Abstract: A method includes receiving a first data set and a second data set. The first data set may include anonymized transaction data that represents purchase transactions made by customers of a merchant. The second data set may include anonymized transaction data that represents purchase transactions made by cardholders in a payment network. The method further includes filtering the second data set to remove therefrom data relating to cardholders who are not customers of the merchant, and processing the first data set and the filtered second data set using a probabilistic engine to establish linkages between data in the first data set and data in the filtered second data set. The method may also include analyzing data in the filtered second data set to generate one or more of shopping habits data, classification data and attribute data with respect to customers of the merchant.

Abstract: A method for associating transaction card accounts with life stage segments is described. The method includes analyzing survey results to define the plurality of life stage segments based on at least one of demographics, transaction categories, and card usage. The method further includes creating at least one spending profile for a life stage target group that includes transaction card holders within at least one of the defined life stages for which a marketing campaign is targeted, developing a survey-based life stage model based on the target group and the profiles, creating a transaction data-based life stage model by applying the survey-based life stage model to a portion of the transaction data, applying the transaction-based life stage model to the transaction data to identifies cardholder accounts included within the life stage target group, and ranking the transaction card accounts stored within the database based on a likelihood the accounts are included within the target group.

Abstract: Systems, methods, means, computer program code and computerized processes include receiving a first set of de-identified transaction data from a first transaction data source, receiving a second set of de-identified transaction data from a second transaction data source, filtering the first and second sets of de-identified transaction data to identify transactions associated with at least a first entity and to create first and second filtered data sets, removing data associated with an identifier field for each of the transactions in the first filtered data set to created a de-identified first data set, removing data associated with an identifier field for each of the transactions in the second filtered data set to create a de-identified second data set, and processing the first and second de-identified data sets using a probabilistic engine to establish a linkage between data in each data set.

Abstract: Systems, methods, means, computer program code and computerized processes include receiving a first set of de-identified transaction data from a first transaction data source, receiving a second set of de-identified transaction data from a second transaction data source, filtering the first and second sets of de-identified transaction data to identify transactions associated with at least a first entity and to create first and second filtered data sets, removing data associated with an identifier field for each of the transactions in the first filtered data set to created a de-identified first data set, removing data associated with an identifier field for each of the transactions in the second filtered data set to create a de-identified second data set, and processing the first and second de-identified data sets using a probabilistic engine to establish a linkage between data in each data set.

Abstract: According to some embodiments, a proximity-sensitivity score is determined for each of a plurality of merchants. The proximity-sensitivity scores may indicate, for example, a likelihood that potential offers from the merchants would be accepted by customers based on distances between customer locations and merchant locations. An indication of a customer's current location may be received, and a selection engine may automatically select for a customer, in substantially real time, at least one selected offer from a plurality of potential offers based at least in part on proximity-sensitivity scores and the customer's current location. Data associated with the selected offer may then be transmitted, via a wireless communication network, to a mobile device associated with the customer.

Abstract: A method for associating transaction card accounts with life stage segments is described. The method includes analyzing survey results to define the plurality of life stage segments based on at least one of demographics, transaction categories, and card usage. The method further includes creating at least one spending profile for a life stage target group that includes transaction card holders within at least one of the defined life stages for which a marketing campaign is targeted, developing a survey-based life stage model based on the target group and the profiles, creating a transaction data-based life stage model by applying the survey-based life stage model to a portion of the transaction data, applying the transaction-based life stage model to the transaction data to identifies cardholder accounts included within the life stage target group, and ranking the transaction card accounts stored within the database based on a likelihood the accounts are included within the target group.

Abstract: A computer-based method for enrolling financial transaction cardholders into a payment card program that includes features that are directed to an empty nester segment of society is described. The method includes creating at least one spending profile representing an empty nester target group. The empty nester target group includes transaction cardholders within the empty nester segment of society targeted for receiving a marketing campaign. The method also includes storing in the database transaction data for transaction card accounts, identifying cardholders included within the empty nester target group by comparing the transaction data to the at least one empty nester spending profile, and offering a payment card program having at least one rewards feature directed to the empty nester segment of society to the cardholders identified as being within the empty nester target group.