U.S. patent application number 14/324471 was filed with the patent office on 2016-01-07 for systems and methods for categorizing neighborhoods based on payment card transactions.
The applicant listed for this patent is MasterCard International Incorporated. Invention is credited to Pedro J. Chavarria, Kristofer Perez.
Application Number | 20160005061 14/324471 |
Document ID | / |
Family ID | 55017280 |
Filed Date | 2016-01-07 |
United States Patent
Application |
20160005061 |
Kind Code |
A1 |
Chavarria; Pedro J. ; et
al. |
January 7, 2016 |
SYSTEMS AND METHODS FOR CATEGORIZING NEIGHBORHOODS BASED ON PAYMENT
CARD TRANSACTIONS
Abstract
A computer implemented method for categorizing neighborhoods
based on cardholder transactions is provided. The method is
implemented using a computing device having a processor
communicatively coupled to a memory. The method includes receiving
a plurality of payment transactions from a plurality of
cardholders, generating a list of cardholders based on the
plurality of payment transactions, determining one or more life
stage segments for each cardholder based on the plurality of
payment transactions, determining one or more geographic regions
based in part on the plurality of payment transactions where each
geographic region contains a plurality of cardholders, determining
a lifestyle category for at least one geographic region of the one
or more geographic regions based on the one or more life stage
segments of each of the cardholders associated with the
corresponding geographic region, and providing a lifestyle report
for the at least one geographic region.
Inventors: |
Chavarria; Pedro J.; (New
York, NY) ; Perez; Kristofer; (New York, NY) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
MasterCard International Incorporated |
Purchase |
NY |
US |
|
|
Family ID: |
55017280 |
Appl. No.: |
14/324471 |
Filed: |
July 7, 2014 |
Current U.S.
Class: |
705/7.34 |
Current CPC
Class: |
G06Q 30/0205 20130101;
G06Q 40/12 20131203 |
International
Class: |
G06Q 30/02 20060101
G06Q030/02; G06Q 40/00 20060101 G06Q040/00 |
Claims
1. A computer implemented method for categorizing neighborhoods
based on cardholder transactions, said method using a computing
device having a processor communicatively coupled to a memory, said
method comprising: receiving, by the processor, a plurality of
payment transactions from a plurality of cardholders; generating,
by the processor, a list of cardholders based on the plurality of
payment transactions; determining, by the processor, one or more
life stage segments for each cardholder of the list of cardholders
based on the plurality of payment transactions; determining, by the
processor, a geographic region containing a plurality of
cardholders from the list of cardholders based in part on the one
or more life stage segments associated with each of the plurality
of cardholders contained within the geographic region; determining,
by the processor, a lifestyle category for the geographic region
based on the one or more life stage segments of each of the
cardholders associated with the geographic region; and providing,
by the processor, a lifestyle report for the geographic region.
2. The method in accordance with claim 1, wherein determining one
or more life stage segments for each cardholder further comprises:
determining, by the processor, a score profile to assign to each
payment transaction of the plurality of payment transactions
associated with a cardholder; calculating, by the processor, one or
more life stage segment probabilities based on the assigned score
profiles; and determining, by the processor, one or more life stage
segments for the cardholder based on the calculated one or more
life stage segment probabilities.
3. The method in accordance with claim 2, further comprising:
generating groups of payment transactions based on the payment
transactions associated with the cardholder; determining, by the
processor, a score profile to assign to each group of payment
transactions; and recalculating, by the processor, the one or more
life stage segment probabilities based on the assigned score
profiles and the calculated one or more life stage segment
probabilities.
4. The method in accordance with claim 2, wherein determining a
score profile is based on a merchant category associated with the
payment transaction.
5. The method in accordance with claim 3, wherein generating groups
of payment transactions is based on the merchant category of the
payment transactions in the group of payment transactions.
6. The method in accordance with claim 1, wherein determining a
lifestyle category further comprises: compiling, by the processor,
a total number for each life stage segment associated with the
plurality of cardholders associated with the geographic region;
determining, by the processor, that the total number for at least
one life stage segment exceeds a predetermined threshold; and
determining, by the processor, a lifestyle category for the
geographic region for each life stage segment that exceeded the
associated predetermined threshold.
7. The method in accordance with claim 1, wherein determining a
lifestyle category further comprises: compiling, by the processor,
a total number for each life stage segment associated with the
plurality of cardholders associated with the geographic region;
determining, by the processor, a lifestyle category for the
geographic region based on the life stage segment with the greatest
total number compared to the other total numbers of life stage
segments.
8. The method in accordance with claim 1, wherein determining a
geographic region further comprises: determining, by the processor,
a proposed geographic region, where the proposed geographic region
includes a plurality of cardholders to exceed a first predetermined
threshold; determining, by the processor, the one or more life
stage segments associated with each of the plurality of cardholders
in the proposed geographic region; determining, by the processor,
that a number of cardholders associated with a particular life
stage segment exceeds a second predetermined threshold, where the
determination is made for each life stage segment with at least one
associated cardholder in the proposed geographic region; and
identifying the proposed geographic region as a geographic
region.
9. The method in accordance with claim 1, wherein determining a
geographic region further comprises: determining, by the processor,
a proposed geographic region, where the proposed geographic region
includes a plurality of cardholders to exceed a first predetermined
threshold; determining, by the processor, the one or more life
stage segments associated with each of the plurality of cardholders
in the proposed geographic region; determining, by the processor,
that a number of cardholders associated with a particular life
stage segment exceeds a second predetermined threshold, where the
determination is made for each life stage segment with at least one
associated cardholder in the proposed geographic region; expanding,
by the processor, the proposed geographic region until the number
of cardholders for each life stage segment with at least one
associated cardholder in the proposed geographic region exceeds the
second predetermined threshold; and assigning the proposed
geographic region as a geographic region.
10. A computer system for categorizing neighborhoods based on
cardholder transactions, said computer system comprising: a memory
device for storing data; and one or more processors in
communication with said memory device, said one or more processors
programmed to: receive a plurality of payment transactions from a
plurality of cardholders; generate a list of cardholders based on
the plurality of payment transactions; determine one or more life
stage segments for each cardholder of the list of cardholders based
on the plurality of payment transactions; determine a geographic
region containing a plurality of cardholders from the list of
cardholders based in part on the one or more life stage segments
associated with each of the plurality of cardholders contained
within the geographic region; determine a lifestyle category for
the geographic region based on the one or more life stage segments
of each of the cardholders associated with the geographic region;
and provide a lifestyle report for the geographic region.
11. The system in accordance with claim 10, wherein said processor
is further programmed to: determine a score profile to assign to
each payment transaction of the plurality of payment transactions
associated with a cardholder; calculate one or more life stage
segment probabilities based on the assigned score profiles; and
determine one or more life stage segments for the cardholder based
on the calculated one or more life stage segment probabilities.
12. The system in accordance with claim 10, wherein said processor
is further programmed to: generate groups of payment transactions
based on the payment transactions associated with the cardholder;
determine a score profile to assign to each group of payment
transactions; and recalculate the one or more life stage segment
probabilities based on the assigned score profiles and the
calculated one or more life stage segment probabilities.
13. The system in accordance with claim 11, wherein said processor
is further programmed to determine a score profile based on a
merchant category associated with the payment transaction.
14. The system in accordance with claim 12, wherein said processor
is further programmed to generate groups of payment transactions
based on the merchant category of the payment transactions in the
group of payment transactions.
15. The system in accordance with claim 10, wherein said processor
is further programmed to: compile a total number for each life
stage segment associated with the plurality of cardholders
associated with the geographic region; determine that the total
number for at least one life stage segment exceeds a predetermined
threshold; and determine a lifestyle category for the geographic
region for each life stage segment that exceeded the associated
predetermined threshold.
16. The system in accordance with claim 10, wherein said processor
is further programmed to: compile a total number for each life
stage segment associated with the plurality of cardholders
associated with the geographic region; determine a lifestyle
category for the geographic region based on the life stage segment
with the greatest total number compared to the other total numbers
of life stage segments.
17. A non-transitory computer-readable storage medium having
computer-executable instructions embodied thereon, wherein when
executed by a computing device having at least one processor
coupled to a memory device, the computer-executable instructions
cause the processor to: receive a plurality of payment transactions
from a plurality of cardholders; generate a list of cardholders
based on the plurality of payment transactions; determine one or
more life stage segments for each cardholder of the list of
cardholders based on the plurality of payment transactions;
determine a geographic region containing a plurality of cardholders
from the list of cardholders based in part on the one or more life
stage segments associated with each of the plurality of cardholders
contained within the geographic region; determine a lifestyle
category for the geographic region based on the one or more life
stage segments of each of the cardholders associated with the
geographic region; and provide a lifestyle report for the
geographic region.
18. The non-transitory computer-readable storage medium of claim
17, wherein the computer-executable instructions further cause the
processor to: determine a score profile to assign to each payment
transaction of the plurality of payment transactions associated
with a cardholder; calculate one or more life stage segment
probabilities based on the assigned score profiles; and determine
one or more life stage segments for the cardholder based on the
calculated one or more life stage segment probabilities.
19. The non-transitory computer-readable storage medium of claim
17, wherein the computer-executable instructions further cause the
processor to: generate groups of payment transactions based on the
payment transactions associated with the cardholder; determine a
score profile to assign to each group of payment transactions; and
recalculate the one or more life stage segment probabilities based
on the assigned score profiles and the calculated one or more life
stage segment probabilities.
20. The non-transitory computer-readable storage medium of claim
17, wherein the computer-executable instructions further cause the
processor to: compile a total number for each life stage segment
associated with the plurality of cardholders associated with the
geographic region; determine that the total number for a particular
life stage segment exceeds a predetermined threshold; and determine
a lifestyle category for the geographic region for each life stage
segment that exceeded the associated predetermined threshold.
Description
BACKGROUND OF THE DISCLOSURE
[0001] The field of the disclosure relates generally to
categorizing a neighborhood of persons, and more specifically to
method and systems for modeling payment card transactions for a
group of cardholders residing within a pre-defined neighborhood
such that the neighborhood can be categorized within a life
stage.
[0002] A life stage segment is a group of consumers who are
classified based on shared demographics and/or certain
differentiating spending behaviors. Determining the life stages of
neighborhoods can be important. For example, realtors may like to
know the demographics of a neighborhood to be able to point
potential buyers to a desired neighborhood. Knowing the
demographics also helps landlords and realtors to better direct
their advertising materials. For example, if a potentially buyer
has small children, then that buyer probably wants to be shown
houses in neighborhoods with other families having small
children.
[0003] Generally, people in different life stages have different
spending behaviors. However, a lack of detailed consumer
information coupled with an inability to access private information
makes it difficult to determine the life stage of a neighborhood
without thoroughly investigating that neighborhood. At least one
result is that realtors and landlords waste resources on poorly
targeted promotional campaigns. Further, potential buyers and
renters may get frustrated with being directed to places to live
that don't fit their life stage.
[0004] Realtors and landlords would like to focus their efforts
more effectively to make their buyers and renters happy. In
addition, it is desired that the categorizing of neighborhoods,
apartment complexes, and/or apartment buildings, be accomplished
without continuous gathering, storing, and updating of consumer
data. A system that is configured to categorize a neighborhood with
different life stages would help direct potential buyers and
renters to places to live that are more relevant to them.
BRIEF DESCRIPTION OF THE DISCLOSURE
[0005] In one aspect, a computer implemented method for
categorizing neighborhoods based on cardholder transactions is
provided. The method is implemented using a computing device having
a processor communicatively coupled to a memory. The method
includes receiving by the processor a plurality of payment
transactions from a plurality of cardholders, generating by the
processor a list of cardholders based on the plurality of payment
transactions, determining by the processor one or more life stage
segments for each cardholder based on the plurality of payment
transactions, determining by the processor one or more geographic
regions based in part on the plurality of payment transactions
where each geographic region contains a plurality of cardholders,
determining by the processor a lifestyle category for at least one
geographic region of the one or more geographic regions based on
the one or more life stage segments of each of the cardholders
associated with the corresponding geographic region, and providing
by the processor a lifestyle report for the at least one geographic
region.
[0006] In another aspect, a computer system for categorizing
neighborhoods based on cardholder transactions is provided. The
computer system includes a memory device for storing data and one
or more processors in communication with the memory device. The one
or more processors are programmed to receive a plurality of payment
transactions from a plurality of cardholders, generate a list of
cardholders based on the plurality of payment transactions,
determine one or more life stage segments for each cardholder based
on the plurality of payment transactions, determine one or more
geographic regions based in part on the plurality of payment
transactions where each geographic region contains a plurality of
cardholders, determine a lifestyle category for at least one
geographic region of the one or more geographic regions based on
the one or more life stage segments of each of the cardholders
associated with the corresponding geographic region, and provide a
lifestyle report for the at least one geographic region.
[0007] In yet another aspect, a computer-readable storage medium
having computer-executable instructions embodied thereon is
provided. When executed by a computing device having at least one
processor coupled to a memory device, the computer-executable
instructions cause the processor to receive a plurality of payment
transactions from a plurality of cardholders, generate a list of
cardholders based on the plurality of payment transactions,
determine at least one life stage segment for each cardholder based
on the plurality of payment transactions, determine one or more
geographic regions based in part on the plurality of payment
transactions where each geographic region contains a plurality of
cardholders, determine a lifestyle category for at least one
geographic region of the one or more geographic regions based on
the one or more life stage segments of each of the cardholders
associated with the corresponding geographic region, and provide a
lifestyle report for the at least one geographic region.
BRIEF DESCRIPTION OF THE DRAWINGS
[0008] FIGS. 1-7 show example embodiments of the methods and
systems described herein.
[0009] FIG. 1 is a schematic diagram illustrating an example
multi-party transaction card industry system for enabling ordinary
payment-by-card transactions in which merchants and card issuers do
not need to have a one-to-one special relationship.
[0010] FIG. 2 is a simplified block diagram of an example computer
system used for determining the lifestyle categories of geographic
regions in accordance with one example embodiment of the present
disclosure.
[0011] FIG. 3 illustrates an example configuration of a client
system shown in FIG. 2, in accordance with one embodiment of the
present disclosure.
[0012] FIG. 4 illustrates an example configuration of the server
system shown in FIG. 2, in accordance with one embodiment of the
present disclosure.
[0013] FIG. 5 is a flowchart illustrating an example of the process
of determining the lifestyle category of a geographic region from
cardholder transaction using the system shown in FIG. 2, in
accordance with one embodiment of the disclosure.
[0014] FIG. 6 is a flowchart illustrating an example of the process
of determining one or more life stage segments for a cardholder
using the system shown in FIG. 2, in accordance with one embodiment
of the disclosure.
[0015] FIG. 7 is a diagram of components of one or more example
computing devices that may be used in the system shown in FIG.
2.
DETAILED DESCRIPTION OF THE DISCLOSURE
[0016] The following detailed description illustrates embodiments
of the disclosure by way of example and not by way of limitation.
The description clearly enables one skilled in the art to make and
use the disclosure, describes several embodiments, adaptations,
variations, alternatives, and uses of the disclosure, including
what is presently believed to be the best mode of carrying out the
disclosure. The disclosure is described as applied to an example
embodiment, namely, methods and systems for providing cardholders
the most traveled paths or routes taken by other cardholders. More
specifically, the disclosure describes a lifestyle determining
("LD") computing device configured to collect transaction data for
a plurality of payment cardholders transacting with a plurality of
merchants, determine the life stage segment of multiple cardholders
residing in a geographic region, determine a lifestyle category for
the geographic region based on the cardholders residing in that
geographic region, and generate a report for that geographic
region.
[0017] In the example embodiment, the life stage segments and the
lifestyle categories use the same categorizations which include,
but are not limited to, singles, recent couples/recently married,
new parents, parents with teenagers, and retirement. In other
embodiments, the life stage segments and the lifestyle categories
may use different categorizations. For example, the life stage
segment may include gender, age group, profession type, marital
status, and family status.
[0018] In the example embodiment, the LD computing device is
configured for use with a payment card processing network such as,
for example, an interchange network. The LD computing device
includes a memory device and a processor in communication with the
memory device and is programmed to communicate with the payment
network to receive transaction information for a plurality of
cardholders. The payment network is configured to process payment
card transactions between the merchant and its acquirer bank, and
the cardholder and their issuer bank. Transaction information
includes data relating to purchases made by cardholders at various
merchants during a predetermined time period, including at least a
unique identifier for each cardholder, a merchant identifier, a
merchant category, a geographic location of a merchant, a
transaction amount, and a date and time for the transaction. In
some embodiments, the plurality of purchases made by the
cardholders are related to each other as being in the same market
category, for example, but not limited to, a dining category, an
events category, a night club category, or an activities
category.
[0019] In the example embodiment, a payment card processing network
receives a plurality of payment transactions for processing. The
processing network stores these payment transactions in a database.
The LD computing device is in communication with the payment
network database. The LD computing device receives the transactions
stored in the database. Each transaction includes at least a unique
identifier for each cardholder, a merchant identifier, a merchant
category, a geographic location of a merchant, a transaction
amount, and a date and time for the transaction.
[0020] In the example embodiment, using the plurality of payment
transactions, the LD computing device determines the cardholders
that have completed at least one transaction during a predetermined
time period. The LD computing device determines one or more life
stage segment(s) for each cardholder. In the example embodiment,
the LD computing device determines that the cardholder belongs to
one life stage segment, such as, but not limited to, singles,
recent couples/recently married, new parents, parents with
teenagers, and retirement. In other embodiments, the LD computing
device determines that the cardholder belongs to multiple life
stage segments.
[0021] In the example embodiment, the LD computing device defines
geographic regions based on the determined cardholder life segments
and the received transaction data. A geographic region may be any
geographic identifier including, for example and without
limitation, a postal code, a city/town/municipality, a neighborhood
in a city/town/municipality, GPS coordinates, a county, a single
city block, an apartment complex, a street, a street address, and
sub-divisions of any of the preceding geographic identifiers. In
some embodiments, the geographic region may be predefined by the
user or may be determined by the LD computing device. In either
case, a minimum number of cardholders in the same life stage
segment are required for a defined geographic region to ensure that
no personally identifiable information may be obtained from the
classification. In the example embodiment, at least three (3)
cardholders in a life stage segment are needed to determine a
geographic region. If it is determined that there is less than
three (3) cardholders in a life stage segment of a geographic
region, then the system or the user must re-define a larger
geographic region.
[0022] To define a geographic region, the LD computing device
identifies a minimum number of cardholders with the same life stage
segment living in close proximity. For example, in some places with
high population density, e.g., New York City, the LD computing
device identifies seven cardholders living in the same apartment
building. The LD computing device identifies three of those
cardholders to be in the "new parents" life stage segment, three of
them in the "retired" life stage segment, and one cardholder in the
"singles" life stage segment. Because there is only one cardholder
in the "singles" life stage segment, which is below the required
minimum number for a geographic region, the LD computing device
expands the geographic region until the number of cardholders in
each life stage segment with at least one cardholder exceeds the
minimum. In the example embodiment, the LD computing device ignores
life stage segments with zero cardholders. In the above example,
the LD computing device expands the proposed geographic region to
include a neighboring building which may add 2 "new parents", 1
"retired", and 3 "singles" cardholders. Since no life stage segment
with cardholders is below the minimum, the LD computing device
defines those two buildings as one geographic region. If the second
building had added a single cardholder in a different life stage
segment, then the LD computing device would expand the proposed
geographic region again. In other places with lower population
density, e.g., rural or suburban cardholders may be more spread out
and the LD computing device may only be able to find three
cardholders of the same life stage segment on a street or a block,
rather than an apartment building and define the geographic region
to be that street or block.
[0023] For each geographic region, the LD computing device
determines a lifestyle category for the geographic region based on
the life stage segments of the cardholders associated with that
geographic region. In some embodiments, the LD computing device may
determine a lifestyle category for a geographic region based on the
life stage segment with the most cardholders in that geographic
region. For example, a majority or more, such as 7 of the 10
cardholders in a geographic region are in the "new parents" life
stage segment, then the LD computing device determines that the
geographic region is in the "new parents" lifestyle category.
However, there may not be a majority of cardholders in one life
stage segment, therefore in other embodiments, the LD computing
device may determine a lifestyle category for a geographic region
based on percentages (i.e., the lifestyle category is determined
based on the life stage segment with the highest percentage of
cardholders) or calculated formulas (e.g., if the total number of
cardholders with a particular life stage segment exceeds a
predetermined threshold). In the example embodiment, the lifestyle
categories are the same as the life stage segments, in other
embodiments, multiple life stage segments may be combined to
determine the lifestyle category. In some embodiments, the
lifestyle category is further broken down into sub-categories, such
as multiple children and single child. In some embodiments, a
minimum number of cardholders must reside in a geographic region to
determine a lifestyle category for the geographic region.
[0024] The LD computing device generates a lifestyle report for
each determined geographic region. In some embodiments, the
lifestyle report is a numerical report, showing the numbers of
cardholders belonging to different life stage segments, living in
the geographic region. In other embodiments, the lifestyle report
may graphically represent the lifestyle categories with different
colors representing different lifestyle categories in one or more
geographic regions. The lifestyle report may be displayed as an
overlay of a geographic map. In further embodiments, the lifestyle
report includes the different life stage segments of the different
cardholders in the geographic region.
[0025] In the some embodiments, the LD computing device determines
the life stage segments associated with a cardholder by analyzing
the transactions that the cardholder made. The LD computing device
first analyzes a transaction that a cardholder performed and
determines a score profile to assign to that transaction. The score
profile includes one or more probability adjustments for one or
more life stage segments. In the example embodiment, the LD
computing device assigns the score profile based on the merchant
category of the transaction. In some embodiments, merchants have
associated scoring profiles based on the merchant category, e.g.,
the scoring profile for a retail toy store is different than the
scoring profile for a high-end men's clothing store. In other
embodiments, the scoring profile is associated with an individual
store. Based on the scoring profile of the merchant, the LD
computing device calculates the cardholder's life stage segment
probabilities based on the score profile and any previously
calculated life stage segment probabilities. The life stage segment
probabilities are a collection of probabilities that the cardholder
belongs to one or more life stage segments, where each probability
is associated with a life stage segment. For example, if the
cardholder makes a purchase from a retail toy store, then the LD
computing device increases the probability associated with the
cardholder being in the "new parents" and the "parents with
teenagers" life stage segments.
[0026] The LD computing device checks to see if there are more
transactions to analyze for this cardholder. If there are more
transactions, then the LD computing device analyzes the next
transaction. If there are no more transactions, then the LD
computing device generates one or more groups of transactions. For
example, the LD computing device may generate a group of all of the
transactions at grocery stores, a group of all of the home
improvement store transactions, and a further group of all of the
high-end clothing store transactions. For each group of
transactions, the LD computing device determines a score profile to
assign to the group. For example, the LD computing device analyzes
the group of cardholder transactions at home-improvement stores. In
the analysis, the LD computing device determines that there are a
significant number of moderately-sized transactions during the
weekends and assigns the score profile of a new home owner. In
another example, the LD computing device determines that there are
a significant number of large purchases that primarily occur on
weekdays, then the LD computing device assigns the score profile of
a contractor.
[0027] Once the score profiles are assigned to the groups, the LD
computing device calculates the life stage segment probabilities
for the cardholder based on the assigned score profiles and any
previously calculated life stage segment probabilities. The LD
computing device determines one or more life stage segments to
assign to the cardholder based on the probabilities. In some
embodiments, the LD computing device determines the one or more
life stage segments based on the probabilities exceeding
predetermined thresholds. In other embodiments, the LD computing
device combines multiple probabilities to determine a life stage
segment.
[0028] In some embodiments, cardholder profiles are stored without
including sensitive personal information, also known as personally
identifiable information or PII, in order to ensure the privacy of
individuals associated with the stored data. Personally
identifiable information may include any information capable of
identifying an individual. For privacy and security reasons,
personally identifiable information may be withheld from the
cardholder profiles. In some examples where privacy and security
can otherwise be ensured, or where individuals consent, personally
identifiable information may be retained in the cardholder
profiles. In such examples, personally identifiable information may
be needed to create enhanced financial assessments. In situations
in which the systems discussed herein collect personal information
about individuals including cardholders or merchants, or may make
use of such personal information, the individuals may be provided
with an opportunity to control whether such information is
collected or to control whether and/or how such information is
used. In addition, certain data may be processed in one or more
ways before it is stored or used, so that personally identifiable
information is removed. For example, an individual's identity may
be processed so that no personally identifiable information can be
determined for the individual, or an individual's geographic
location may be generalized where location data is obtained (such
as to a city, ZIP code, or state level), so that a particular
location of an individual cannot be determined Thus, the individual
may have control over how information is collected about the
individual and used by systems including the LD computing
device.
[0029] The methods and systems described herein may be implemented
using computer programming or engineering techniques including
computer software, firmware, hardware, or any combination or subset
wherein a technical effect of the systems and processes described
herein is achieved by performing at least one of the following
steps: (a) receiving a plurality of payment transactions from a
plurality of cardholders; (b) generating a list of cardholders
based on the plurality of payment transactions; (c) determining at
least one life stage segment for each cardholder based on the
plurality of payment transactions; (d) determining an inferred
geographic region associated with each cardholder based on the
plurality of payment transactions; (e) determining a lifestyle
category for at least one inferred geographic region based on the
at least one life stage segments of each of the cardholders
associated with the corresponding inferred geographic region; and
(f) providing, by the processor, a lifestyle report for the at
least one geographic region.
[0030] As used herein, the terms "transaction card," "financial
transaction card," and "payment card" refer to any suitable
transaction card, such as a credit card, a debit card, a prepaid
card, a charge card, a membership card, a promotional card, a
frequent flyer card, an identification card, a prepaid card, a gift
card, and/or any other device that may hold payment account
information, such as mobile phones, Smartphones, personal digital
assistants (PDAs), key fobs, and/or computers. Each type of
transactions card can be used as a method of payment for performing
a transaction.
[0031] In one embodiment, a computer program is provided, and the
program is embodied on a computer readable medium. In an example
embodiment, the system is executed on a single computer system,
without requiring a connection to a server computer. In a further
example embodiment, the system is being run in a Windows.RTM.
environment (Windows is a registered trademark of Microsoft
Corporation, Redmond, Wash.). In yet another embodiment, the system
is run on a mainframe environment and a UNIX.RTM. server
environment (UNIX is a registered trademark of X/Open Company
Limited located in Reading, Berkshire, United Kingdom). In a
further embodiment, the system is run on an iOS.RTM. environment
(iOS is a registered trademark of Cisco Systems, Inc. located in
San Jose, Calif.). In yet a further embodiment, the system is run
on a Mac OS.RTM. environment (Mac OS is a registered trademark of
Apple Inc. located in Cupertino, Calif.). The application is
flexible and designed to run in various different environments
without compromising any major functionality. In some embodiments,
the system includes multiple components distributed among a
plurality of computing devices. One or more components are in the
form of computer-executable instructions embodied in a
computer-readable medium. The systems and processes are not limited
to the specific embodiments described herein. In addition,
components of each system and each process can be practiced
independently and separately from other components and processes
described herein. Each component and process can also be used in
combination with other assembly packages and processes.
[0032] In one embodiment, a computer program is provided, and the
program is embodied on a computer readable medium and utilizes a
Structured Query Language (SQL) with a client user interface
front-end for administration and a web interface for standard user
input and reports. In another embodiment, the system is web enabled
and is run on a business-entity intranet. In yet another
embodiment, the system is fully accessed by individuals having an
authorized access outside the firewall of the business-entity
through the Internet. In a further embodiment, the system is being
run in a Windows.RTM. environment (Windows is a registered
trademark of Microsoft Corporation, Redmond, Wash.). The
application is flexible and designed to run in various different
environments without compromising any major functionality.
[0033] As used herein, an element or step recited in the singular
and preceded with the word "a" or "an" should be understood as not
excluding plural elements or steps, unless such exclusion is
explicitly recited. Furthermore, references to "example embodiment"
or "one embodiment" of the present disclosure are not intended to
be interpreted as excluding the existence of additional embodiments
that also incorporate the recited features.
[0034] As used herein, the term "database" may refer to either a
body of data, a relational database management system (RDBMS), or
to both. A database may include any collection of data including
hierarchical databases, relational databases, flat file databases,
object-relational databases, object oriented databases, and any
other structured collection of records or data that is stored in a
computer system. The above examples are for example only, and thus
are not intended to limit in any way the definition and/or meaning
of the term database. Examples of RDBMS's include, but are not
limited to including, Oracle.RTM. Database, MySQL, IBM.RTM. DB2,
Microsoft.RTM. SQL Server, Sybase.RTM., and PostgreSQL. However,
any database may be used that enables the systems and methods
described herein. (Oracle is a registered trademark of Oracle
Corporation, Redwood Shores, Calif.; IBM is a registered trademark
of International Business Machines Corporation, Armonk, N.Y.;
Microsoft is a registered trademark of Microsoft Corporation,
Redmond, Wash.; and Sybase is a registered trademark of Sybase,
Dublin, Calif.)
[0035] The term processor, as used herein, may refer to central
processing units, microprocessors, microcontrollers, reduced
instruction set circuits (RISC), application specific integrated
circuits (ASIC), logic circuits, and any other circuit or processor
capable of executing the functions described herein.
[0036] As used herein, the terms "software" and "firmware" are
interchangeable, and include any computer program stored in memory
for execution by a processor, including RAM memory, ROM memory,
EPROM memory, EEPROM memory, and non-volatile RAM (NVRAM) memory.
The above memory types are for example only, and are thus not
limiting as to the types of memory usable for storage of a computer
program.
[0037] FIG. 1 is a schematic diagram illustrating an example
multi-party transaction card industry system 120 for enabling
ordinary payment-by-card transactions in which merchants 124 and
card issuers 130 do not need to have a one-to-one special
relationship. Embodiments described herein may relate to a
transaction card system, such as a credit card payment system using
the MasterCard.RTM. interchange network. The MasterCard.RTM.
interchange network is a set of proprietary communications
standards promulgated by MasterCard International Incorporated.RTM.
for the exchange of financial transaction data and the settlement
of funds between financial institutions that are members of
MasterCard International Incorporated.RTM.. (MasterCard is a
registered trademark of MasterCard International Incorporated
located in Purchase, N.Y.).
[0038] In a typical transaction card system, a financial
institution called the "issuer" issues a transaction card, such as
a credit card, to a consumer or cardholder 122, who uses the
transaction card to tender payment for a purchase from a merchant
124. To accept payment with the transaction card, merchant 124 must
normally establish an account with a financial institution that is
part of the financial payment system. This financial institution is
usually called the "merchant bank," the "acquiring bank," or the
"acquirer." When cardholder 122 tenders payment for a purchase with
a transaction card, merchant 124 requests authorization from a
merchant bank 126 for the amount of the purchase. The request may
be performed over the telephone, but is usually performed through
the use of a point-of-sale terminal, which reads cardholder's 122
account information from a magnetic stripe, a chip, or embossed
characters on the transaction card and communicates electronically
with the transaction processing computers of merchant bank 126.
Alternatively, merchant bank 126 may authorize a third party to
perform transaction processing on its behalf. In this case, the
point-of-sale terminal will be configured to communicate with the
third party. Such a third party is usually called a "merchant
processor," an "acquiring processor," or a "third party
processor."
[0039] Using an interchange network 128, computers of merchant bank
126 or merchant processor will communicate with computers of an
issuer bank 130 to determine whether cardholder's 122 account 132
is in good standing and whether the purchase is covered by
cardholder's 122 available credit line. Based on these
determinations, the request for authorization will be declined or
accepted. If the request is accepted, an authorization code is
issued to merchant 124.
[0040] When a request for authorization is accepted, the available
credit line of cardholder's 122 account 132 is decreased. Normally,
a charge for a payment card transaction is not posted immediately
to cardholder's 122 account 132 because bankcard associations, such
as MasterCard International Incorporated.RTM., have promulgated
rules that do not allow merchant 124 to charge, or "capture," a
transaction until goods are shipped or services are delivered.
However, with respect to at least some debit card transactions, a
charge may be posted at the time of the transaction. When merchant
124 ships or delivers the goods or services, merchant 124 captures
the transaction by, for example, appropriate data entry procedures
on the point-of-sale terminal. This may include bundling of
approved transactions daily for standard retail purchases. If
cardholder 122 cancels a transaction before it is captured, a
"void" is generated. If cardholder 122 returns goods after the
transaction has been captured, a "credit" is generated. Interchange
network 128 and/or issuer bank 130 stores the transaction card
information, such as a category of merchant, a merchant identifier,
a location where the transaction was completed, amount of purchase,
date and time of transaction, in a database 220 (shown in FIG.
2).
[0041] After a purchase has been made, a clearing process occurs to
transfer additional transaction data related to the purchase among
the parties to the transaction, such as merchant bank 126,
interchange network 128, and issuer bank 130. More specifically,
during and/or after the clearing process, additional data, such as
a time of purchase, a merchant name, a type of merchant, purchase
information, cardholder account information, a type of transaction,
itinerary information, information regarding the purchased item
and/or service, and/or other suitable information, is associated
with a transaction and transmitted between parties to the
transaction as transaction data, and may be stored by any of the
parties to the transaction. In the exemplary embodiment, when
cardholder 122 purchases travel, such as airfare, a hotel stay,
and/or a rental car, at least partial itinerary information is
transmitted during the clearance process as transaction data. When
interchange network 128 receives the itinerary information,
interchange network 128 routes the itinerary information to
database 220.
[0042] For debit card transactions, when a request for a personal
identification number (PIN) authorization is approved by the
issuer, cardholder's account 132 is decreased. Normally, a charge
is posted immediately to cardholder's account 132. The payment card
association then transmits the approval to the acquiring processor
for distribution of goods/services or information, or cash in the
case of an automated teller machine (ATM).
[0043] After a transaction is authorized and cleared, the
transaction is settled among merchant 124, merchant bank 126, and
issuer bank 130. Settlement refers to the transfer of financial
data or funds among merchant's 124 account, merchant bank 126, and
issuer bank 130 related to the transaction. Usually, transactions
are captured and accumulated into a "batch," which is settled as a
group. More specifically, a transaction is typically settled
between issuer bank 130 and interchange network 128, and then
between interchange network 128 and merchant bank 126, and then
between merchant bank 126 and merchant 124.
[0044] FIG. 2 is a simplified block diagram of an example system
200 used for determining the lifestyle categories of geographic
regions in accordance with one example embodiment of the present
disclosure. In the example embodiment, system 200 may be used for
performing payment-by-card transactions received as part of
processing cardholder transactions. In addition, system 200 is a
payment processing system that includes a lifestyle determining
("LD") computing device 224 configured to determine the life stage
segment of the residents in a geographic region based on cardholder
transactions. As described below in more detail, LD computing
device 224 is configured to collect transaction information from a
plurality of transactions from a plurality of cardholders,
determine a life stage segment for multiple cardholders residing in
a geographic region, determine a lifestyle category for the
geographic region based on the cardholders residing in that
geographic region, and generate a report for that geographic
region.
[0045] In the example embodiment, client systems 214 are computers
that include a web browser or a software application, which enables
client systems 214 to access server system 212 using the Internet.
More specifically, client systems 214 are communicatively coupled
to the Internet through many interfaces including, but not limited
to, at least one of a network, such as the Internet, a local area
network (LAN), a wide area network (WAN), or an integrated services
digital network (ISDN), a dial-up-connection, a digital subscriber
line (DSL), a cellular phone connection, and a cable modem. Client
systems 214 can be any device capable of accessing the Internet
including, but not limited to, a desktop computer, a laptop
computer, a personal digital assistant (PDA), a cellular phone, a
smartphone, a tablet, a phablet, or other web-based connectable
equipment.
[0046] A database server 216 is communicatively coupled to a
database 220 that stores data. In one embodiment, database 220
includes transaction information from a plurality of cardholders
and paths based on those transactions. In the example embodiment,
database 220 is stored remotely from server system 212. In some
embodiments, database 220 is decentralized. In the example
embodiment, a person can access database 220 via client systems 214
by logging onto server system 212, as described herein.
[0047] The LD computing device 224 is communicatively coupled with
the server system 212. The LD computing device 224 can access the
server system 212 to store and access data and to communicate with
the client systems 214 through the server system 212. In some
embodiments, the LD computing device 224 may be associated with, or
is part of the payment system, or in communication with the payment
card system payment network 120, shown in FIG. 1. In other
embodiments, the LD computing device 224 is associated with a third
party and is merely in communication with the payment network
120.
[0048] One or more point of sale systems 222 are communicatively
coupled with the server system 212. The one or more point of sale
systems 222 can be merchants 124 shown in FIG. 1, where the point
of sale systems 222 are communicatively coupled with the server
system through the payment network 120. Point of sale systems 222
may be, but are not limited to, machines that accept card swipes,
online payment portals, or stored payment card numbers for
recurring transactions.
[0049] In some embodiments, server system 212 may be associated
with a financial transaction interchange network 128 shown in FIG.
1, and may be referred to as an interchange computer system. Server
system 212 may be used for processing transaction data and for
registering cardholders and/or merchants into a plurality of
programs offered by the interchange network, including, but not
limited to, a rewards program. In addition, at least one of client
systems 214 may include a computer system associated with an issuer
of a transaction card. Accordingly, server system 212 and client
systems 214 may be utilized to process transaction data relating to
purchases a cardholder makes utilizing a transaction card processed
by the interchange network and issued by the associated issuer. At
least one client system 214 may be associated with a user or a
cardholder seeking to register, access information, or process a
transaction with at least one of the interchange network, the
issuer, or the merchant. In addition, client systems 214 or point
of sales devices 222 may include point-of-sale (POS) devices
associated with a merchant and used for processing payment
transactions. POS devices may be, but are not limited to, machines
that accept card swipes, online payment portals, or stored payment
card numbers for recurring transactions.
[0050] FIG. 3 illustrates an example configuration of a client
system 214 shown in FIG. 2, in accordance with one embodiment of
the present disclosure. User computer device 302 is operated by a
user 301. User computer device 302 may include, but is not limited
to, client systems 214 and LD computing device 224 (both shown in
FIG. 2). User computer device 302 includes a processor 305 for
executing instructions. In some embodiments, executable
instructions are stored in a memory area 310. Processor 305 may
include one or more processing units (e.g., in a multi-core
configuration). Memory area 310 is any device allowing information
such as executable instructions and/or transaction data to be
stored and retrieved. Memory area 310 may include one or more
computer readable media.
[0051] User computer device 302 also includes at least one media
output component 315 for presenting information to user 301. Media
output component 315 is any component capable of conveying
information to user 301. In some embodiments, media output
component 315 includes an output adapter (not shown) such as a
video adapter and/or an audio adapter. An output adapter is
operatively coupled to processor 305 and operatively coupleable to
an output device such as a display device (e.g., a cathode ray tube
(CRT), liquid crystal display (LCD), light emitting diode (LED)
display, or "electronic ink" display) or an audio output device
(e.g., a speaker or headphones). In some embodiments, media output
component 315 is configured to present a graphical user interface
(e.g., a web browser and/or a client application) to user 301. A
graphical user interface may include, for example, an online store
interface for viewing and/or purchasing items, and/or a wallet
application for managing payment information. In some embodiments,
user computer device 302 includes an input device 320 for receiving
input from user 301. User 301 may use input device 320 to, without
limitation, select and/or enter one or more items to purchase
and/or a purchase request, or to access credential information,
and/or payment information. Input device 320 may include, for
example, a keyboard, a pointing device, a mouse, a stylus, a touch
sensitive panel (e.g., a touch pad or a touch screen), a gyroscope,
an accelerometer, a position detector, a biometric input device,
and/or an audio input device. A single component such as a touch
screen may function as both an output device of media output
component 315 and input device 320.
[0052] User computer device 302 may also include a communication
interface 325, communicatively coupled to a remote device such as
server system 212 (shown in FIG. 2). Communication interface 325
may include, for example, a wired or wireless network adapter
and/or a wireless data transceiver for use with a mobile
telecommunications network.
[0053] Stored in memory area 310 are, for example, computer
readable instructions for providing a user interface to user 301
via media output component 315 and, optionally, receiving and
processing input from input device 320. A user interface may
include, among other possibilities, a web browser and/or a client
application. Web browsers enable users, such as user 301, to
display and interact with media and other information typically
embedded on a web page or a website from server system 212. A
client application allows user 301 to interact with, for example,
server system 212. For example, instructions may be stored by a
cloud service, and the output of the execution of the instructions
sent to the media output component 315.
[0054] Processor 305 executes computer-executable instructions for
implementing aspects of the disclosure. In some embodiments, the
processor 305 is transformed into a special purpose microprocessor
by executing computer-executable instructions or by otherwise being
programmed. For example, the processor 305 is programmed with the
instruction such as illustrated in FIGS. 5 & 6.
[0055] FIG. 4 illustrates an example configuration of the server
system 212 shown in FIG. 2, in accordance with one embodiment of
the present disclosure. Server computer device 401 may include, but
is not limited to, database server 216 (shown in FIG. 2). Server
computer device 401 also includes a processor 405 for executing
instructions. Instructions may be stored in a memory area 410.
Processor 405 may include one or more processing units (e.g., in a
multi-core configuration).
[0056] Processor 405 is operatively coupled to a communication
interface 415 such that server computer device 401 is capable of
communicating with a remote device such as another server computer
device 401, client systems 214, or LD computing device 224 (both
shown in FIG. 2). For example, communication interface 415 may
receive requests from client systems 214 via the Internet, as
illustrated in FIG. 2.
[0057] Processor 405 may also be operatively coupled to a storage
device 434. Storage device 434 is any computer-operated hardware
suitable for storing and/or retrieving data, such as, but not
limited to, data associated with database 220 (shown in FIG. 2). In
some embodiments, storage device 434 is integrated in server
computer device 401. For example, server computer device 401 may
include one or more hard disk drives as storage device 434. In
other embodiments, storage device 434 is external to server
computer device 401 and may be accessed by a plurality of server
computer devices 401. For example, storage device 434 may include a
storage area network (SAN), a network attached storage (NAS)
system, and/or multiple storage units such as hard disks and/or
solid state disks in a redundant array of inexpensive disks (RAID)
configuration.
[0058] In some embodiments, processor 405 is operatively coupled to
storage device 434 via a storage interface 420. Storage interface
420 is any component capable of providing processor 405 with access
to storage device 434. Storage interface 420 may include, for
example, an Advanced Technology Attachment (ATA) adapter, a Serial
ATA (SATA) adapter, a Small Computer System Interface (SCSI)
adapter, a RAID controller, a SAN adapter, a network adapter,
and/or any component providing processor 405 with access to storage
device 434.
[0059] FIG. 5 is a flowchart illustrating an example of the process
500 of determining the lifestyle category of a geographic region
from cardholder transaction using the system shown in FIG. 2, in
accordance with one embodiment of the disclosure. Process 500 may
be implemented by a computing device, for example the LD computing
device 224 (shown in FIG. 2). In the example embodiment, the LD
computing device 224 receives 510 a plurality of cardholder
transactions. The plurality of cardholder transactions may be
received from the database server 216, where the cardholder
transactions may have been stored in the database 220 (both shown
in FIG. 2). In the example embodiment, the plurality of cardholder
transactions may include cardholder transactions over a significant
period of time, e.g., six months. Each transaction includes at
least a unique identifier for each cardholder, a merchant
identifier, a merchant category, a geographic location of a
merchant, a transaction amount, and a date and time for the
transaction.
[0060] The LD computing device 224 generates 520 a cardholder list
of all of the cardholders that had at least one transaction in the
received plurality of cardholder transactions. The LD computing
device 224 determines 530 one or more life stage segment(s) for
each cardholder. In some embodiments, the LD computing device 224
determines that the cardholder belongs to one life stage segment,
such as, but not limited to married with children or empty nester.
In other embodiments, the LD computing device 224 determines that
the cardholder belongs to multiple life stage segments, such as,
but not limited to, singles, recent couples/recently married, new
parents, parents with teenagers, and retirement.
[0061] The LD computing device 224 determines 540 one or more
geographic regions based on the determined cardholder life segments
and the received plurality of transactions. A geographic region may
be any geographic identifier including, for example and without
limitation, a postal code, a city/town/municipality, a neighborhood
in a city/town/municipality, GPS coordinates, a county, a single
city block, an apartment complex, a street address, and
sub-divisions of any of the preceding geographic identifiers.
[0062] In some embodiments, one or more geographic regions may be
predefined by the user or may be determined by the LD computing
device 224. In either case, a minimum number of cardholders in the
same life stage segment are required for a defined geographic
region to ensure that no personally identifiable information may be
obtained from the classification. In the example embodiment, at
least three (3) cardholders in a life stage segment are needed to
determine a geographic region. If it is determined that there is
less than three (3) cardholders in a life stage segment of a
geographic region, then the LD computing device 224 or the user
must re-define a larger geographic region.
[0063] To define a geographic region, the LD computing device 224
identifies a minimum number of cardholders with the same life stage
segment living in close proximity. For example, in some places with
high population density, e.g., New York City, the LD computing
device 224 identifies seven cardholders living in the same
apartment building. The LD computing device 224 identifies three of
those cardholders to be in the "new parents" life stage segment,
three of them in the "retired" life stage segment, and one
cardholder in the "singles" life stage segment. Because there is
only one cardholder in the "singles" life stage segment, which is
below the required minimum number for a geographic region, the LD
computing device 224 expands the geographic region until the number
of cardholders in each life stage segment with at least one
cardholder exceeds the minimum. In the example embodiment, the LD
computing device 224 ignores life stage segments with zero
cardholders. In the above example the LD computing device 224
expands the proposed geographic region to include a neighboring
building which may add two "new parents", one "retired", and three
"singles" cardholders. Since no life stage segment with cardholders
is below the minimum, the LD computing device 224 defines those two
buildings as one geographic region. If the second building had
added a single cardholder in a different life stage segment, then
the LD computing device 224 would expand the proposed geographic
region again. In other places with lower population density, e.g.,
rural or suburban cardholders may be more spread out and the LD
computing device 224 may only be able to find three cardholders of
the same life stage segment on a street or a block, rather than an
apartment building and define the geographic region to be that
street or block.
[0064] For each geographic region, the LD computing device 224
determines 550 a lifestyle category for the geographic region based
on the life stage segments of the cardholders associated with that
geographic region. In some embodiments, the LD computing device may
determine a lifestyle category for a geographic region based on the
life stage segment with the most cardholders in that geographic
region. For example, if a majority or more, such as 7 of the 10
cardholders in a geographic region are in the "new parents" life
stage segment, then the LD computing device 224 determines that the
geographic region is in the "new parents" lifestyle category.
However, there may not be a majority of cardholders in one life
stage segment, therefore in other embodiments, the LD computing
device may determine a lifestyle category for a geographic region
based on percentages (i.e., the lifestyle category is determined
based on the life stage segment with the highest percentage of
cardholders) or calculated formulas (e.g., if the total number of
cardholders with a particular life stage segment exceeds a
predetermined threshold). In the example embodiment, the lifestyle
categories are the same as the life stage segments, in other
embodiments, multiple life stage segments may be combined to
determine the lifestyle category. In some embodiments, the
lifestyle category is further broken down into sub-categories, such
as multiple children and single child. In some embodiments, a
minimum number of cardholders must reside in a geographic region to
determine a lifestyle category for the geographic region.
[0065] The LD computing device 224 generates 560 a lifestyle report
for each determined geographic region. In some embodiments, the
lifestyle report is a numerical report, showing the numbers of
cardholders belonging to different life stage segments, living in
the geographic region. In other embodiments, the lifestyle report
may graphically represent the lifestyle categories with different
colors representing different lifestyle categories in one or more
geographic regions. The lifestyle report may be displayed as an
overlay of a geographic map. In further embodiments, the lifestyle
report includes the different life stage segments of the different
cardholders in the geographic region.
[0066] FIG. 6 is a flowchart illustrating an example of the process
600 of determining one or more life stage segments for a cardholder
using the system shown in FIG. 2, in accordance with one embodiment
of the disclosure. Process 600 may be implemented by a computing
device, for example the LD computing device 224 (shown in FIG. 2).
The LD computing device 224 analyzes a transaction that a
cardholder performed and determines 610 a score profile to assign
to that transaction. The score profile includes one or more
probability values for one or more life stage segments. In the
example embodiment, the LD computing device 224 determines the
score profile based on the merchant category of the transaction. In
some embodiments, merchants have associated scoring profiles based
on the merchant category, e.g., the scoring profile for a retail
toy store is different than the scoring profile for a high-end
men's clothing store. In other embodiments, the scoring profile is
associated with an individual store. Based on the scoring profile
of the merchant, the LD computing device 224 calculates 620 the
cardholder's life stage segment probabilities based on the score
profile and any previously calculated life stage segment
probabilities. The life stage segment probabilities are a
collection of probabilities that the cardholder belongs to one or
more life stage segments, where each probability is associated with
a life stage segment. For example, if the cardholder makes a
purchase from a retail toy store, then the LD computing device 224
increases the probability associated with the cardholder being in
the "new parents" and the "parents with teenagers" life stage
segments.
[0067] The LD computing device 224 checks 630 to see if there are
more transactions to analyze for this cardholder. If there are more
transactions, then the LD computing device 224 returns to Step 610.
If there are no more transactions, then the LD computing device 224
generates 640 one or more groups of transactions. For example, the
LD computing device 224 may generate a group of all of the
transactions at grocery stores, a group of all of the home
improvement store transactions, and a further group of all of the
high-end clothing store transactions. For each group of
transactions, the LD computing device 224 determines 650 a score
profile to assign to the group. For example, the LD computing
device 224 analyzes the group of cardholder transactions at
home-improvement stores. In the analysis, the LD computing device
224 determines that there are a significant number of
moderately-sized transactions during the weekends and assigns the
score profile of a new home owner. In another example, the LD
computing device 224 determines that there are a significant number
of large purchases that primarily occur on weekdays, then the LD
computing device 224 assigns the score profile of a contractor.
[0068] Once the score profiles are assigned to the groups, the LD
computing device 224 calculates 660 the life stage segment
probabilities for the cardholder based on the assigned score
profiles and any previously calculated life stage segment
probabilities. The LD computing device 224 determines 670 one or
more life stage segments to assign to the cardholder based on the
probabilities. In some embodiments, the LD computing device 224
determines the one or more life stage segments based on the
probabilities exceeding predetermined thresholds. In other
embodiments, the LD computing device 224 combines multiple
probabilities to determine a life stage segment.
[0069] FIG. 7 is a diagram 700 of components of one or more example
computing devices that may be used in the system 200 shown in FIG.
2. In some embodiments, computing device 710 is similar to server
system 212; it may also be similar to LD computing device 224 (both
shown in FIG. 2). Database 720 may be coupled with several separate
components within computing device 710, which perform specific
tasks. In this embodiment, database 720 includes transaction
information 722, cardholders 724, geographic regions 726, and score
profiles 728. In some embodiments, database 720 is similar to
database 220 (shown in FIG. 2).
[0070] Computing device 710 includes the database 720, as well as
data storage devices 730. Computing device 710 also includes a
communication component 740 for receiving 510 a plurality of
cardholder transactions 722, as shown in FIG. 5. Computing device
710 also includes a generating component 750 for generating a list
of cardholders 520, generating a lifestyle report 560 (both shown
in FIG. 5), and generating groups of transactions 640 (as shown in
FIG. 6). A determining component 760 is also included for
determining the life stage segment(s) for each cardholder 540,
determining one or more geographic regions 726, determining a
lifestyle category for a geographic region 550 (all three shown in
FIG. 5), determining a score profile 728 to assign to a transaction
610, determining a score profile to assign to each group of
transactions 650, and determining one or more life stage segments
to assign to a cardholder 670 (all three shown in FIG. 6). A
calculating component 770 is also included for calculating the life
stage segment probabilities based on a score profile 620 and 660
(as shown in FIG. 6). A processing component 780 assists with
execution of computer-executable instructions associated with the
system.
[0071] The systems and processes are not limited to the specific
embodiments described herein. In addition, components of each
system and each process can be practiced independent and separate
from other components and processes described herein. Each
component and process also can be used in combination with other
assembly packages and processes.
[0072] Having described aspects of the disclosure in detail, it
will be apparent that modifications and variations are possible
without departing from the scope of aspects of the disclosure as
defined in the appended claims. As various changes could be made in
the above constructions, products, and methods without departing
from the scope of aspects of the disclosure, it is intended that
all matter contained in the above description and shown in the
accompanying drawings shall be interpreted as illustrative and not
in a limiting sense.
[0073] While the disclosure has been described in terms of various
specific embodiments, those skilled in the art will recognize that
the disclosure can be practiced with modification within the spirit
and scope of the claims.
[0074] As will be appreciated based on the foregoing specification,
the above-described embodiments of the disclosure may be
implemented using computer programming or engineering techniques
including computer software, firmware, hardware or any combination
or subset thereof. Any such resulting program, having
computer-readable code means, may be embodied or provided within
one or more computer-readable media, thereby making a computer
program product, i.e., an article of manufacture, according to the
discussed embodiments of the disclosure. Example computer-readable
media may be, but are not limited to, a flash memory drive, digital
versatile disc (DVD), compact disc (CD), fixed (hard) drive,
diskette, optical disk, magnetic tape, semiconductor memory such as
read-only memory (ROM), and/or any transmitting/receiving medium
such as the Internet or other communication network or link. By way
of example and not limitation, computer-readable media comprise
computer-readable storage media and communication media.
Computer-readable storage media are tangible and non-transitory and
store information such as computer-readable instructions, data
structures, program modules, and other data. Communication media,
in contrast, typically embody computer-readable instructions, data
structures, program modules, or other data in a transitory
modulated signal such as a carrier wave or other transport
mechanism and include any information delivery media. Combinations
of any of the above are also included in the scope of
computer-readable media. The article of manufacture containing the
computer code may be made and/or used by executing the code
directly from one medium, by copying the code from one medium to
another medium, or by transmitting the code over a network.
[0075] This written description uses examples to disclose the
embodiments, including the best mode, and also to enable any person
skilled in the art to practice the embodiments, including making
and using any devices or systems and performing any incorporated
methods. The patentable scope of the disclosure is defined by the
claims, and may include other examples that occur to those skilled
in the art. Such other examples are intended to be within the scope
of the claims if they have structural elements that do not differ
from the literal language of the claims, or if they include
equivalent structural elements with insubstantial differences from
the literal languages of the claims.
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