CONSUMER IDENTITY RESOLUTION BASED ON TRANSACTION DATA
According to an embodiment, a data processing system for facilitating consumer identity resolution comprises: a first logic module adapted to receive at least two collections of consumer records from at least two different sources; a second logic module adapted to compute first trust scores for first data fields of the first collection and second trust scores for second data fields of the second collection; a third logic module adapted to generate a master collection of consumer records comprising at least one master consumer record that is correlated to a record from the first collection and a record from the second collection, the correlation being based on at least on the trust scores; and a fourth logic module adapted to receive a set of contextual transaction data. The data processing system is adapted to identify a consumer based on the contextual transaction data and the master collection of consumer records.
1 . A data processing system for facilitating consumer identity resolution, the system comprising:
a first logic module adapted to receive at least two collections of consumer records from at least two different sources, the first collection including a set of first data fields and the second collection including a set of second data fields;
a second logic module adapted to compute a set of first trust scores for the first data fields and a set of second trust scores for the second data fields;
a third logic module adapted to generate a master collection of consumer records comprising at least one master consumer record that is correlated to at least one record from the first collection and to at least one record from the second collection, the correlation being based on at least one of the first trust scores and at least one of the second trust scores; and
a fourth logic module adapted to receive a set of contextual transaction data,
wherein the data processing system is adapted to identify a consumer based on the contextual transaction data and the master collection of consumer records.
2 . The data processing system of claim 1 , wherein the system is adapted to select at least one electronic offer based on the identification of the consumer.
3 . The data processing system of claim 2 , wherein the electronic offer is selected in response to a request for a receipt.
4 . The data processing system of claim 2 , wherein the electronic offer is included in a transaction receipt transmitted to a customer data processing system.
5 . The data processing system of claim 4 , wherein the customer data processing system is at least one of: a desktop computer, laptop computer, netbook, electronic notebook, ultra mobile personal computer (UMPC), electronic tablet, client computing device, client terminal, client console, mobile telephone, smartphone, wearable computer, head-mounted computer, or personal digital assistant.
6 . The data processing system of claim 2 , wherein the selection of the electronic offer is based on at least one of: an activity associated with a particular master consumer record, or a consumer attribute associated with a particular master consumer record.
7 . The data processing system of claim 2 , wherein the selection of the electronic offer is based on determining whether an offer has previously been activated in connection with a particular master consumer record.
8 . The data processing system of claim 2 , wherein the selection of the electronic offer is based on a transaction log.
9 . The data processing system of claim 2 , wherein the selection of the electronic offer comprises selecting multiple master records and scoring a likelihood that the contextual transaction data relates to a particular record included in the multiple master records.
10 . The data processing system of claim 2 , wherein the selection of the electronic offer is further based on confidence scores that indicate the frequency with which a particular value occurs in a data field of correlated records.
11 . The data processing system of claim 1 , wherein the system is further adapted to transmit a list of offers that have been activated for a particular master consumer record, the transmission being in response to a request from a retailer, and wherein the contextual transaction data includes a credential supplied by the consumer during a transaction.
12 . The data processing system of claim 1 , wherein the contextual transaction data includes information regarding at least one of: a universal product code, a quantity of product purchased, a number of items purchased, a transaction amount, at least a portion of a credit card number used, a payment identifier used, a secure payment hash key, a data processing system or facility, time, date, one or more offers activated or redeemed, customer name, phone number, pin number, password, code, loyalty card number, RFID data, a device identifier, one or more items that were purchased in a previous or concurrent transaction, or a transaction number.
13 . The data processing system of claim 1 , wherein at least one trust score is modified subsequently based on at least one of: an update from at least one of the two sources, new transaction data, or a confidence score that indicates the frequency with which a particular value occurs in a data field of correlated records.
14 . The data processing system of claim 1 , wherein the fourth logic module is further adapted to correlate transactions from a plurality of different retail stores with the at least one master consumer record.
15 . The data processing system of claim 1 , wherein the first logic module is further adapted to receive updates to the at least two collections from the at least two different sources over time, and the third logic module is further adapted to revise the correlations based thereon.
16 . The data processing system of claim 1 , wherein the third logic module is further adapted to link each value of the at least one master consumer record to a particular collection, of the at least two collections, from which the value originated.
17 . The data processing system of claim 1 , wherein the first data fields include aggregated transaction data.
18 . The data processing system of claim 1 , further comprising a fifth logic module adapted to identify one or more values for a particular data field of the at least one master consumer record in response to a query that requests the one or more values for the particular field, by querying a first consumer record of the first collection for a first value pertaining to a first data field, querying a second consumer record of the second collection for a second value pertaining to a second data field, and deciding which one or more values of the first value and the second value to return based at least on different trust scores assigned to the first data field and the second data field.
19 . The data processing system of claim 1 , wherein the third logic module is configured to determine which one or more values of a first value, pertaining to a first data field of the first collection, and a second value, pertaining to a second data field of the second collection, to store in the at least one master consumer record based at least on the different trust scores.
20 . The data processing system of claim 1 , wherein the fourth logic module is adapted to receive particular contextual transaction data in a query that selects for a first value in a particular data field of the master collection, and, responsive to the first value being assigned to the particular data field in a plurality of master consumer records, identify one or more master consumer records from which to return information based on trust scores assigned to different data fields of the at least two collections from which the plurality of master consumer records were generated.
21 . The data processing system of claim 1 , wherein the first source is a first retailer and the second source is a second retailer.
22 . A method for facilitating consumer identity resolution, the method comprising:
receiving at least two collections of consumer records from at least two different sources, the first collection including a set of first data fields and the second collection including a set of second data fields;
computing a set of first trust scores for the first data fields and a set of second trust scores for the second data fields;
generating a master collection of consumer records comprising at least one master consumer record that is correlated to at least one record from the first collection and to at least one record from the second collection, the correlation being based on at least one of the first trust scores and at least one of the second trust scores; and
receiving a set of contextual transaction data,
identifying a consumer based on the contextual transaction data and the master collection of consumer records.
23 . The method of claim 22 , further comprising selecting at least one electronic offer based on the identification of the consumer.
24 . The method of claim 23 , further comprising including the at least one electronic offer in a transaction receipt transmitted to a customer data processing system.
25 . The method of claim 22 , further comprising transmitting a list of offers that have been activated for a particular master consumer record, the transmission being in response to a request from a retailer, and wherein the contextual transaction data includes a credential supplied by the consumer during a transaction.
26 . The method of claim 22 , further comprising correlating transactions from a plurality of different retail stores with the at least one master consumer record.
27 . The method of claim 22 , further comprising receiving updates to the at least two collections from the at least two different sources over time, and revising the correlations based thereon.
28 . The method of claim 22 , further comprising determining which one or more values of a first value, pertaining to a first data field of the first collection, and a second value, pertaining to a second data field of the second collection, to store in the at least one master consumer record based at least on the different trust scores.
29 . The method of claim 22 , further comprising receiving particular contextual transaction data in a query that selects for a first value in a particular data field of the master collection, and, responsive to the first value being assigned to the particular data field in a plurality of master consumer records, identifying one or more master consumer records from which to return information based on trust scores assigned to different data fields of the at least two collections from which the plurality of master consumer records were generated.
30 . One or more computer readable media storing program instructions adapted to facilitate consumer identity resolution, wherein execution of the program instructions by a data processing system causes:
receiving at least two collections of consumer records from at least two different sources, the first collection including a set of first data fields and the second collection including a set of second data fields;
computing a set of first trust scores for the first data fields and a set of second trust scores for the second data fields;
generating a master collection of consumer records comprising at least one master consumer record that is correlated to at least one record from the first collection and to at least one record from the second collection, the correlation being based on at least one of the first trust scores and at least one of the second trust scores; and
receiving a set of contextual transaction data,
identifying a consumer based on the contextual transaction data and the master collection of consumer records.