with each one of the platforms in the set of platforms based on the set of settings, the

Abstract: Methods and systems are provided herein for summarizing a set of anomalies corresponding to a group of metrics of interest to a monitoring system user. Initially, a set of anomalies corresponding to a group of metrics is identified as having values that are outside of a predetermined range. A correlation value is determined for at least a portion of pairs of anomalies in the set of anomalies. For each anomaly in the set of anomalies, an informativeness value is computed that indicates how informative each anomaly in the set of anomalies is to the monitoring system user. The correlation values and the informativeness values are then used to identify at least one key anomaly and a plurality of non-key anomalies from the set of anomalies. A summary is generated of the identified at least one key anomaly to provide information to the monitoring system user about the set of anomalies for a particular time period.

Abstract: A system including a secondary visual digital display on the customer-facing side of a cash register or point-of-sale terminal display. The customer-facing digital display presents advertising content, videos, informational content, or any other form of content that the business or location owner or operator would like to have displayed to customers. An application program, as described below, is stored and/or loaded on memory storage in the secondary display and run by a microprocessor in the secondary display, or alternatively, is stored and/or loaded on a separate device, and run by a microprocessor in the secondary display or in the separate device. The content may be displayed based upon context.

Abstract: A machine is configured to generate in real time personalized online banner images for users based on data pertaining to user behavior in relation to an image of a product. For example, the machine receives a user selection indicating one or more data features associated with the user. The one or more data features include a data feature pertaining to user behavior in relation to an image of a product. The machine generates, using a machine learning algorithm, a data representation of the machine learning algorithm based on the one or more data features including the data feature pertaining to user behavior in relation to the image of the product. The data representation includes one or more data features pertaining to one or more characteristics of online banner images. The machine generates an online banner image for the user based on the data representation.

Abstract: Disclosed embodiments may include a system that may receive an interaction message associated with an interaction a user has with an application or website, the interaction message may include an error message or a repeated action message. The system may identify, using a first machine learning model, one or more issues associated with the interaction message, retrieve one or more troubleshooting steps mapped to the one or more issues, and generate a first message comprising the one or more troubleshooting steps and a feedback request on an effectiveness of the one or more troubleshooting steps. The system may transmit the first message to the user, receive feedback from the user in response to the feedback request, and determine whether the feedback is negative. When the feedback is negative, the system may transmit a second message to a representative requesting the representative call the user.

Abstract: Aspects of the subject disclosure may include, for example, determining that an addressable user is subscribed to at least a first platform and a second platform that is different from the first platform, assigning an identification that maps to each of the first platform and the second platform, determining that an advertisement associated with a buyer is available to be delivered to the addressable user via the first platform, the second platform, or a combination thereof, in accordance with a first parameter associated with the addressable user and at least a second parameter associated with the first platform, the second platform, or the combination thereof, and responsive to the determining that the advertisement is available, delivering the advertisement to the addressable user in accordance with the identification. Other embodiments are disclosed.

Abstract: An example method performed by a processing system includes retrieving a digital model of a media element from a database storing a plurality of media elements, wherein the media element is to be inserted into a scene of an audiovisual media, rendering the media element in the scene of the audiovisual media, based on the digital model of the media element and on metadata associated with the digital model to produce a rendered media element, wherein the metadata describes a characteristic of the media element and a limit on the characteristic, and inserting the rendered media element into the scene of the audiovisual media.

Abstract: A system and method are provided implementing user searching. The method includes receiving information from a potential user by an onboarding system including one or more attributes for attaching the user to one or more communities with similar attributes, and receiving one or more search terms from the user by a search system. A processor then performs a search based upon the received search terms and the one or more communities to which the user is attached, and a response to the search is displayed to the user on a display. A user preference to the presented response is confirmed by a preference system, and one or more communities to which the user is attached are dynamically updated, along with updating the attributes of the communities to which the user is attached in response to the user preference.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for selecting an audience for content are disclosed. In one aspect, a method includes receiving, from a content item provider, a request to distribute content items to users that have been deemed interested in a particular entity. First users that have expressed an interest in the particular entity are identified. Expansion entities for the particular entity are identified in a knowledge graph. At least one of the expansion entities can be connected to the particular entity by a relationship path. Second users are identified. The second users are deemed interested in the particular entity based on the second users having expressed an interest in an expansion entity. The content items are provided to at least a portion of the first users and at least a portion of the second users.

Abstract: A computer-implemented method for using a machine-learning trained predictive engine to predict failures, comprising receiving, from a user using a graphical user interface, electronic transaction data comprising an item and candidate transaction terms, the candidate transaction terms comprising a first transaction term, the electronic transaction data being associated with a candidate transaction. The method may determine, by a machine learning predictive engine, a likelihood of success of the candidate transaction based on the electronic transaction data, and may determine, by the machine learning predictive engine, based on the first transaction term, a second transaction term that, together with the first transaction term, increases the likelihood of success of the candidate transaction above a predetermined threshold. An indication of the second transaction term and an indication of the likelihood of success of the candidate transaction may be displayed on the graphical user interface.

Abstract: A method for providing context based artefact access to tenants of a cloud computing system includes receiving a request to access an artefact deployed on the cloud computing system. The request includes a tenant identifier and an artefact identifier. Context data associated with the artefact is determined based on the tenant identifier. Context data associated with the artefact is retrieved from an artefact repository stored in a database of the cloud computing system. Access to the artefact is provided based on the retrieved context data associated with the artefact on a device associated with the tenant.

Abstract: The invention relates to a campaign management system comprising a computer-data processor memory, a graphical user interface, the management system processing a plurality of participant records according to a user-configured process structure of a plurality of configured logic templates; a plurality of participant records arranged to store participant contact interface information associated with participant contact interfaces; a plurality of logic templates; a plurality of graphical elements each associated with one of said logic templates; a graphical user interface arranged to display said graphical elements; wherein the campaign management system is configured for execution of a live mode and a test mode, wherein the live mode for the campaign executes executable program fragments of the process structure for processing of the individual participant records established for a respective campaign, wherein the test mode executes executable program fragment of the process structure of the respective campaign

Abstract: A method and system of matching a first product with a second product. The method including converting first product metadata with image metadata and textual data to a first product feature vector. Further, determining a distance between the first product feature vector and a second product feature vector of the second product, the second product feature vector stored in a database of product feature vectors. The distance is compared to a threshold distance, and if the distance is within the threshold distance, validating a match between the first product feature vector and the second product feature vector. The validating further includes geometrically verifying the image metadata of the first product corresponds to image metadata of the second product.

Abstract: Systems and methods are described for monitoring and managing an online experience. An example method includes: obtaining user data describing interactions between a plurality of users and plurality of online services; determining, based on the user data, a rate of change in usage of the online services for each user in the plurality of users; assigning a portion of the users to a user segment based on the user data and the determined rate of change in usage; and based on the assignment, providing each user in the user segment with a customized experience in one or more of the online services.

Abstract: Systems and methods are provided for generating and provisioning personalized news feeds for athletes. One embodiment is a system that receives metrics for exercise activities performed by athletes. The system generates records of the exercise activities of the athletes based on the metrics, determines a type of exercise for each record, classifies the records based on corresponding types of exercise, and compiles a fitness history, for each athlete, comprising records of exercise activities performed by the athlete. For each of the athletes, the system generates a digital news feed for the athlete, identifies categories of engagement for the athlete based on types of exercise indicated in the fitness history of the athlete, selects articles from a repository, personalizes the digital news feed for the athlete by populating the digital news feed with the selected articles, and transmits the digital news feed to a user device.

Abstract: A computer-implemented method, and a computer system are provided for implementing dynamic and automatic altering a user profile based on machine learning and cognitive analysis to improve user performance. The user profile is dynamically altered based upon live data from multiple external data sources using machine learning and cognitive application programming interfaces (APIs) without explicit input from the user. The altered user profile is automatically stored for the user. The stored user profile is deployed for multiple selected user applications enabling enhanced performance for the user.

Abstract: A method, a device, and a non-transitory storage medium are described, which provide a recommendation system with performance management service. The service may include selecting and ranking content that relate to a user query and a problem associated with an application and/or a device. The service may include invoking a remedial procedure based on user feedback data. The service may include similarity and classification models based on successful recommendation records.

Abstract: A method is disclosed. The method may include establishing a connection with a client device via an application executing on the client device; detecting one or more web pages that the application of the client device has visited during the established connection; determining a target audience for the connection based on the detected one or more web pages; responsive to determining the target audience, identifying a set of content items from memory based on each content item of the set having a stored association with an identifier of the target audience in the memory; selecting a first content item from the set of content items; and transmitting the first content item to the client device over the connection for display on a web page.

Abstract: A station device in a biometric pre-identification system uses identity to perform one or more actions. Identities are determined (such as via a backend) using biometric information. A biometric pre-identification device obtains biometric information and/or a digital representation thereof from a person approaching the station device. The biometric pre-identification device transmits such to the station device, facilitating the station to begin and/or perform various actions. The station device begins or performs the actions using the identity determined based on the biometric information before the person arrives at the station device.

Abstract: Various implementations described herein provide systems and methods for online advertising and, more particularly, systems and methods that utilize user preferences in providing online advertising. In various implementations, systems or methods described herein facilitate user control of user-related data with respect to online advertisement systems, which can include supply-side platforms (SSPs), advertisement exchanges, demand-side platforms (DSPs), content delivery networks (CDNs), ad networks, or adservers. In some implementations, the system and methods implement or otherwise facilitate a user advertisement preference service that enables online users to manage one or more user advertisement preferences and selectively provide those user advertisement preferences to online advertisement systems.

Abstract: A computing system receives user activity data from a user interacting with content associated with a third party computing system. The computing system generates a profile for the user based on the user activity data. The profile includes tags indicating attributes about the user. The computing system establishes a communication session between the user and the intelligent assistant via a chat interface. The computing system receives a message from the user to the intelligent assistant. The computing system determines that the message includes at least one key word triggering retrieval of relevant content. Based on the determining, the computing system retrieves content that is associated with the key word and relevant to the user based on the tags associated with the user profile. The computing system causes a client device associated with the user to display the content alongside the chat interface.

Abstract: Systems and methods associated with providing content personalization are disclosed. In one embodiment, an exemplary method may comprise receiving first data including content preferences associated with an audience, receiving second data including an initial digital message being proposed for transmission to the audience, generating a recommendation data set based at least in part on the first data and the second data, wherein the recommendation data set identifies at least one recommended content type and at least one recommended message type, determining via a natural language generation machine learning model suggested content for the audience, and providing the suggested content for dissemination to the audience.

Abstract: A method and system for providing one or more suggested application features to a user of an application may include receiving an indication of a user action in a document, accessing contextual document data associated with the document, providing at least one of information about the user action or the contextual document data as input to a machine-learning (ML) model to predict a desired intent for the document, obtaining the predicted desired intent as an output from the ML model, identifying based on the predicted desired intent one or more application features that fulfil the desired intent, and providing data about the one or more application features for display.

Abstract: An apparatus and method for profile assessment, the apparatus including at least a processor, and a memory communicatively connected to the processor, the memory containing instructions configuring the processor to receive user data, receive system data, classify the user data to a service type, generate a pecuniary adjustment assessment as a function of the classified user data and system data and output the pecuniary adjustment assessment.

Abstract: A mobile device is used to initiate and execute a transaction between a customer and a merchant. A mobile device is used to initiate a point of sale transaction, wherein a merchant ID is sent to a payment processing server. Responsive to receiving a communication from the mobile device, the payment processing server requests transaction information from the merchant, wherein the merchant is identified based on the provided merchant ID. The merchant can provide transaction information such as the total sale amount to the payment processing server. The payment processing server can authenticate the customer and initiate a purchase transaction with the appropriate financial institutions associated with the customer and the merchant. The payment processing server can send a confirmation of the executed transaction to the merchant and the mobile device.

Abstract: Systems as described herein determine merchant enforced transaction rules. A determination server may receive transaction data associated with a plurality of merchants. The determination server may generate a histogram of payments associated with a merchant category and filter out transaction data having purchase amounts above or below a predetermined threshold. The determination server may determine a first average purchase amount associated with merchants in the merchant category and a second average purchase amount associated with each merchant in the merchant category. The determination server may determine user spending patterns and that a first merchant in the merchant category enforces one or more card-based transaction rules using machine learning models. After determining that a user device is proximately located to the first merchant, a notification indicating the one or more card-based transaction rules associated with the first merchant may be sent to the user device.

Abstract: A method and apparatus comprising generating a dynamic personalized webpage is disclosed. At least two webpages are loaded in a fashion that is hidden from the user. Content from the at least two webpages is extracted based on classification “of interest” by an artificial intelligence algorithm. A dynamic personalized webpage comprising extracted content is then generated and displayed to the user. In the preferred embodiment, the user's dynamic personalized webpage will be filled with advertisements tailored to the user and the user would receive 100% of the payment from the advertisers.

Abstract: Methods, computer-readable media, software, and apparatuses may retrieve, from a computing device at a vehicle, driving data, and determine, based on the driving data, a range of time when a driver of the vehicle has a low likelihood of accessing a web resource over a network. An online activity may be detected for an account associated with the driver. In some aspects, a time of the online activity may be compared to the range of time. Based upon a determination that the time of the online activity is within the range of time, a potentially unauthorized activity may be identified. In some aspects, in response to the potentially unauthorized activity, one or more steps may be triggered to protect the driver from the potentially unauthorized activity.

Abstract: The method includes: collecting historical operations of sample users for M items, and predicting a preference value of a target user for each of the M items according to historical operations of the sample users for each of the M items, collecting classification data of N to-be-recommended items, and classifying the N to-be-recommended items according to the classification data of the N to-be-recommended items, to obtain X themes, where each of the X themes includes at least one of the N to-be-recommended items, and the N to-be-recommended items are some or all of the M items; calculating a preference value of the target user for each of the X themes according to a preference value of the target user for a to-be-recommended item included in each of the X themes; and pushing a target theme to the target user.

Abstract: Methods and apparatus to incorporate saturation effects into marketing mix models are disclosed. An example apparatus includes means for converting adstock data associated with an advertising campaign into effective reached realized (ERR) data based on a first saturation curve, the adstock data corresponding to adstocked gross rating points generated from marketing mix input data. The apparatus further including means for performing regression analysis to: identify the first saturation curve from among a plurality of plausible curves based on a fit of different ones of the plurality of plausible curves to the marketing mix input data, the first saturation curve to define a relationship indicative of saturation effects of the advertising campaign on a target audience of the advertising campaign; and determine an impact of the advertising campaign on sales during a period of interest based on a regression analysis of the ERR data relative to sales data.

Abstract: A credit scoring method and a server are provided. The method includes: determining at least one target user set in a plurality of user sets. The at least one target user set includes first behavior-unknown users whose predicted profit values are higher than second behavior-unknown users, the second behavior-unknown users are users other than the first behavior-unknown users on an application platform. The method also includes determining credit scores of first behavior-unknown users according to credit scores of behavior-known users in at least one determined target user set; obtaining first user samples from the first behavior-unknown users according to credit records of the first behavior-unknown users, the first user samples having profit values that satisfy a preset threshold; and performing credit scoring for a user according to a second scoring model obtained through training a first scoring model according to the first user samples and second user samples.

Abstract: Systems, methods, and computer-readable media are disclosed for optimizing a programmatic advertising system by continuously adjusting certain policies with respect to the advertising bids to manage and balance commitments made to publishers and/or advertisers. The policies may be modified to adjust an attach rate and/or a guaranteed bid rate to balance various type of advertising bids (e.g., open auction, private market place deals, preferred deals, etc.) and ensure that commitments publishers and/or advertisers are satisfied. The system may continuously track new bids and may adjust the policies in real time or near real time to achieve certain targets for submissions, impressions, and other well-known advertising metrics.

Abstract: Provided an information processor capable of proposing more useful items to a user. An information processor includes: a processor; and a memory. The memory holds: first information on a relationship between a first assistant and a first person to be assisted who is assisted by the first assistant; second information on a relationship between a second assistant and a second person to be assisted who is assisted by the second assistant; third information on an item purchase history of the first assistant and/or the first person to be assisted; and fourth information on an item purchase history of the second assistant and/or the second person to be assisted. The processor judges a similarity between the first information and the second information, and provides an advertisement based on the fourth information to the first assistant and/or the first person to be assisted if judging that a similarity is observed between the first information and the second information.

Abstract: In one aspect, an example methodology implementing the disclosed techniques includes, by a survey workflow module, receiving a survey request event for which a survey is requested and generating a first feature vector for the survey request event, wherein the first feature vector comprises features extracted from the survey request event. The method also includes predicting, by a first trained prediction module, whether the survey request event will result in a survey based on the first feature vector, wherein the first trained prediction module is trained using a training dataset generated from a corpus of historical survey request event-survey data.

Abstract: A system for providing a third party engagement in a host property is provided. The system includes a user device structured to: provide an indication of an active user session associated with a host property, the host property communicatively coupled to a host property provider computing system; receive a third party engagement based on a trigger activated during the active user session, the trigger structured to generate the third party engagement; provide, via a graphical user interface comprising the host property, the third party engagement based on the trigger activated; and receive an indication of activation of the third party engagement.

Abstract: Methods and systems described herein recite the use of specific data structures for stateful data that include fields for populating with specific information that may be used to prevent and/or minimize the corruption in stateful data. The systems and methods may recite the application of specific data normalization sets that include functions to be applied to test data sets and control data sets, respectively, in order to prevent and/or minimize the corruption. Finally, the methods and systems may recite the determination of incrementality being based on uncorrupted impressions corresponding to test data sets and control data sets, respectively.

Abstract: A system and method are provided implementing user searching. The method includes receiving information from a potential user by an onboarding system including one or more attributes for attaching the user to one or more communities with similar attributes, and receiving one or more search terms from the user by a search system. A processor then performs a search based upon the received search terms and the one or more communities to which the user is attached, and a response to the search is displayed to the user on a display. A user preference to the presented response is confirmed by a preference system, and one or more communities to which the user is attached are dynamically updated, along with updating the attributes of the communities to which the user is attached in response to the user preference.

Abstract: The method includes: collecting historical operations of sample users for M items, and predicting a preference value of a target user for each of the M items according to historical operations of the sample users for each of the M items, collecting classification data of N to-be-recommended items, and classifying the N to-be-recommended items according to the classification data of the N to-be-recommended items, to obtain X themes, where each of the X themes includes at least one of the N to-be-recommended items, and the N to-be-recommended items are some or all of the M items; calculating a preference value of the target user for each of the X themes according to a preference value of the target user for a to-be-recommended item included in each of the X themes; and pushing a target theme to the target user.

Abstract: Examples to determine media impressions using distributed demographic information are disclosed. An example system includes programmable circuitry to log, at a first Internet domain, a first record for a first website visit by a first client device to a website at a second Internet domain, the first record based on a hypertext transfer protocol (HTTP) request, the first record to include a timestamp, a uniform resource locator (URL), and a user identifier, the timestamp to represent a time of the first website visit, the URL corresponding to the website at the second Internet domain, and weight impression data in a report, the impression data associated with the first record and with second records, the second records corresponding to second website visits to the website via second client devices, the weighting of the impression data based on demographic distributions of audience members corresponding to the first and second records.

Abstract: Disclosed herein are systems, methods, and apparatuses that can provide, for example, dynamic page feed recognition for providing zero-configuration analysis of web pages and tailored advertisement provision to website visitors. The systems, methods, and apparatuses can be used to analyze inventory feed. Based on analysis of user interaction data on the web pages, one or more matching methodologies can be used to determine matching data between the visited web pages and the inventory feed.

Abstract: Examples to determine media impressions using distributed demographic information are disclosed. An example system includes programmable circuitry to log, at a first Internet domain, a first record for a first website visit by a first client device to a website at a second Internet domain, the first record based on a hypertext transfer protocol (HTTP) request, the first record to include a timestamp, a uniform resource locator (URL), and a user identifier, the timestamp to represent a time of the first website visit, the URL corresponding to the website at the second Internet domain, and weight impression data in a report, the impression data associated with the first record and with second records, the second records corresponding to second website visits to the website via second client devices, the weighting of the impression data based on demographic distributions of audience members corresponding to the first and second records.

Abstract: Method and system for playing audio on a device, the method comprising the steps of a component of a digital work initiating a request for audio data during a rendering of the digital work, the digital work including video data. In response to the request, receiving the audio data. While continuing the rendering of the digital work on the device, suspending playback of first audio data currently playing on the device and playing the received audio data on the device. When the received audio data stops playing continuing with the rendering of the digital work on the device and resuming playback of the first audio data previously playing on the device.

Abstract: Embodiments are directed towards employing multiple profiles to track identification of users across multiple domains. Multiple application-domain profiles and multiple web-domain profiles may each include a statistical identifier. A profile enrichment store may be generated from the application-domain profiles and web-domain profiles, where each entry in the profile enrichment store may be based on statistical identifiers. The profile enrichment store may be utilized to determine categories associated with a statistical identifier for a request from a client device. A targeted advertisement may be determined based on the determined category and may be provided to the client device. A client caching identifier may be used in a mobile web domain, in combination with the statistical identifier, to track mobile web users. If a request is associated with a profile that includes an affirmative opt-out flag, categories in the profile enrichment store for a corresponding statistical identifier may be cleaned up.

Abstract: A control system determines whether a browser is retrieving supplemental content over a slow or faulty network using a tracking indicator. Based on determining that browser is retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser. The control system may modify responses by declining to bid, responding with a lower bid amount, or responding with alternate supplemental content. Based on determining that browser is no longer retrieving supplemental content over a slow or faulty network, the control system modifies responses to opportunities to provide supplemental content to the browser by responding with a higher bid amount or responding with the original supplemental content. Thus, the control system maximizes the use of control system and campaign manager resources by responding to opportunities according to the likelihood that they will result in an impression or a conversion.