Abstract: A client application can be configured to render user interface cards, based on card data provided by a remote card engine. An API Response as Card (ARC) engine can intercept a communication between the client application and the card engine, and determine that the communication is associated with another backend system. The ARC engine can request that the backend system perform an account action associated with a user account. The ARC engine can provide information derived from a response from the backend system, reflecting a result of the account action, to the card engine. The card action can generate card data associated with the result of the account action performed by the backend system, and the client application can use the card data to render and display a corresponding card, even if neither the client application nor the card engine are natively configured to interface with the backend system.

Abstract: Systems and methods are provided for using automated mobile computing device testing to ensure that a given targeted message is actually appearing in an intended manner for various types of intended recipients. The intended content or format of a target message to be presented by each of a plurality of mobile computing devices may be based on characteristics of each device. The targeted message may be sent to each device, and an indication of the actual content and/or format of the targeted message as presented by each device may be received and compared to the intended content or format of the targeted message for each device. Errors associated with the targeted message may be detected based on any discrepancies between the intended content and/or format of the targeted message for each device and the actual content or format of the targeted message as presented by each device.

Abstract: Systems and methods are provided for using automated mobile computing device testing to ensure that a given targeted message is actually appearing in an intended manner for various types of intended recipients. The intended content or format of a target message to be presented by each of a plurality of mobile computing devices may be based on characteristics of each device. The targeted message may be sent to each device, and an indication of the actual content and/or format of the targeted message as presented by each device may be received and compared to the intended content or format of the targeted message for each device. Errors associated with the targeted message may be detected based on any discrepancies between the intended content and/or format of the targeted message for each device and the actual content or format of the targeted message as presented by each device.

Abstract: A server operated by a service provider may enable a user to upgrade and/or purchase one or more service plans associated with a user account and provided by the service provider. The service plan may include access to one or more third-party services that provide content accessible via applications. The service provider may inform a notification service that operates a device management platform that the user account is permitted access to the content provider. The notification service may send a message to the user device including an indication that the user device now has access to the content provider and/or a selectable option to install an application associated with the content provider.

Abstract: Call propensity source data may be received that include a first percentage of call propensity source data that correspond to presence of post-visit phone calls to a customer service of an entity after some customer visits to a web site of an entity and a second percentage of call propensity source data that correspond to absence of post-visit phone calls to the customer service after other customer visits to the website. A machine-learning model is trained based on a plurality of features in at least a portion of the call propensity source data to generate a trained machine-learning model. The trained machine-learning model is applied to multiple features included in at least one of corresponding website activity data and corresponding activity error data of a customer to generate a probability score that measures a likelihood of the customer calling the customer service regarding an issue that is unresolved via the website.

Abstract: A client application can be configured to render user interface cards, based on card data provided by a remote card engine. An API Response as Card (ARC) engine can intercept a communication between the client application and the card engine, and determine that the communication is associated with another backend system. The ARC engine can request that the backend system perform an account action associated with a user account. The ARC engine can provide information derived from a response from the backend system, reflecting a result of the account action, to the card engine. The card action can generate card data associated with the result of the account action performed by the backend system, and the client application can use the card data to render and display a corresponding card, even if neither the client application nor the card engine are natively configured to interface with the backend system.

Abstract: A server operated by a service provider may enable a user to upgrade and/or purchase one or more service plans associated with a user account and provided by the service provider. The service plan may include access to one or more third-party services that provide content accessible via applications. The service provider may inform a notification service that operates a device management platform that the user account is permitted access to the content provider. The notification service may send a message to the user device including an indication that the user device now has access to the content provider and/or a selectable option to install an application associated with the content provider.

Abstract: Call propensity source data may be received that include a first percentage of call propensity source data that correspond to presence of post-visit phone calls to a customer service of an entity after some customer visits to a web site of an entity and a second percentage of call propensity source data that correspond to absence of post-visit phone calls to the customer service after other customer visits to the website. A machine-learning model is trained based on a plurality of features in at least a portion of the call propensity source data to generate a trained machine-learning model. The trained machine-learning model is applied to multiple features included in at least one of corresponding website activity data and corresponding activity error data of a customer to generate a probability score that measures a likelihood of the customer calling the customer service regarding an issue that is unresolved via the website.

Abstract: Systems and methods are provided for using automated mobile computing device testing to ensure that a given targeted message is actually appearing in an intended manner for various types of intended recipients. The intended content or format of a target message to be presented by each of a plurality of mobile computing devices may be based on characteristics of each device. The targeted message may be sent to each device, and an indication of the actual content and/or format of the targeted message as presented by each device may be received and compared to the intended content or format of the targeted message for each device. Errors associated with the targeted message may be detected based on any discrepancies between the intended content and/or format of the targeted message for each device and the actual content or format of the targeted message as presented by each device.

Abstract: The techniques provide a wireless communication carrier with the ability to efficiently add a device that is currently provisioned for a different carrier. Identification information is received for a mobile device to be switched from a first mobile network operator to a second mobile network operator. From a user interface executing on the mobile device, authorization is received to switch the mobile device. A token is generated that is usable to access unique identification data for an embedded Universal Integrated Circuit Card (eUICC) installed on the mobile device. Based in part on the tokens, subscription credentials are generated for accessing a mobile communications network operated by the second mobile network operator. Using the subscription credentials, the mobile device is provisioned to communicate on the mobile communications network operated by the second mobile network operator without further user input.