Abstract: The techniques disclosed herein provide a secure control plane (SCP), which in turn provides an isolated secure execution environment for a data plane (DP). Any arbitrary business logic can execute within the DP, and all sensitive data traversing the SCP and entering the DP is encrypted. Split keys generated outside the DP are assembled within, and only within, the DP, where they are used to decrypt sensitive data, enabling the business logic to perform computations using the sensitive data within the secure execution environment. The DP also provides attestation for the business logic executing within the DP, enabling outside parties to verify that the deployed business logic matches published logic. In the event of proprietary logic that is not published, techniques are also disclosed herein that enable verification that proprietary business logic deployed on the DP adheres to security policies.

Abstract: A processing device selects a population of persons and measures sales metrics from the population over a time period and measures an advertising weight over the time period. The processing device determines an effect that the advertising weight has on the sales metrics and additionally calculates values for a degree of targetedness for the advertisement to the population of persons. The processing device determines an effect that the degree of targetedness has on the sales metrics and generates a multi-dimensional model that measures the combined effects of the advertising weight and the degree of targetedness on the sales metrics.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: The techniques disclosed herein provide a secure control plane (SCP), which in turn provides an isolated secure execution environment for a data plane (DP). Any arbitrary business logic can execute within the DP, and all sensitive data traversing the SCP and entering the DP is encrypted. Split keys generated outside the DP are assembled within, and only within, the DP, where they are used to decrypt sensitive data, enabling the business logic to perform computations using the sensitive data within the secure execution environment. The DP also provides attestation for the business logic executing within the DP, enabling outside parties to verify that the deployed business logic matches published logic. In the event of proprietary logic that is not published, techniques are also disclosed herein that enable verification that proprietary business logic deployed on the DP adheres to security policies.

Abstract: A processing device receives set-top box data, sales data, and advertising data. The processing device associates set-top boxes from the set-top box data with viewers and calculates advertising exposure events for advertisements. The processing device further calculates, for each viewer, an advertising weight as a function of number of exposures of the advertisement as applied to the viewer based on the advertising exposure events. The processing device further calculates, for each viewer, a score representing a degree-of-targetedness between an advertisement campaign and the viewer. The processing device manages the advertisement campaign based on the advertising weight and the degree-of-targetedness.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: A processing device selects a population of persons and measures sales metrics from the population over a time period and measures an advertising weight over the time period. The processing device determines an effect that the advertising weight has on the sales metrics and additionally calculates values for a degree of targetedness for the advertisement to the population of persons. The processing device determines an effect that the degree of targetedness has on the sales metrics and generates a multi-dimensional model that measures the combined effects of the advertising weight and the degree of targetedness on the sales metrics.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: A processing device selects a population of persons and measures sales metrics from the population over a time period and measures an advertising weight over the time period. The processing device determines an effect that the advertising weight has on the sales metrics and additionally calculates values for a degree of targetedness for the advertisement to the population of persons. The processing device determines an effect that the degree of targetedness has on the sales metrics and generates a multi-dimensional model that measures the combined effects of the advertising weight and the degree of targetedness on the sales metrics.

Abstract: A processing device receives set-top box data, sales data, and advertising data. The processing device associates set-top boxes front the set-top box data with viewers and calculates advertising exposure events for advertisements. The processing device further calculates, for each viewer, an advertising weight as a function of number of exposures of the advertisement as applied to the viewer based on the advertising exposure events. The processing device further calculates, for each viewer, a score representing a degree-of-targetedness between an advertisement campaign and the viewer. The processing device manages the advertisement campaign based on the advertising weight and the degree-of-targetedness.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: A processing device receives set-top box data, sales data, and advertising data. The processing device associates set-top boxes from the set-top box data with viewers and calculates advertising exposure events for advertisements. The processing device further calculates, for each viewer, an advertising weight as a function of number of exposures of the advertisement as applied to the viewer based on the advertising exposure events. The processing device further calculates, for each viewer, a score representing a degree-of-targetedness between an advertisement campaign and the viewer. The processing device manages the advertisement campaign based on the advertising weight and the degree-of-targetedness.

Abstract: This paper presents a practical method for measuring the impact of multiple marketing events on sales, including marketing events that are not traditionally trackable. The technique infers which of several competing media events are likely to have caused a given conversion. The method is tested using hold-out sets, and also a live media experiment for determining whether the method can accurately predict television-generated web conversions.

Abstract: A processing device selects a population of persons and measures sales metrics from the population over a time period and measures an advertising weight over the time period. The processing device determines an effect that the advertising weight has on the sales metrics and additionally calculates values for a degree of targetedness for the advertisement to the population of persons. The processing device determines an effect that the degree of targetedness has on the sales metrics and generates a multi-dimensional model that measures the combined effects of the advertising weight and the degree of targetedness on the sales metrics.

Abstract: A processing device receives set-top box data, sales data, and advertising data. The processing device associates set-top boxes from the set-top box data with viewers and calculates advertising exposure events for advertisements. The processing device further calculates, for each viewer, an advertising weight as a function of number of exposures of the advertisement as applied to the viewer based on the advertising exposure events. The processing device further calculates, for each viewer, a score representing a degree-of-targetedness between an advertisement campaign and the viewer. The processing device manages the advertisement campaign based on the advertising weight and the degree-of-targetedness.

Abstract: A processing device selects a population of persons and measures sales metrics from the population over a time period and measures an advertising weight over the time period. The processing device determines an effect that the advertising weight has on the sales metrics and additionally calculates values for a degree of targetedness for the advertisement to the population of persons. The processing device determines an effect that the degree of targetedness has on the sales metrics and generates a multi-dimensional model that measures the combined effects of the advertising weight and the degree of targetedness on the sales metrics.