Abstract: The present disclosure relates to systems and methods for automatic attribution modeling and measurement. In aspects, a system may receive identification information associated with profiles and electronic devices that were exposed to a certain piece of targeted content. The demographic and device data associated with the individuals who were exposed to the targeted content are used to create a control group of individuals who were not exposed to that targeted content. The real-world visit rates of the exposed group and the control group to one or more locations may be monitored over a period of time (or campaign) and evaluated to assess the effectiveness of the targeted content.

Abstract: The present disclosure relates to systems and methods for automatic attribution modeling and measurement. In aspects, a system may receive identification information associated with profiles and electronic devices that were exposed to a certain piece of targeted content. The demographic and device data associated with the individuals who were exposed to the targeted content are used to create a control group of individuals who were not exposed to that targeted content. The real-world visit rates of the exposed group and the control group to one or more locations may be monitored over a period of time (or campaign) and evaluated to assess the effectiveness of the targeted content.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: The present disclosure relates to systems and methods for automatic attribution modeling and measurement. In aspects, a system may receive identification information associated with profiles and electronic devices that were exposed to a certain piece of targeted content. The demographic and device data associated with the individuals who were exposed to the targeted content are used to create a control group of individuals who were not exposed to that targeted content. The real-world visit rates of the exposed group and the control group to one or more locations may be monitored over a period of time (or campaign) and evaluated to assess the effectiveness of the targeted content.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.

Abstract: In non-limiting examples, passive information is used to verify the location of a client computing device and to create segment categories for directed information using location-based services and/or applications. In aspects, passive information is received from a client computing device. The client computing device is detected as being located at a predicted venue using the passive information. It may be determined whether directed information associated with the predicted venue has been displayed at an earlier time on a predetermined portion of the client computing device. In response to determining directed information associated with the predicted venue has been displayed on the predetermined portion of the client computing device, a statistical model may be applied to calculate a confidence score that the client computing device is located at the predicted venue. When the confidence score meets a predetermined threshold, a directed information conversion record may be stored in a data store.