U.S. patent application number 13/890817 was filed with the patent office on 2013-09-19 for personalized interactive network for delivery of information including targetted offers for goods and services.
This patent application is currently assigned to JPMorgan Chase Bank, N.A.. The applicant listed for this patent is Anthony Caiazzo, Jennifer Holme, Ameet Patel. Invention is credited to Anthony Caiazzo, Jennifer Holme, Ameet Patel.
Application Number | 20130246189 13/890817 |
Document ID | / |
Family ID | 26861664 |
Filed Date | 2013-09-19 |
United States Patent
Application |
20130246189 |
Kind Code |
A1 |
Patel; Ameet ; et
al. |
September 19, 2013 |
Personalized Interactive Network for Delivery of Information
Including Targetted Offers for Goods and Services
Abstract
Systems and methods personalize interaction between a central
server system, a plurality of consumers, and a plurality of
providers of information regarding products and services of
potential interest. For each consumer, a plurality potential offers
may be generated for various products and/or services. The system
may generate a list of personalized offers for each consumer
corresponding to various products and/or services to promote to
that consumer. When a consumer interacts with the central server
system, a response results in the delivery of responsive content as
well as personalized offer content. Consumers can interact with the
system over a variety of communication channels and user devices,
including ATMs, PDAs, cell phones, computers accessing web sites or
other Web Devices, Voice Response Units (VRUs), and others.
Inventors: |
Patel; Ameet; (Trenton,
NJ) ; Holme; Jennifer; (Hoboken, NJ) ;
Caiazzo; Anthony; (Tuckerton, NJ) |
|
Applicant: |
Name |
City |
State |
Country |
Type |
Patel; Ameet
Holme; Jennifer
Caiazzo; Anthony |
Trenton
Hoboken
Tuckerton |
NJ
NJ
NJ |
US
US
US |
|
|
Assignee: |
JPMorgan Chase Bank, N.A.
New York
NY
|
Family ID: |
26861664 |
Appl. No.: |
13/890817 |
Filed: |
May 9, 2013 |
Related U.S. Patent Documents
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Application
Number |
Filing Date |
Patent Number |
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13326271 |
Dec 14, 2011 |
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13890817 |
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11950112 |
Dec 4, 2007 |
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13326271 |
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09564783 |
May 4, 2000 |
7370004 |
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11950112 |
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Current U.S.
Class: |
705/14.67 |
Current CPC
Class: |
G06Q 30/0251 20130101;
G06Q 30/0269 20130101; G06Q 30/0237 20130101; G06Q 20/382 20130101;
G06Q 30/02 20130101; G06Q 30/0271 20130101; G06Q 30/0613 20130101;
G06Q 30/0201 20130101; G06Q 30/0239 20130101; G06Q 30/0204
20130101; G06Q 40/00 20130101; G06Q 30/0631 20130101; G06Q 30/0203
20130101; G06Q 30/0256 20130101; G06Q 20/108 20130101 |
Class at
Publication: |
705/14.67 |
International
Class: |
G06Q 30/02 20120101
G06Q030/02 |
Claims
1. A computer-implemented method for delivering personalized offers
in a system including a plurality of customers, a central server
system, and a plurality of merchants, comprising: storing in at
least one non-transitory computer memory, data and instructions
pertaining to at least one of products and services to be offered;
accessing the at least one computer memory using a computer
processor at a central server system to execute instructions and to
perform operations including: storing data in said at least one
computer memory including financial account information for a
plurality of customer financial accountholders, storing, by the
central server system, data in said at least one computer memory
including customer profile data for a plurality of customer
financial accountholders, delivering content to client applications
providing customer accountholder access to (a) customer financial
account information and (b) personalized offers for goods or
services, receiving at said central server system an electronically
transmitted request from a customer financial accountholder for
information regarding specific financial services, selecting, by
the central server system, at least one personalized offer for
goods or services for the requesting customer accountholder based
on customer profile data; and delivering a response to said request
including (a) information content regarding the specific financial
services and (b) personalized offer content corresponding to the
selected at least one personalized offer.
2. The computer-implemented method for delivering personalized
offers according to claim 1, wherein the (a) information content
regarding the specific financial services and (b) personalized
offer content corresponding to the selected at least one
personalized offer, are electronically transmitted together.
3. The computer-implemented method for delivering personalized
offers according to claim 1, wherein the (a) information content
regarding the specific financial services and (b) personalized
offer content corresponding to the selected at least one
personalized offer, are electronically transmitted together for
display together on a web page.
4. The computer-implemented method for delivering personalized
offers according to claim 1, wherein personalized offers made by
the central server system are delivered over multiple different
communication channels.
5. The computer-implemented method for delivering personalized
offers according to claim 1, wherein at least some personalized
offers made by the central server system are delivered over a
communication channel different than the communication channel used
for the request.
6. The computer-implemented method for delivering personalized
offers according to claim 5, further wherein at least some
personalized offers are delivered over communication channels
selected based on customer profile data.
7. The computer-implemented method for delivering personalized
offers according to claim 1, further comprising: selecting at least
one offer for goods or services using a decision engine at the
central server system; wherein the decision engine applies
personalization rules to make the selection.
8. The computer-implemented method for delivering personalized
offers according to claim 1, wherein multiple personalized offers
are selected and delivered to the requesting user.
9. The computer-implemented method for delivering personalized
offers according to claim 1, further comprising: storing, in said
at least one computer memory, tag lists of offers to make to
customers for a plurality of different campaigns.
10. The computer-implemented method for delivering personalized
offers according to claim 1, further comprising: storing, in said
at least one computer memory, a plurality of potential offers to
make to a customer corresponding to a plurality of different
campaigns.
11. The computer-implemented method for delivering personalized
offers according to claim 10, wherein the plurality of potential
offers is scored or weighted by the central server system to enable
selecting a specific offer in response to the request.
12. The computer-implemented method for delivering personalized
offers according to claim 1, wherein personalized offers made by
the central server system include information regarding credit
cards, loans, and investments.
13. The computer-implemented method for delivering personalized
offers according to claim 1, wherein the request from a customer
financial accountholder is from a customer access computer.
14. The computer-implemented method for delivering personalized
offers according to claim 13, wherein the customer access computer
is a web device or a handheld device.
15. The computer-implemented method for delivering personalized
offers according to claim 1, wherein the central server system
services customer requests from a plurality of different customer
access computers including (a) Automatic Teller Machines (ATMs) or
kiosks, (b) web devices or handheld devices, and (c) Voice Response
Units (VRUs).
16. A computer-implemented method for delivering personalized
offers according to claim 1, wherein at least some of said
personalized offers are generated dynamically while a
17. A computer-based system for delivering personalized offers for
at least one of products and services, comprising: a central server
system, comprising an inbound channel server and an outbound
channel server, communicating through at least one computer network
with a plurality of merchants and a plurality of consumer access
devices; a database coupled to the central server system storing
consumer financial account information and information regarding
products and services to be offered to said consumers; the database
further including consumer profile data for a plurality of consumer
financial accountholders, the outbound channel server delivering
content to client applications providing consumer accountholder
access to (a) consumer financial account information and (b)
personalized offers for goods or services, the inbound channel
server for receiving an electronically transmitted request from a
consumer financial accountholder for information regarding specific
financial services, a personalization engine at the central server
system selecting at least one personalized offer for goods or
services for the requesting consumer accountholder based on
consumer profile data; wherein the outbound channel server delivers
a response to said request including (a) information content
regarding the specific financial services and (b) personalized
offer content corresponding to the selected at least one
personalized offer.
18. The computer-based system of claim 17, wherein the inbound
server and outbound server are the same.
19. The computer-based system of claim 17, wherein at least one of
the inbound server and outbound server is a web server.
20. The computer-based system of claim 17, wherein the outbound
server at least in some cases delivers responses over a
communication channel different than the communication channel used
for the request.
21. A computer-based system for delivering personalized offers for
at least one of products and services, comprising: a central server
system, comprising an inbound channel server and an outbound
channel server, communicating through at least one computer network
with a plurality of merchants and a plurality of consumer access
devices; a database coupled to the central server system storing
(i) consumer financial account information for a plurality of
consumer financial accountholders, (ii) a plurality of advertising
campaigns regarding products and services to be offered to at least
some of said consumer accountholders, and (ii) consumer profile
data for said consumer financial accountholders, the outbound
channel server delivering content to client applications providing
consumer accountholder access to (a) consumer financial account
information and (b) personalized offers for goods or services, the
inbound channel server for receiving an electronically transmitted
request from a consumer financial accountholder for information
regarding specific financial services, a personalization engine at
the central server system selecting at least one personalized offer
for goods or services for the requesting consumer accountholder
based on consumer profile data; wherein the outbound channel server
delivers a response to said request including (a) information
content regarding the specific financial services and (b)
personalized offer content corresponding to the selected at least
one personalized offer; wherein the (a) information content
regarding the specific financial services and the (b) personalized
are delivered together on a web page.
Description
CROSS REFERENCE TO RELATED APPLICATIONS
[0001] This application is a continuation of U.S. patent
application Ser. No. 13/326,271, filed Dec. 14, 2011, which in turn
is a continuation of U.S. patent application Ser. No. 11/950,112,
filed Dec. 4, 2007, which in turn is a continuation of U.S. patent
application Ser. No. 09/564,783, filed May 4, 2000, now U.S. Pat.
No. 7,370,004, which in turn claims the benefit of and incorporates
by reference the subject matter of U.S. Provisional Application
Ser. No. 60/165,739, filed Nov. 15, 1999. Each of U.S. patent
application Ser. No. 13/327,271, U.S. patent application Ser. No.
11/950,112, U.S. patent application Ser. No. 09/564,783 and U.S.
Provisional Application Ser. No. 60/165,739 is hereby incorporated
by reference in its entirety.
BACKGROUND OF THE INVENTION
[0002] The present invention relates to a system for personalized
interaction over a communications channel between a user and a
provider of information/services/goods. In particular, the present
invention allows for personalized interactivity between an Internet
web site user and the web site provider of
information/services/goods. For example, the present invention
allows a provider of services, for example, a provider of financial
services such as a bank, to interact personally through a customer
personalized website with a customer of that financial service
provider. Although the invention may be used to personalize the
provision of financial services over a communications channel, it
is not limited to financial services but can be used to personalize
the interaction between a customer and a provider of any products,
goods, services and/or information of any kind. In particular, the
present invention allows the provider of the
information/goods/services to personalize the web site to the
preferences of the particular user, for example, preferences such
as interests, hobbies, business interests, product/service
preferences, etc. Although an example has just been provided of a
personalized approach to providing an Internet based service, the
invention is equally applicable to any other communications channel
including such channels involving interaction through automatic
teller machines (ATMs) and other communications devices and kiosks,
other communication channels, intranets or extranets, e-mail,
telephone communications, faxes, call centers, branch offices,
etc.
[0003] There are some limited forms of personalized interactive
systems presently in operation, in particular, over the Internet.
For example, Amazon.com provides a service which can select books
for customers based upon their previous selections and preferences.
However, these systems are limited in scope, and basically only use
what is known as collaborative filtering to infer either what
should be offered next or to make recommendations to the user.
[0004] Another system patented by Broadvision, described in U.S.
Pat. No. 5,710,887, provides for electronic commerce over a
computer driven network. An aim of this system is to allow commerce
to be conducted across a number of different platforms and
networks. Although offering the ability to be implemented over
different networks, not just the internet, this system offers
limited ability to customize the interaction between the customer
and the provider of goods/services so that each customer interacts
in a unique way with the provider based on the customer's
preference, characteristics, lifestyle, etc. The Broadvision patent
creates a participant program object that identifies the
participant and contains information about the participant, e.g.,
name, address, privacy controls, demographic data and payment
methods. However, the system is not capable of making knowledge
driven decisions about a customer to personalize the interaction
with the provider so that it takes into account more intangible
customer characteristics such as preferences, lifestyles, and such
customer characteristics as, for example, preferred tone of voice
of interaction, decisions about user interests and hobbies, etc.,
that may be important to making an electronic interaction more
"human" or personal.
[0005] Another system is described in U.S. Pat. No. 6,014,638.
assigned to America Online, Inc. This system, however, is directed
to an Internet only based system and is not applicable to a system
which is adaptable to multiple channels and points of contact.
Further, the system of the AOL patent does not allow for
personalization in real time, i.e., using current interactions with
the user.
BRIEF SUMMARY OF THE INVENTION
[0006] The present invention aims to manage knowledge obtained from
customer interactions and personalize the
information/product/services that are offered to the customer as a
result of those interactions. The present invention utilizes data
obtained from past and present interactions to make decisions about
what to offer the customer and about what
information/products/services the customer may be interested in.
Further, the present invention is directed at totally personalizing
the relationship between the customer and the
information/service/product provider based upon using all the
knowledge which can be obtained from past and present interactions
with the customer to personalize the relationship with the
customer. In the context of an Internet web site, the present
invention personalizes the web site to the customer's preferences,
characteristics and interests, etc. and pushes information,
products, etc. that would be suitable to the customer.
[0007] The present invention provides a single, integral system
that allows all channels to utilize the system, thus centralizing
knowledge and creating a unique customer interaction
experience.
[0008] Further, the present invention meets a need to integrate
within an information/product/service provider, the various
departments of the information/product/service provider so that the
various information/product/service providers within a single
company, for example, or even amongst groups of companies, can
provide a plurality of information/services/products to the
customer using an integrated or "cross channel" approach. For
example, taking the example of a financial service provider, the
present invention allows information concerning an ATM user having
a high savings balance to be known to an investment department of
the financial service provider so that the financial service
provider can provide investment opportunities to that customer.
Taking another example, a financial service customer having a high
savings balance may be offered information concerning real estate
mortgage offerings or loans on the rationale that a customer with a
high balance may be saving funds to purchase and/or finance a home.
In this way, the system of the invention allows collaboration and
cross-fertilization (cross-application) across different channels
of an information/service/product provider.
[0009] Presently, in many institutions that provide multiple
services/products/information, one department providing a
particular service/product/information may be totally unaware of
prospects known to another department specializing in a different
area of that same company or of knowledge that a customer exists in
other relationships. The present invention, through an integrated
system, will allow the company to be more responsive to the
customer's various needs. In effect, the present invention has the
effect of ending what is often called the "silo" mentality, i.e.,
the compartmentalizing of branches or departments in a company so
that one branch or department is unaware of prospects/customers
from another branch or department. A customer or user is defined as
anyone who uses the system. The present invention aims to achieve
the above objects by integrating various channels through which
customers communicate with the information/service/product
provider. The various channels may include the Internet, but also
other channels such as phone lines, automatic teller machines,
branch offices, bank cards, e-mail, direct mail and most other
channels of communication. Further, the system of the invention
allows use of multiple channels, e.g., a user may initiate
communication using an ATM, but receive a response over the
internet or fax or by phone or e-mail. The system allows the
customer and provider to interact and allows customer to customer
interaction or user to user interaction within a product/service
information provider.
[0010] According to the invention, the above described objects are
achieved by a system for personalizing interaction between a user
communicating over at least one communication channel and a
provider of information/products/services, the user having a
communication device for communication over the channel with the
provider, the system comprising: a channel interface for
interfacing with the channel; a product/service interface for
interfacing with an information/product/service provider; and a
knowledge management system coupled to the channel and
product/service interfaces, the knowledge management system
comprising a knowledge/management repository storing information
concerning the user, the information obtained from interaction with
the user over the channel including current interactions between
the user and the knowledge management system and further for
storing information concerning a plurality of
information/products/services to offer to the user; and a
personalization engine for making a decision as to which of the
plurality of information/product/services to present to the user
over the communication channel based on the stored information in
the knowledge/management repository.
[0011] According to one aspect, the system of the invention
comprises a plurality of managers, brokers and services that
contain and utilize databases and objects.
[0012] According to another aspect, the invention comprises a
method for personalizing interaction between a user communicating
over at least one communication channel and a provider of
information/products/services, the user having a communication
device for communication over the channel with the provider with
which the user interfaces with the channel. A knowledge management
system is interfaced with the channel and an
information/product/service provider. Information is stored in a
knowledge management repository concerning the user, the
information obtained from interaction with the user over the
channel including current interactions between the user and the
knowledge management system. Further, information is stored in the
knowledge management repository concerning a plurality of
information/products/services to offer to the user. A decision is
made as to which of the plurality of information/products/services
to present to the user over the communication channel based on the
stored information in the knowledge management repository.
[0013] According to yet another aspect, the present invention
provides a system for personalizing interaction between a user
communicating over at least one communication channel and a
provider of information/products/services, the user having a
communication device for communication over the channel with the
provider, the system comprising: a channel interface for
interfacing with the channel; a product/service interface for
interfacing with an information/product/service provider; and a
knowledge management system coupled to the channel and
product/service interfaces. The knowledge management system
comprises a knowledge management repository storing information
concerning the user, the information obtained from at least one of
interaction with the user over the channel including current
interactions between the user and the knowledge management system;
and information obtained about the user from other sources. The
knowledge management repository further storing information
concerning a plurality of information/products/services to offer to
the user; and a personalization engine for making a decision as to
which of the plurality of information/product/services to present
to the user and for personalizing content of the
information/product/services provided to the user over the
communication channel based on the stored information in the
knowledge management repository.
[0014] According to still yet another aspect, the invention
provides a method for personalizing interaction between a user
communicating over at least one communication channel and a
provider of information/products/services, the user having a
communication device for communication over the channel with the
provider in which the user is interfaced with the channel. A
knowledge management system is interfaced with the channel and an
information/product/service provider. Information is stored in a
knowledge management repository concerning the user, the
information obtained from at least one of interaction with the user
over the channel including current interactions between the user
and the knowledge management system and information obtained from
other sources. Information is further stored in the knowledge
management repository concerning a plurality of
information/products/services to offer to the user. A decision is
made as to which of the plurality of information/product/services
to present to the user and for personalizing content of the
information/product/services provided to the user over the
communication channel based on the stored information in the
knowledge management repository.
[0015] The system of the invention accordingly provides a framework
of components, their relationships, functions, and purposes for
creating and maintaining a personalized interaction that is
constant and can be tailored to any communications channel.
[0016] Further, the system of the invention can be used with any
interactive communication channel and further is applicable to a
wide variety of goods/products/services/information including,
without limitation, financial products/services, legal
products/services, entertainment products/services, government
products/services, personal products/services, corporate
products/services, consumer/individual products/services and
information in general. For example, with respect to financial
institutions, information such as payment information, statements,
documents and files can be stored. Personalized offerings can be
provided to the customer in such areas as archives for legal
requirements, product fulfillment and customer service. For law
firms, document storage can be provided and the interaction
personalized. For example, archives for legal requirements or data
mining of intellectual property are some examples of personalized
offerings which can be provided by the system of the invention.
With respect to entertainment companies, media such as music and
video libraries may be stored. Personalized offerings such as
consumer sales/global order fulfillment and video and audio
screening may be provided. For governmental agencies, forms, deeds,
statements and other documents and files etc. may be stored and
personalized offerings may be provided with respect to these, for
example, personalized data views can be provided. The system of the
invention provides convenience, security and efficiency. With
respect to personal services and markets, examples of media stored
include PC backup, documents, music and video data, which can be
used for internal use, customer service or order fulfillment, for
example. Corporations can use the invention for documents/file
storage, trade materials and/or vault services, for example. These
can be used for internal use work flow improvement or order
fulfillment.
[0017] Other features and advantages of the present invention will
become apparent from the following detailed description of the
invention which refers to the accompanying drawings.
BRIEF DESCRIPTION OF THE DRAWINGS
[0018] The invention will be described in greater detail in the
following detailed description with reference to the accompanying
drawings in which:
[0019] FIG. 1 shows the overall framework for the personalization
architecture of the present invention;
[0020] FIG. 1A is a linear technical architecture diagram showing
the various layers of the system of the invention and their
applicability to various input channels and products and/or
services, their relationships and interactions; this drawing uses
time with zero minutes being the distribution channel with 1+ being
the product layer;
[0021] FIG. 1B shows an example of operation of the system
illustrating a case study demonstrating the components
involved;
[0022] FIG. 1C shows modeling of the data using, for example, the
"Papaa" framework (to be described herein);
[0023] FIG. 2 is a more detailed block diagram of the basic
components of the personalization architecture including the
distribution channels and product processors;
[0024] FIG. 3 is a yet more detailed block diagram of the
personalization architecture of the invention, including
components, relationships and flows;
[0025] FIGS. 4, 5, 5A, 6 and 7 are flow charts and accompanying
related data applicable to users using a web site which has been
personalized and showing the techniques used to personalize the
experience and flow;
[0026] FIGS. 8 and 8A are detailed block diagrams of the
interaction of the personalization manager component shown in FIGS.
2 and 3, this flow demonstrating the role and functionality of this
component;
[0027] FIG. 8A shows the technical objects used to construct the
personalization manager;
[0028] FIGS. 9 and 9A are block diagrams showing the interaction of
components of the invention based upon triggering by an event to
achieve personalization;
[0029] FIGS. 10 and 10A show the interaction of functional
components of the personalization architecture and technical
objects used during campaign management;
[0030] FIG. 11 shows functional components of the personalization
architecture portal interface with the user;
[0031] FIGS. 12, 12A and 12B show functional components and
technical objects of the personalization architecture relating to
content management;
[0032] FIGS. 13 and 13A show functional components and technical
objects of the personalization architecture relating to customer
profile management;
[0033] FIG. 14 shows functional components of the personalization
architecture relating to user authentication:
[0034] FIGS. 15 and 15A show functional components and technical
objects of the personalization architecture relating to management
information system reporting and customer analysis;
[0035] FIG. 16 shows how a decision on a value proposition to be
offered to a customer online is made by the system of the
invention; and
[0036] FIG. 17 shows the Papaa model.
DETAILED DESCRIPTION OF PREFERRED EMBODIMENTS
[0037] With reference now to the drawings, FIG. 1 is an overall
block diagram of the architecture of the invention for providing
personalized interaction between a provider of information and/or
goods and/or services and a customer. A customer 1 interacts with
the system through any of a number of distribution channels 10
which may comprise, for example, the Internet, automatic teller
machines/kiosks, direct mail (email, fax, letter, etc.), Extranet,
an Intranet, call centers, and branch offices, without limitation.
The system includes an integrated knowledge management component or
personalization system 100 to be described in greater detail. The
component 100 implements such functions as scoring (propensity
rating), campaign management, knowledge engineering, analysis and
mining of information, data warehousing, forming customer profiles,
providing customer profiles, and contacting management. The system
component 100 includes a decision engine to make decisions to
enable the system to personalize the interaction, a personalization
engine to personalize the interaction and a content management
engine, amongst other components referenced later. The system
enables personalization of the interaction between the customer and
an information/product/service provider offering
information/product/service 30 that the customer desires. For
example, as shown by items 30, in the case of a financial
institution, the products or services may comprise items such as
home finance, small business credit, credit cards, automobile
financing, savings deposits, other investments, insurance,
education financing, etc. The system includes the necessary means
to achieve product fulfillment. Although financial products 30 are
shown in FIG. 1, the system is equally applicable to other
information/services/products, such as goods or information.
Integrated in the system are the necessary means for providing
security, authentication/recognition and authorization directory
services, middleware and workflow services, groupware such as
web/Intranet messaging and media services, network systems
infrastructure and systems management services and support systems
such as compensation, fraud and compliance tracking systems,
etc.
[0038] FIG. 1A is a linear technical architecture diagram showing
the overall technical architecture of the system in the form of
layers. It shows the interaction from the distribution channels 10
on the left to the product layer 30 on the right. For example, if a
person interacts with the system via the Internet, the customer
interaction session 12 is direct. The customer interacts through an
authentication application 14 which provides work flow,
entitlements, and allows beginning a session on the system. As the
user crosses this layer, the user also registers the session and
retrieves any alerts/messages for the user. A presentation layer 16
is then used to access the system. The presentation layer shows the
relationship--the total view--to the user. Infrastructure layer 18
is the administration layer that allows the system to be maintained
and administrated. An application and business logic layer 20
includes the various applications and business logic, to be
described in detail below. The layer 20 then interacts through an
information product/processor layer 25 with
information/product/services 30 in the product layer.
[0039] Interacting with the various layers is a metadata-knowledge
discovery-object model 32 which includes various data bases and
services. These databases include a contacts database (db), work
flow db, security db, audit db, customer preference db, entitlement
db, content db, application db, data warehouse db, data mart db,
profile db, segmentation db, business rules db, campaign rule db
and product db, in addition to others.
[0040] Personalization is the ability to deliver targeted products,
services and information tailored to the user's preferences,
interests and needs. Personalization allows the creation of a
customer experience which reflects the relationship and the
customer's requirements, also called "customer centric" experience.
Furthermore, with respect to interaction via an Internet web site,
personalization allows filling "white space" which can be described
as the ability to promote an interaction with messages and other
personalized components using matching and selection based upon the
customer's profile, contacts, indications or assumptions derived
through analysis, past interactions or contacts and the current
interaction. The system is designed to adapt to all touch points or
channels and all devices of interaction. Personal information can
be static or dynamic based on a customer's explicit/implicit
preferences and historic data or dynamic based on real time
assessment of the next best step.
[0041] Personalization is adaptable to all channels, as described
above, such channels as the internet, extranet, phone lines,
e-mail, automatic teller machines, branch offices, etc.
[0042] Personalization of the interaction between customers and
providers of information/goods/services is driven by a number of
factors including environmental factors and business goals. With
respect to environmental factors, such factors as commoditization
of a particular industry, the disappearance of geographical
boundaries, the dissolution of product identities, consolidation
and competition have caused a need to distinguish one's products
and services from those of others and to build a system to obtain
this distinction through personalization of the interaction with
the customer.
[0043] Business goals also drive the need for personalization. A
customer feels more appreciated and more involved if there is
personalized interaction. Further, personalization of the
interaction empowers a customer and creates an environment
supportive of selling information/goods/services or cross-selling
information/goods/services amongst different departments of a
provider of information/goods/services. Solutions are tailored due
to knowledge of the customer.
[0044] The present invention provides a means to personalize an
interaction via various communication channels between a customer
and a provider of information/goods/services. The present invention
allows a customer to interact with the provider through a preferred
channel and at the customer's convenience. The system allows
personalization of that interaction so that the customer is
recognized and the customer's needs anticipated. The system allows
advising the customer and providing access to all
information/products/services offered by the provider. Further, the
system allows the provider to provide customer tailored packages,
i.e., non-standard packages. Furthermore, the system allows for
continuously gathering, analyzing and distributing information to
make the customer receive a more rewarding experience and
interaction with the provider. Moreover, the system creates a basis
for retaining customers, better servicing customers, and tailoring
solutions as a result of the personalization provided by the
system.
[0045] According to the invention, once a customer contacts the
provider through a communications channel using the personalized
system of the invention, the first step is identification and
authentication of the customer at the start of the session (the
security layer 14). This triggers the collection of a real time,
customer profile which, created and combined, provides the basis
for the delivery of a personalized experience. The same functions
and information are made available at each touch point, i.e.,
through each channel. The actual experience that the customer has
will be adapted to the customer's preferences and the capabilities
and environment at that touch point. A decision engine provides key
parameters for the real time assembly of the experience. Other
parameters are the capabilities of the touch point and the course
of the dialogue, for example, the click stream if communication is
over the internet. The system is capable of interacting with the
customer over a wide range of communication channels, however.
[0046] A Profile Manager, to be described in detail later, is the
central coordinator and manager for all user profile related
information. The Profile Manager is designed to be a service broker
with appropriate directory service and repository support and it
mediates access to all user profile related information.
Sub-components of the profile manager provide services such as
authentication and authorization, aggregation of profile attributes
including user preferences, segmentation and campaign
targeting/tracking information for the user, contact information,
and outstanding commercial and services issues ("workflow process"
status).
[0047] Value propositions i.e., offers to be made or information to
be presented to the customer, are matched with the customer profile
needs and preferences and delivered at the right time and the right
place. Each session will update the customer profile, trigger
follow-up activity and provide data for customer interaction
analysis and fine tuning of the customer dialogue and the value
proposition (offer).
[0048] The steps in the personalization process include adaptation
to the channel, selection of functions, navigation screens and
templates which take into account the specifics of the
communication channel. The system customizes the experience based
upon predefined navigation, language and tone of voice, metaphor
including color scheme graphics and layout. News and messages can
be provided to the customer.
[0049] Further, the system personalizes the process by content
selection, based on preferences and customization rules. The system
provides news and topics to the customer using searching and
filtering technologies.
[0050] Further, so called "white space" in the customer display can
be filled with propositions, actions, alerts, notifications, etc.,
decided by rules based on, for example, customer preferences or
analysis of the customer profile.
[0051] In addition, the system can predict needs and can propose
actions or recommendations based on matching of user profiles and
behavior of like minded people. The system determines next steps
based on analysis of the current interaction, obtains feedback and
learning to be captured in the customer knowledge base and includes
a rule oriented data base for application of personalization to
thereby personalize information, offers, terms, conditions, and
financial advice, etc.
[0052] FIG. 1B shows an example of how the system operates. FIG. 1B
shows one example of how the system personalizes in a cross channel
environment the interaction with a customer. The customer in this
particular case is a customer of a financial institution having a
high average savings balance, for example, greater than $10,000.00,
a credit card, and a mortgage. The customer's characteristics are
shown at 1A in FIG. 1C, along with the financial products,
agreements and accounts 1B utilized by the customer.
[0053] FIG. 1C shows an example of how the system would use various
data for this particular case study, i.e., the case study of FIG.
1B previously referred to. The customer has various demographics,
preferences, values, financial objectives and a lifestyle (1A).
Further, the customer has various agreements, if the service
provider is, for example, a bank, such as credit cards and a
mortgage (1B). Accordingly, the user makes use of various products
such as credit cards and a mortgage from the service provider, in
this case a bank. The user also may have accounts with the bank as
shown. The system of the invention may also maintain a plurality of
campaigns, contact lists, campaign responses, campaign priorities,
etc. (45). Campaigns may be, for example, programs currently
offered by the provider to customer prospects. The system further
incorporates business/marketing rules and decision factors, target
indicators, etc. (47) for determining which campaign to target to a
particular user based on the rule/factors. This data model--called
Papaa for applications in the banking industry--allows all
personalization data and actions to be modeled. This data framework
allows for a multi-channel, multi-action system to be unified for
mining and audit of information. Papaa is an acronym standing for
"Party--Agreement--Product--Account--Activity." It is an object
relational framework. The object model defines the business logic
and services to insulate interfaces from the physical, relational
database layer. The relational model offers the flexibility needed
to address and support evolving entity attributes. Papaa is a
framework defining the Global Profile Repository, discussed herein,
for Personalization, supporting the needs of the profile manager.
The Papaa model is shown schematically in FIG. 17.
[0054] Referring again to FIG. 1B, a campaign manager 122, to be
described in detail later, is programmed to run various campaigns
(FIG. 1C), for example, offering a credit card, currency on the go,
home equity loans, a mutual fund and/or small business services.
Based upon the customer profile managed by profile manager 122, a
personalization engine 112 selects, for example, a mutual fund
campaign to display on an ATM screen 40 while the customer
withdraws cash. The rationale for this decision is the high average
savings balance maintained by this customer. There is a likelihood
that this customer will desire to invest in a mutual fund. Further,
this decision may be based on other information available to the
system including lack of any knowledge of significant upcoming life
events, a comfortable lifestyle, and internal business/marketing
rules. Should the customer be interested, the customer will express
interest by touching the ATM screen and ask to be provided with
further details, for example, by e-mail or any other means. E-mail
can be sent with the information via e-mail server 121 and a link
to a web page 50, and an electronic form may be forwarded to the
customer which can be used to complete the sale.
[0055] As FIG. 1B shows, alternatively, the customer may interact
initially with the system by the Internet 45 in which case the
mutual fund ad is displayed on a webpage 50. The customer then has
the option of communicating via the web site with the provider to
consummate a transaction. Alternatively, another inbound and/or
outbound communication channel(s) could be used, e.g., telephone,
etc.
[0056] The personalization engine 112 is coupled to a decision
engine 114 making each personalization decision at an appropriate
time, in this case, on the best campaign to present to the
customer, also weighing which is the best option for the user. This
is performed based on business/marketing rules 47 (FIG. 1C) and the
customer's profile. A profile manager 118 contains the profile of
the customer which is retrieved and provided to the personalization
engine 112 and which the personalization engine contact manager 120
updates based upon further interactions. The campaign manager 122
is coupled to the personalization engine 117 to provide any of
selected campaigns for presentation to the customer. A contact
manager 120 is also provided which is updated by the
personalization engine 112 and records all the contacts with the
users of the system (user and provider). The CSR (customer service
representative) is alerted by an event manager to call the customer
to provide further information or to close a sale.
[0057] With the above in mind, reference is now made to FIG. 2
which is an overall block diagram of the system of the invention.
The customer interacts with the system via various channels 10, as
previously described. The various products or services are shown at
30 as previously described. The personalization system (integrated
knowledge management system) is indicated generally by reference
numeral 100. As described previously, to illustrate how the system
operates in a particular case, the system's primary components
include interface identification components 110 including a portal
111 for interfacing with the channel 10 by which the customer
interacts with the personalization system. The system 100 includes
the personalization manager 112, previously described, for
personalizing the interaction, the decision engine 114 which makes
decisions concerning personalization, a content manager 116 which
assembles and maps content to be provided to the user by providing
selected templates and screen objects and a profile manager 118
which creates and caches the customer profile based upon previous
interactions and other information concerning the customer profile
stored in a global profile repository 118A. The system further
includes a contact manager 120, campaign manager 122, customer
analysis component 124, alert/event manager 126, authentication
component 128 and various information sources, internal and
external, shown at 130.
[0058] With reference to FIG. 2, the portal 111 serves as an entry
point and common connector that interconnects the various
components. Components of the portal 111 include a repository which
contains metadata about screen objects, customer
authentication/ACLs, preferences, profile, etc., a
publish/subscribe engine, customer agents to deliver subscribed
events/messages, search engine-key word and boolean/crawler/filter
engine, etc. Portals control and administer the user's complete
"view" (what they see and how it is organized in each channel based
on user's preferences and entitlements etc.). Portal capability is
essentially cross channel. Portals provide the customer the
capability to customize their view and tailor the view according to
their preferences. They typically offer content folders to organize
content into multiple logical groups which may be shown in separate
view zones, i.e., transaction data, published information such as
stock quotes, "white space" content driven by personalization and
marketing, static information, etc. User preferences can be channel
specific (Internet has a certain view while call centers should
answer pre-configured view or queries) and context specific (i.e.,
specific view while looking at, for example, account balances).
[0059] The portal may use a single sign-on (SSO) server 198 (FIG.
3), to be described later and the profile manager which collects
the data for customer authentication and authorizations. The
profile manager maintains a membership directory containing the
information necessary to authenticate and assign entitlement roles
to each customer. It provides a single sign-on across all the
web/application servers. It displays an individual navigation menu
with all the enterprise resources/services the customer is
authorized to access. The menu reflects the customer's
entitlements, and work flow which are obtained in real time based
on the customer's current relationship with the
information/product/service provider.
[0060] The Profile Manager 118 manages all the details related to
the user's profile. This component is essentially a service broker,
which maps and mediates access to all user profile related
information, which may be maintained on multiple systems. These
include user authentication and authorization, profile attributes,
user preferences, user-campaign tag lists and related data, contact
information etc. While all the above are not accessed through the
Profile Manager, it provides the data and service directories to
access this information as a service broker.
[0061] Some of the data elements related to a user's profile may be
generated by other systems directly, i.e., contact information or
campaign tag lists. However, the Profile Manager will provide
reference maps and services to access this information. Some other
profile elements may be accessed only through the profile manager,
i.e., core profile elements.
[0062] The Profile Manager is considered the master reference for
all user profile related data. The Global Profile Repository (GPR)
acts as the central directory or repository of all the data
mappings, references, services. The actual data elements may
physically be distributed in different databases (part of a common
CRM data model).
[0063] The menus provided to the customer also reflect customer
profiles, preferences and subscription services. Profiles and
preferences are managed by the profile manager 118. The key
functions of the profile manager 118 include managing customer
relationship events and assembling customer profiles using an LDAP
based customer directory which provides linkages to all systems
containing customer data and has supplementary customer information
such as preferences., interests, etc.
[0064] If the internet is the chosen communication channel, as soon
as the customer opens the home page, the portal 111 delivers
personalized assembled information relative to the customer's
profile. This automatic assembly of content is done by the content
manager 116. The personalization is achieved via the
personalization manager 112.
[0065] The content manager 116 aggregates content from multiple
sources. Content sources may be of two categories, either static or
dynamic. Static content may come from external feeds 130A, for
example, weather, news, stock quotes, etc., and also from internal
feeds 130B, for example, product/service knowledge. Static content
is served directly by the portal 111 but stored/retrieved from the
content manager 116. Dynamic and personalized content is served by
the personalization manager 112, based on rules, work flow,
interaction, campaigns and collaborating filtering, amongst other
techniques. The content repository 116A contains the actual screen
content objects, for example, HTML files, images, and applets. FIG.
3 shows the system of FIG. 2 in more detail.
[0066] The Portal 111 contacts the Content Manager 116 component
for content elements. The Content Manager manages the content
components delivered to the user. The Content manager may assemble
content for channels when that is technically possible (i.e.,
Internet and e-mail) and will request content to be delivered in
other channels where content is assembled by the channel specific
application. However, content elements related to personalization
will be mapped into the content manager (may or may not physically
hold and assemble) and referenced by channel adapters which do
their own content assembly and delivery.
[0067] For example. most of the content for channels like the
Internet is stored in the Content Manager's repository 116A and
assembled by the Content Manager, whereas contents of traditional
ATM screens will be based in the ATM driver or ATM itself, with
personalized messages mapped and referenced from the content
manager. The Content manager maps and assembles content from its
own repository, business applications (transaction systems), other
static and dynamic internal and external sources, and resources
referred by the Personalization Manager etc. Content elements for
personalization will be decided by the Personalization Manager 112
based on the provider's personalization strategy, as reflected by
commercial rules, etc.
[0068] The customer analysis (data mining) component 124 utilizes
the datamart 125 to produce campaign rules, decision rules, and
profile elements. The campaign manager 122 exports campaign rules
to the personalization manager 112 and decision engine 114 and
campaign content components to the content manager 116. Campaign
response tracking is used to provide a real time feed back loop on
campaign effectiveness. Customer interests and other campaign
events are tracked in the content manager 116 for follow-up.
[0069] The personalization manager is the hub of the system. It is
a broker which retrieves, weighs and sorts. The personalization
manager 112 gets interaction events, collaborative filtering
results and customer profile/preferences as input. It organizes and
passes these inputs to the decision engine 114. The decision engine
114 evaluates the inputs against its marketing/campaign
intelligence rules stored therein to come up with a decision or
recommendation 114A. The decision is used by the personalization
manager 112 to prepare value propositions (offers), best next steps
and/or content to be presented to the customer. The personalization
manager 112 can also inquire of a collaborative filtering engine,
not shown in FIG. 2 or 3, but to be discussed in detail later,
which makes decisions based on analysis of like minded customers.
Further, it can make decisions based upon an interaction analyzer
which analyses the current interaction, for example, click stream
analysis, to make a recommendation.
[0070] The Campaign Manager 122 generates and manages reports such
as click stream analysis, interaction analysis, customer analysis,
campaign response analysis, etc. MIS Reporting--data
marts--customer data marts hold customer and transaction
information and are accessed by customer analysis components to
assist campaign generation and targeting, segmentation, distilling
of profile attributes, etc.
[0071] The Personalization Manager 112 component is a service
coordinator and receptacle that provides required services and data
support for personalization. Essentially the personalization
manager abstracts requests for personalized content and helps
manage other functionality/services associated with personalization
(such as decisioning, campaigns, etc.). It accepts campaign rules
from the campaign manager and executes the rules in the context of
the user with the help of decision engines. This component can
reference profile variables through the profile manager (tag lists,
attributes etc.), specific transaction values, event data, session
data, etc. (made available to decision engines as variables
influencing a rule). It can also accept, store and retrieve
personalization and campaign related status in appropriate data
repositories.
[0072] The Contact management 120 component aggregates and makes
available cross channel contact information across the
product/service/information provider. All contacts, both inbound
and outbound, generate information about the context of the contact
(in what context the contact happened, i.e., customer wanted to
withdraw money, had a service request, etc.). And the interaction
that occurs during the contact (how the user interacted, i.e., what
was user's click stream or dialogue with the CSR). For example, the
user may ask for all account balances, how much money can be
transferred at a time etc. before transferring money. Here,
transferring money is the context, but the interaction includes all
the activities that happened during the interaction. The view of
the contacts made available at the different points will be based
on the user of the information (decided by business needs) and will
be mediated through contact manager services. The data may
physically exist in multiple systems.
[0073] The event manager 126 component provides a publish and
subscribe mechanism for events. An event is a stimulus that
triggers an action. Events may result in a notification that can be
delivered via multiple channels. For example, the event that a
check has bounced can generate a notification to a customer and/or
CSR. (The process of notification is at times referred to as
Alerts. However, for clarity and to avoid confusion with the alert
manager sub-component of the content manager, the term notification
in this document issued to denote such alerts). The action could be
executed by provider staff or by a provider business application or
a messaging/notification sub-component system.
[0074] Services of the channel/device identifier component 111A are
used to determined the channel through which the user has accessed
the provider as well the capabilities and characteristics of the
device (i.e., browser type, security level, hand held device type,
graphics support, type of ATM, link speeds etc.). The format and
type of content (including functions permitted on this
channel/device) presented will be based on this identification.
This component, nevertheless, does not do any modification to the
content or participate in delivery of the content.
[0075] Turning now to FIGS. 4-7, these figures show the initial
interaction of a site visitor with a website personalized by the
system of the invention. For a first time site visitor 200, if
anonymous and without a unique identification (201), the customer
has an option to accept (203) or reject (204) an identifier. At
this stage, personalization is based only on interaction based on
current sessions, since there is no profile or history.
Customization at this stage may relate to layout colors, and
product/service offerings. Assuming the customer accepts the
identifier (cookie), personalization can now be based on current
and past sessions and information passed by the cookie. When the
customer gives explicit information (205) that the business
provider wants, personalization is then based on current and past
interaction, collaborative filtering, rules using the customer
profile and events. A determination (207) is then made whether the
customer is the customer that he claims to be by various
authentication techniques, for example, social security number,
account number, etc. Customization at this stage can include
layout, colors, product information, news, weather, stock quotes,
statements of account, interest rate charges, etc.
[0076] FIGS. 5, 5A, and 6 show what the user sees and the data
captured by the profile manager global profile repository 118A
(FIGS. 2 and 3) and interaction data 118B which is captured by the
system using the techniques of personalization. The profile manager
118 creates a PIF entry (profile file) for the user, updates the
PIF entry with explicit information and preferences, interests,
etc., addresses, E-mail addresses, phone numbers, demographic
information like age, income group or any other information that
the information/service/product provider needs and asks for any
other demographic information, some of which can be confidential
such as social security number, relationships, etc. The steps in
the dashed box, including steps 207-213, show some of the
authentication techniques.
[0077] FIG. 7 again shows the initial interaction between a site
visitor and the system, this time showing the personalization
techniques used by the system at the various stages of the
interaction. These include real time click stream analysis from
current session interaction, click stream analysis from previous
sessions and collaborative filtering, to be described in greater
detail below, based on past interaction and data collection.
Further, personalization is based on other rules based on
interactions and explicit/implicit information. In addition, other
rules stored in the system in addition to those based on
interactions and demographics, e.g., include those based upon
campaign transactions, the customer's profile and events including
transactions and service related events.
[0078] FIGS. 8 and 8A show a more detailed block diagram of the
functional components of the system which are used in
personalization. FIG. 8A shows greater detail than FIG. 8. As
described previously, personalization can be achieved through
various techniques including collaborative filtering, interaction
based on rules, including campaign rules and events. A value
proposition database 114A, included in the decision engine 114, has
user specific value proposition information like the number of
times the value proposition is shown, adjusted weightage for each
value proposition, time stamps, the channel upon which the user is
interacting with the system, etc.
[0079] With reference to FIGS. 8 and 8A, the content manager 116
passes a request 116A from the user to the personalization manager
112 for a recommendation of a value proposition to be presented to
the user. As part of this request, a user's profile is passed from
the profile manager 118 to the personalization manager 112. The
user's interaction data from the interaction data storage 130 is
also passed as an input to the personalization manager 112. These
personalization manager queries are passed to the decision engine
114 for application of rules. The decision engine 114 evaluates the
various rules stored in the rules data base 132. The decision
engine 114 then passes back all the value propositions that the
user should be targeted with based on a decision process executed
by the decision engine 114. Along with each value proposition, the
decision engine 114 passes a weightage and rule type. The
personalization manager 112 will calculate the best value
proposition to present to the customer, as described below.
[0080] The personalization manager 112 then sends a request 133 to
collaborative filtering engine 134 for a recommendation. The
filtering engine 134 uses various data elements including profile
from profile manager 118, interaction. etc. from the interaction
data storage 130 to perform a "like mind" analysis. The
collaborative filtering engine 134 returns a recommendation 136,
i.e., a value proposition.
[0081] The personalization manager 112 gets the weightage for this
user for all the value propositions obtained from the various
sources including the decision engine 114, collaborative filtering
134, etc.
[0082] The personalization manager 112 then balances weightages of
various value propositions and selects the best one for the
particular user.
[0083] The personalization manager 112 updates, along with other
flags, the value proposition data base 114A to adjust the weightage
for this particular user and this particular value proposition and
records the use of the proposition in the campaign manager. The
personalization manager 112 then contacts the product configurator
136 which builds a personalized proposal depending on the user's
profile and product/service (value proposition) profile 136A.
[0084] If the value proposition has been selected by the decision
engine 114 and the rule type satisfied for the value proposition is
a campaign, then the decision engine 114 checks the corresponding
campaign, category for this user. The selected value proposition
need not be a campaign, it could be an alert, etc. If the user is
present, the decision engine 114 updates flags in a tagged list
138. If the user is not present then it adds the user to the list
138. The personalization manager 112 then sends the best value
proposition to the content manager 116 which provides the selected
value proposition to the user and assembles the content thereof via
the portal 111 and selected channel 120.
[0085] FIGS. 9 and 9A shows functional components for event
triggered personalization; FIG. 9A in greater detail. An event is a
stimulus which triggers an action. The action could be executed by
the information/service/product provider or by a business
application. A business application can publish events whenever any
business action is executed. External feeds can trigger events. The
following types of events can be distinguished although they are
not exhaustive: life events, market/bank information, feed events,
customer relationship events, sales related events, advice related
events, service related events, transactional/work flow events,
user session events, profile related events, etc.
[0086] The campaign manager 122 generates target customer lists
140. Events 142 can be associated with campaigns. These events are
subscribed with the alert/event manager 126. The campaign manager
also sets frequency rates for the campaign against the tagged list
as well as tracks cost data regarding the campaign.
[0087] The flow for event triggered personalization is as follows.
Business applications 141 trigger various types of events. All
generated events are associated with a particular user
(customer/prospect). The alert/event manager 126 subscribes to all
events for all customers, implicit or explicitly by the user.
[0088] The alert/event manager 126 publishes the event to all the
subscribers of the event. One of the subscribers is the
personalization manager 112. The alert/event manager 126 passes
this event to the personalization manager 112 through a queue 144.
The personalization manager 112 picks up this event from the queue
144. The personalization manager 112 checks the user associated
with the event. The personalization manager 112 retrieves the
user's profile from the profile manager 118. The content manager
paints and pushes the event information to the subscriber.
[0089] Using the decision engine 114, the personalization manager
112 selects the most appropriate value proposition at that time for
the event and for the particular user. The notification service 146
gets the user's preferences from the profile manager 118 to find
out the user's preferred outbound contact channel, which may be one
of the inbound channels 10 or different outbound channels. The
notification service 146 gets the content (or pointer to content
depending on the channel) for the value proposition to be delivered
on the selected channel from the content manager 116. If the value
proposition is to be delivered on an inbound access channel 10,
then the value proposition is saved in the user's profile in the
profile manager 118. This can be used for later delivery on the
channel, for example, the Internet, when the user comes back to the
provider. The notification service 146 updates the profile manager
118 with the outbound activity 150. For outbound delivery 152, the
notification service 146 creates a contact/activity list in
sales/service application 154 and informs the outbound delivery
service 156 to deliver. The outbound delivery service 156 actually
initiates the contact across various channels 158, for example
e-mail, paper mail, faxes, etc. The sales/service application 154
is updated by the outbound delivery service 156 with the status of
the outbound contact/delivery.
[0090] FIGS. 10 and 10A show functional components related to
campaign management. FIG. 10A shows greater technical detail.
[0091] Customer analysis (data mining) 160 utilizes the data
warehouse 162 to produce campaign rules including propensity rating
(scores) for a particular customer. Marketing personnel 164
initiate campaigns for product promotion. The campaign manager 122
accepts the product/value proposition input and registers campaign
related content components with the content manager 116.
[0092] Campaign targeting 122A validates the generated campaign
rules 166. It generates a tagged customer list 168 with the help of
the profile manager 118. Campaign targeting 122A exports the
campaign rules 166 to the personalization manager 112 and, in
particular, to the decision engine 114. Campaign targeting 122A
also creates a contact and activity list 168 in sales applications
154 and informs the outbound delivery service 156 to start the
outbound contact activity across various channels, for example,
E-mail, paper mail, telephone calls, faxes, etc. The campaign is
then executed on the chosen outbound channels 158.
[0093] Customer/prospect responses 170 can be of two types. One is
that the customer seeks more information about the campaign or
product. The contact response information is captured in real time
and passed to campaign tracking 122B. The response is also fed to
the sales/service application 154. This assists in scheduling
further follow-up or can also be for no further outbound contact in
the case of a negative response. Other kinds of response includes
that the user/prospect actually buys the targeted product, e.g., by
opening an account 171. This is entered in the fulfillment
application 172. The fulfillment application 172 generates a
fulfillment response 174 keyed to campaign tracking 122B.
Fulfilment response is also recorded in sales and service
applications 154 to follow-up.
[0094] Campaign tracking 122B updates the tagged targeted list 168
with the response. This helps the personalization manager 112 to
take appropriate next action on inbound contact with the user from
channels 10. Response analysis 176 analyzes the campaign response
using a decision engine 178. This information is passed back to
marketing 164 which can evaluate campaign effectiveness. The
feedback is looped back into the existing campaigns and/or used for
future campaigns.
[0095] When a customer/prospect interacts on an inbound channel,
the personalization manager 112 evaluates the campaign rules 166.
If the customer satisfies the campaign rules and is not present on
the list, then the user is added to the list with relevant
information. The personalization manager 112 then provides the
campaign value proposition to the user via the content
manager/assembler 116 and portal 111. If the user is already on the
list then the personalization manager 112 also offers the value
proposition to the user.
[0096] FIG. 11 shows the functional components of the portal and
content assembler.
[0097] The content folders 190 are a set of business defined
logical groups of one or more topics. The business provider can
publish information to the folders and users can subscribe to them.
Preferably, the folders do not have the actual content. Instead,
they have pointers to content. The actual content preferably
resides in the content repository 192 connected to content manager
116. A folder 190 may have restrictions for access as specified by
the business provider.
[0098] A metadata repository 194 is also provided. The metadata
repository contains pointers to the content elements, user
preferences, content folders, ACLs, etc. This is information on how
to reach a particular item of information.
[0099] The customer agents 196 work in the background to
automatically search customer defined events and to save the
content in the customer specific content folder 190. They also
pre-fetch commonly requested information in the same folder.
[0100] The flow of content between user and portal 111 and the
personalization manager 112 is as follows:
[0101] After the user is identified or authenticated by SSO 198,
the request is passed to a channel access manager 111A. The channel
access manager 111A identifies the user's channel and device that
the user is using and passes the user identification and
device/channel characteristics to the portal 111. The portal 111
fetches the user's preferences from the profile manager 118. Based
on the user's channel characteristics and preferences, the portal
111 selects an appropriate template from the metadata repository
194. Based on the user's subscription stored in the profile, the
portal gets the general content folder information and customer
specific folder information from the metadata repository 194 based
on pointers in folders 190. The content folder information is
passed to the content manager 116.
[0102] The content manager 116 then returns a filled personalized
content 200. This content, personalized to the customer, is
delivered to the user through a delivery engine, not shown.
[0103] Offline, a crawler filter engine 202 automatically scans
specified data sources for objects of interest. It classifies them
and places the actual content in the content manager 116 and
appropriate information in a content folder 190. This occurs off
line. Additionally, also offline, a search engine 204 enables users
to find objects using key words like names, descriptions, content
types and filters. The user could be alert or notified upon return
of new content.
[0104] FIGS. 12 and 12A show functional components for content
management.
[0105] Content can come from two types of content sources, either a
dynamic content source 161 or a static content source 163. Dynamic
content is provided by applications like the personalization
manager 112. Campaign related content is also selected dynamically
and registered with the content server. Static content 163 can come
from external feeds 201, for example, weather, news, stock quotes
or internal feeds 203, for example product knowledge.
[0106] The content repository 116A contains content elements,
pieces of content, for example, HTML files, images, applets, for
selected channels, for example, the internet, web, ATM, etc. and
pointers to content for other channels, for example, IVR, Siebel,
etc. It also has information to map a value proposition to the
content manager 116.
[0107] The flow for content management is as follows:
[0108] The portal 111 passes (181) a template name to the content
manager 116. It uses the layout manager 208 to retrieve the actual
template from the content repository 116A. The template is passed
to the content assembler 210 which evaluates the template. It is
divided into zones and each zone has a pointer to the source of the
content. One or more zones can point to the personalization manager
112. The content assembler queries the personalization manager 112
for a value proposition. The personalization manager 112, using
various techniques including the decision engine 114 and
personalization rules database 114A, returns the best value
proposition to the content assembler 210. The content assembler 210
maps the value proposition to the actual content element which is
selected from the content repository 116A. The content assembler
210 returns the assembled content to the portal 111 for passage to
the user.
[0109] Off-line, a version manager 212 publishes a notification
event whenever a specified content element is changed. The portal
111 subscribes to this event and puts it in the user's content
folder 190. The version manager 212 also notifies the owner of the
content for version update. The content mapper 214 offers the
content designer 216 a multi-dimensional view of the content
element. It shows all other content that refers to this content,
all channels that it is used in, all rules that point to this
content, etc. The content mapper 214 provides content integrity and
cross references. All content is added/removed/administered through
the content mapper 214.
[0110] FIGS. 13 and 13A show functional components for profile
management. The profile manager 118 is a broker which offers
pointers/linkages to systems containing customer/prospect data. It
contains supplementary information such as customer preferences. It
assembles customer profiles using the global profile repository
118A. The profile manager is preferably integrated with single sign
on (SSO) 198. It holds psychographic, demographic and other data
elements related to a profile.
[0111] Online identity and credit verification of new customers can
be by known means of online inquiry or external systems such as
Bureauflex. The profile manager 118 is the gateway to any customer
related information. It provides an aggregated view of the customer
information. It provides a common API/messaging interface to all
other business/provider applications. The profile manager 118
shields everyone from collecting distributed data across the
business/provider.
[0112] Over a period of time, as the available customer data
increases, the profile can be enriched to update the psychographic
variables through knowledge discovery 220. The profile is enriched
with the knowledge derived from various applications like the
campaign manager 122, MIS reporting 160, collaborative filtering
134 and other interactions collectively indicated at 190.
[0113] FIG. 13A shows the architecture of the profile manager 118
in greater detail.
[0114] FIG. 14 shows functional components relating to single sign
on (SSO).
[0115] All user authentication requests are passed to an
authentication and authorization server (AAS) 230. The AAS 230
maintains/manages a security registry 232 which holds all
customer/non-customer security identifiers like user name,
password, access control layer, roles, etc. Whenever a new user
signs up, the AAS 230 creates the same user scheme for a customer
and/or prospect in the profile manager 118.
[0116] The flow for single sign on is as follows:
[0117] On any user request, the identification component 234
identifies if the user's request needs authentication. If the
request is for a non-restricted item, the request is passed forward
and the profile manager retrieves the user's preferences and alerts
the content manager to assemble the view to the portal 111. If the
request is for restricted items, it is passed through the AAS 230.
The AAS 230 authenticates the user by verifying the user's
identification/password. This is done by checking against the
security registry 232. If the user is authenticated, along with the
authentication status, the AAS 230 returns a navigation menu to the
identification component 234 which holds the customer's
entitlements for application servers and services. This is built by
the AAS 230 based on rules. The AAS 230 also returns encrypted
authentication tokens to the identification component. The token
holds the user name, roles and validity information. The
authentication token is stored in the customer's session. The token
is passed with every subsequent service request to the
corresponding web/application server, as shown at 233.
[0118] The access token is passed with every subsequent service
request from the user. The token verification layer 234A verifies
the tokens. If the token passes the verification process, the
service request is passed forward, as shown at 236. Otherwise, it
is blocked and the user is denied access to the service.
[0119] FIGS. 15 and 15A show functional components related to MIS
(management information systems) reporting.
[0120] Data mining is the extraction analysis of data for purposes
of discovering knowledge for large data bases. Data mining tools
automate prediction of trends/behaviors and discovery of previously
unknown patterns, allowing businesses to make proactive, knowledge
driven decisions and new business logic/rules. Data mining can be
performed on any user related data available across the
information/product/service provider. Analysts 240 can extract a
snap shot of the data bases 400 and run data mining tools in a
separate analytical environment.
[0121] An analyst 240 using the customer/prospect data in the
profile manager 118 and data mining tools can create a predictive
propensity model. From this model, the data mining tools generate a
customer segment, rules and propensity score for a customer
segment. This can operate also in reverse. Marketing can define a
customer segment by a rule in the campaign management application
and data mining can generate a propensity model and score the
customer segment in the campaign management application.
[0122] Campaign response data 250 can be fed to data mining
applications 160 to analyze the response data. The response can be
used to modify existing campaigns or for future campaigns. It can
also derive certain customer/prospect attributes which can be
updated through the profile manager 118.
[0123] User interaction, for example, click stream on the internet,
can be captured and analyzed in real time, as shown at 260.
Analysis can derive context out of the interaction. The context can
generate interaction events, which can be sent to the alert/event
manager 126. These events can be further sent to the
personalization manager 112 for selecting the best value
proposition. Interaction analysis 260 can generate new
personalization rules based in real time for the personalization
rules database 132. Interaction analysis 260 can also derive
customer behavior patterns, channel usage, navigation patterns
etc.
[0124] A contact manager 120 (see FIG. 2) captures contracts made
with the system and stores these in contacts data base 270.
Contacts can be analyzed using contacts data mining tools 162 to
understand the user contact patterns, channel usage and purpose,
etc. This can be fed back into the user's profile. Contacts can be
used for purposes of audit, security, service analysis, and
business processes.
[0125] As described, the present invention provides the ability for
cross-channel applications to offer services, functions, and
capabilities across all channels and allows the user of the system
to have the ability to create a customer centric experience as well
as allowing data knowledge to be gathered, analyzed and used. A
cross-channel application can be used on any channel, for example,
internet, ATM, phone lines, call centers, etc. Cross-channel
applications can be layered on top of industry standard technology
infrastructure, for example, message oriented middleware, component
based architecture, industry standard platforms such as EJB, JMS,
XML, MQ series, LDAP, BEA Weblogic, Oracle DB, Java Script
scripting Engine, Sun Solaris and Unix, without limitation.
Cross-channel application services are available to the different
types of applications including the profile manager 118, the
personalization manager 112, the event manager 126, the product
configurator 136 and other cross-channel applications. All
cross-channel applications can be made available on both external
messaging and an internal EJB bus. To ensure performance and
scalability, cross-channel applications are preferably hosted on an
EJB application server environment. To meet today's fast changing
business environment. a scripting capability can be provided to
link the business service components to shorten the cycle time for
rolling out new/updated business services.
[0126] FIG. 16 shows in greater detail how the personalization
manager 112 calculates the best value proposition or offer to a
customer on line.
[0127] A rules value proposition list 300 contains a list of all
best value propositions with rules for each value proposition. This
list is specific to a user. For a value proposition which is
waiting for a delivery to a customer, the value proposition list is
provided by the decision engine 114 and collaborative filtering
134. These are saved in the value proposition list 300.
[0128] A user proposition history object 302 contains the value
proposition and the weight of each for a user. This information is
extracted from a proposition history data base 304. The weight of
the value proposition being offered to the user is reduced further.
On session termination, all this updated information is written
back to the proposition history data base 304.
[0129] The proposition history access object 302 accesses the
proposition history data base 304 to get/set a value proposition
weight list for a user. In case of an off line request, the found
best value proposition is stored in the proposition history
database 304.
[0130] The value proposition object 302 contains the best proposal
that can be offered to a user. It contains the value proposition
related rule and proposal information.
[0131] The flow for calculating the best value proposition is as
follows:
[0132] First, a request to find a best value proposition for a user
is passed to the calculate best value proposition component 306.
The calculate best value proposition component 306 determines
whether it is necessary to present any personalized proposals to
the user. This is based upon the personalization rules data base
132 and rules evaluator 132A that is part of decision engine 114.
The rules are applied on the request for the particular user and
session. A user profile is then obtained from the session manager
308. This is used as one of the inputs to derive value
propositions. The user profile and session information are kept
ready for use by the decision engine 114. The decision engine 114
is used to extract a value proposition list for the user. The
calculate best value proposition component 306 also finds out
whether any value propositions are waiting for delivery for this
particular user. Any such value propositions are stored in the user
proposition history object 302.
[0133] The decision engine 114 and collaborative filtering engine
134 are then queried to derive value proposition lists best suited
for this user. The decision engine 114 applies rules on the user
and session information it has and derives a value proposition list
300. Collaborative filtering 134 gives a list of value
proposition/recommendations after performing a "like mind
analysis." The returned lists are stored in the Value proposition
list 300.
[0134] The calculate best value proposition component 306 balances
weightages of various value propositions and selects the best one
for this user from the complete list present in the rules/value
proposition list 300. The product configurator 136 keeps a mapping
of all value propositions to proposals that can be offered to a
particular user. It applies rules and finds out whether the
proposal for a value proposition can be offered to the user. In
case a value proposition cannot be offered to a user, the calculate
best value proposition component 306 checks for the next best value
proposition.
[0135] If the chosen value proposition is a result of a campaign,
then the user is added to the tag list 310 if the user is not
already present. If the campaign has expired, then the value
proposition/rules are deleted and the next value proposition is
checked with the product configurator 136. The best found proposal
is stored with its rules in the best value proposition object 312.
In case of an on line request, this proposal is returned to the
user. If the request or user is off line, it is saved in the
proposition history data base 304 for later on line use.
[0136] Personalization is a process by which the system of the
invention identifies the best value proposition to be delivered to
the user. This can be done in several ways. One way is to calculate
the best value proposition in real time on every click and show it
to the user. Another way is to calculate/save a list of value
propositions off line, even when the user has not come to the
service provider. This means that the service provider does not use
the user's context and current session click stream as inputs.
Further, this would not use the contact history that the user may
have generated after the off line activity. Another way is to
calculate/save a list of value propositions at the start of the
session and at every click select one and show it to the user.
Again, this method does not use the user context and current
session click stream.
[0137] Another option is to categorize rules as session static and
session dynamic and at the start of the session or when off line
calculate and save a list of value propositions. Later, when
on-line, on every click the session dynamic rules can be evaluated.
The downside to this method is that new session static rules that
are added during the session cannot be utilized. The choice between
the various options is a compromise between being effective and
performance.
[0138] With reference again to FIG. 8A, the decision engine 114
manages a rule variable dictionary 114B. The rule variable
dictionary 114B is a data structure which holds information of all
the attributes shown. It is a list of variables and associated
information that can be used for personalization. The rule variable
dictionary includes the following categories of variables: profile
attributes from the profile manager, session attributes from the
session manager, context variables from the content manager, and
events from the event manager. See FIG. 8A.
[0139] The rule variable dictionary 114B is updated to match the
corresponding data model or attribute list of each of the above
systems. In order to set up the dictionary, all the attributes are
entered in the dictionary. The attributes can be entered either
manually in the dictionary via a user interface 115 or can be
updated by a programming interface 115A.
[0140] The personalization manager 112 preferably has a graphical
user interface (GUI) through which marketing personnel can refresh
the dictionary whenever required. This could also be done in real
time whereby each of these systems could update the personalization
manager 112.
[0141] The collaborative filtering engine 134 returns
recommendations based upon user input and is fed with the user list
135 along with psychographic data and the value proposition list
137. The collaborative filtering engine 134 uses ratings which
customers provide with respect to value propositions, i.e.,
information/products/services offered. Based upon these ratings it
can then determine what types of information/services/products
should be offered to the user. Another way to do this is over a
period of time. After customers use the system, ratings can be
defined based upon the user's preferences. Based upon these
preferences, the collaborative filtering engine 134 can make
recommendations as to other information/products/services.
[0142] Turning again to the content manager (FIG. 12A), the content
manager 116 maintains a content dictionary 116B which is maintained
in the content repository 116A. The content repository 116A is
organized in the form of a tree structure termed a "content
dictionary" 116B. The content dictionary is a hierarchical tree of
content category by which content elements are classified. The tree
structure allows content to be grouped into categories and further
subcategories. The root of the content dictionary tree is called
"NCS root".
[0143] The first three branches from the root are as follows: The
first branch is the layout category subtree. All template/layouts
are stored under this node. They are further classified as
branches. Each such branch represents a unique template which can
be directly mapped to user preferences. They are not further
branched. The second branch is the function category subtree. All
functions are stored under this node. They are further classified
as branches and sub-branches. Each has a unique function which can
be directly mapped to user preferences.
[0144] The third branch is the data category subtree. All data
categories are stored under this node. They are further classified
as branches and sub-branches. Each sub-branch represents a unique
data category which can be directly mapped to user preferences.
[0145] Still referring to FIG. 12A, and with further reference to
FIG. 12B, the content assembler flow is as follows: Every incoming
request (URL) directly refers to a layout category. Each layout
category may have a number of layouts. The correct layout is chosen
based on the user's layout preference and on the device and channel
the user is utilizing. Each layout has an associated template which
defines visual characteristics. This template defines multiple
zones and a function category for each zone. Each function category
has one or more functions. Appropriate functions are chosen based
on the user's interests amongst all the functions in this function
category stored as preferences with the profile manager. A function
contains a template and one or more data categories. This function
template provides a consistent way (for a device/channel) in which
the function is displayed irrespective of the data category. A data
category is a node in the content dictionary 116B. Each function
may have one or more data categories and also have one or more data
elements. For all static contents, appropriate data elements are
chosen based on which data element the user is interested in
amongst all the data elements in this data category. This interest
is stored as a preference with the profile manager 118. For all
dynamic content a separate adapter component can be written. This
component can communicate with an application and get back the data
elements.
[0146] Content is gathered for personalization as follows:
Personalization is a function category specified in a zone. A
content selector contacts the personalization manager to resolve
this function category to a value proposition for the customer. The
value proposition is mapped to a function for the channel and
device. The function has a template and one or more data categories
and is processed accordingly as other functions.
[0147] Transactions, for example, a balance summary, transfers,
etc. are a function by themselves. Transactions contains a template
and a data category. The transaction data category has a
corresponding object component to be called and provides the data
for the transaction result to be displayed.
[0148] The product configuration is the data category with a
corresponding object component to be called and provides the
product configuration information for a given product for the
customer in session. For example, if a home equity loan is being
proposed, the product configuration will provide terms and
conditions for this customer based on the customer's relationship
and credit information.
[0149] Events, pending for delivery during inbound customer
interaction, belong to a specialized event data category. The
corresponding object component will be called to retrieve the
pending events for customer display.
[0150] Turning again to the event manager (FIG. 9A), all events are
stored in an event tree 126A. The tree structure allows event types
to be grouped into categories and further subcategories. Each
branch in the tree represents a subcategory of the event it
branches from. The event tree is built dynamically. When a new
event type is added to the environment, it is added to the tree so
that it is available for subscription. Access to the event tree can
be either to read or to write. A write access adds an event type to
the tree. The tree is read to publish the event to all the
subscribers.
[0151] The event properties describe the event itself and further
relevant information associated with the event. Event agents 127
generate events that are in the event tree. For the first event. a
new event type is created in the tree. This is done by calling one
of the operations offered by the event manager. Every time,
including the first time, the event agents 127 generate the event
and pass event properties to the event manager 126. Subscribers
subscribe to events that are in the event tree. For the first time
they subscribe to the event and every time including the first time
they receive the event along with event properties.
[0152] Event subscriptions are customer applications which
subscribe to events or event categories. They can specify the
following subscription information: Extra conditions that must be
satisfied before the event is forwarded to them. The event manager
126 will evaluate these conditions before forwarding the event.
They also specify what action to perform when the event occurs.
They also indicate the expiration of the subscription. The
conditions are evaluated and the action is performed by the event
manager 126. The client application specifies this in a form of
class name. These classes are installed on the event manager.
[0153] Event agents 127 are applications that generate events. They
monitor required data sources. Event agents have user preferences
about the event that they can generate. A new event that is sent to
the event manager 126 will have a user ID associated with it. Event
agents communicate with the event manager 126 through standard
adapters 129 which support, for example, XML over MQ series, EJB
interfaces, etc. Custom adapters can be built to support additional
interfaces, for example, news agents, stock agents, transaction
agents.
[0154] The LDAP comprises the following: A profile data dictionary,
interface dictionary and a storage dictionary. The profile data
dictionary is a dictionary to hold the data model of the profile.
The data model is stored as a hierarchical tree. It has a list of
profile attributes. The tree is stored in an LDAP directory. The
profile dictionary manager automatically updates the interface and
storage dictionary whenever the profile data dictionary is
modified.
[0155] The interface dictionary holds information about the source
of the attributes. It describes how each attribute needs to be
fetched and which adapter to use. It describes that the attributes
have to be fetched in real time or in batch mode, the frequency,
age, etc.
[0156] The storage dictionary holds an internal storage and
retrieval related information like the table name, field name,
name, etc. this dictionary describes each and every attribute and
attribute category. These attributes are saved in multiple tables
across data bases. This dictionary is stored in an LDAP
directory.
[0157] The profile data base physically holds the actual profile
attributes. Storage of the attributes is optimized for
retrieval/update of the attributes and may not be the same as the
profile data model.
[0158] Returning to FIG. 13A, the data access manager 118B manages
all read and write access to the customer profile database. It
aggregates scattered attributes from internal and external storage
systems. For reading the profile, it reads the storage dictionary
118C. This gives information about how to fetch the profile.
Various methods can be used to fetch the profile, for example,
obtaining it in real time from the source system through the
interface manager 118D, reading from the local database, etc. For
each method, there is additional information which aids in fetching
the profile. In writing the profile, the data access manager 118B
uses the storage dictionary 118C. The dictionary tells where to
write the profile attributes.
[0159] The interface manager 118D manages interfacing to business
systems. Anything coming in or going out occurs through the
interface manager 118D. It uses suitable interface adapters 118E to
gather/exchange profile information.
[0160] The global profile repository 118A is built by pushing and
pulling. Certain attributes are fetched in real time when required.
Certain attributes are downloaded periodically, for example, in
batch mode. Applications can update the profile attributes in real
time. Certain attributes can be written in batch mode. The profile
attributes can have ACLs for read/write access. Any read/write
access to the global profile repository 118A preferably should be
through an authorization component. The data access manager 118B
can impose these restrictions.
[0161] Although the present invention has been described in
relation to particular embodiments thereof, many other variations
and modifications and other uses will become apparent to those
skilled in the art. Therefore, the present invention should be
limited not by the specific disclosure herein, but only by the
appended claims.
* * * * *