A system, computer program product, and method for activation-based marketing are presented. In one embodiment, the system includes one or more data storage devices configured to store demographic data, healthcare utilization data, and response data associated with a target individual. The system may include a server coupled to the one or more data storage devices. The server may be suitably programmed to determine a life stage associated with a target individual, determine an attitudinal segment associated with the target individual, and determine a response model associated with the target individual. The server may assign the target individual to at least one of a predetermined set of segmentation groups in response to the life stage, the attitudinal segment, and the response model associated with the individual. The system may generate a personalized communication modality tailored to the target individual in response to the segmentation group assigned to the target individual.

A system, computer program product, and method for activation-based marketing are presented. In one embodiment, the system includes one or more data storage devices configured to store demographic data, healthcare utilization data, and response data associated with a target individual. The system may include a server coupled to the one or more data storage devices. The server may be suitably programmed to determine a life stage associated with a target individual, determine an attitudinal segment associated with the target individual, and determine a response model associated with the target individual. The server may assign the target individual to at least one of a predetermined set of segmentation groups in response to the life stage, the attitudinal segment, and the response model associated with the individual. The system may generate a personalized communication modality tailored to the target individual in response to the segmentation group assigned to the target individual.

Some implementations use the same exposed and unexposed (i.e., control) groups for foot traffic and transaction (e.g., sales) attribution analysis. Some implementations are configured to preserve user data privacy, e.g., the processing entity need not access user-specific sales data that is separately maintained by a third party that provides sales aggregate data.

Some implementations use the same exposed and unexposed (i.e., control) groups for foot traffic and transaction (e.g., sales) attribution analysis. Some implementations are configured to preserve user data privacy, e.g., the processing entity need not access user-specific sales data that is separately maintained by a third party that provides sales aggregate data.

Implementations described herein provide systems and methods for vehicle telematics control. In one implementation, telematics data for a particular user is obtained. The telematics data is captured using at least one sensor associated with a vehicle in connection with an operation of the vehicle by the particular user. A privacy vault of the particular user is identified. The privacy vault has a user-defined access permission set for at least one service provider. The telematics data is stored in the privacy vault. Access to the telematics data stored in the privacy vault by the at least one service provider is controlled. The access to the telematics data controlled according to the user-defined access permission set for the at least one service provider.

A method, apparatus and computer program product are provided for providing auto-replenishment of an inventory of promotions. Auto-replenishment amounts and dates may be determined based on a variety of factors including current inventory, outstanding promotions, redemption ratios and redemption rates. Redemption ratios and redemption rates may be characterized based on provider information, consumer information, and/or promotion information. Auto-replenishment may result in a smoothed redemption curve and optimal impact to the provider.

As described herein, a collaborative filtering system, method, and computer program provide a model used to calculate ranked predictions for subscribers. In use, data is received which correlates subscribers of a service provider with offers provided to the subscribers by the service provider, wherein each correlation is associated in the data with an indication of whether the offer was accepted by the subscriber. From the data, a plurality of unique correlations between subscribers and offers are determined. An implicit ranking is calculated for each unique correlation, based on the associated indication of acceptance for correlations matching the unique correlation. Input data is generated that includes each unique correlation with the implicit ranking calculated for the unique correlation. The input data is processed utilizing a collaborative filtering algorithm to generate a model configured to provide predicted implicit rankings for new correlations between subscribers and offers.

As described herein, a collaborative filtering system, method, and computer program provide a model used to calculate ranked predictions for subscribers. In use, data is received which correlates subscribers of a service provider with offers provided to the subscribers by the service provider, wherein each correlation is associated in the data with an indication of whether the offer was accepted by the subscriber. From the data, a plurality of unique correlations between subscribers and offers are determined. An implicit ranking is calculated for each unique correlation, based on the associated indication of acceptance for correlations matching the unique correlation. Input data is generated that includes each unique correlation with the implicit ranking calculated for the unique correlation. The input data is processed utilizing a collaborative filtering algorithm to generate a model configured to provide predicted implicit rankings for new correlations between subscribers and offers.

Disclosed is a method in which an electronic apparatus processes information, the method including acquiring information for requesting access to a second page from a user terminal through a first page, confirming address information reflecting information on the first page, and providing the second page to the user terminal according to the address information.

A method, apparatus and computer program product are provided for providing auto-replenishment of an inventory of promotions. Auto-replenishment amounts and dates may be determined based on a variety of factors including current inventory, outstanding promotions, redemption ratios and redemption rates. Redemption ratios and redemption rates may be characterized based on provider information, consumer information, and/or promotion information. Auto-replenishment may result in a smoothed redemption curve and optimal impact to the provider.