Patent Application
20140278741
The present invention relates generally to the field of community analytics, and more particularly to customer community analytics for use by an enterprise.
Analytics is the process of discovery of meaningful insights from data. Analytics is typically used in areas rich with recorded information. To quantify performance, analytics relies on: (i) statistics; (ii) computer programming; and (iii) operations research. Analytics typically uses data visualization to communicate insight. Enterprises commonly apply analytics to business data, to describe, predict, and improve business performance. Some representative known applications of analytics include: (i) enterprise decision management; (ii) retail analytics; (iii) store assortment; (iv) SKU (stock-keeping unit) optimization; (v) marketing optimization; (vi) marketing mix analytics; (vii) web analytics; (viii) sales force sizing and optimization; (ix) price and promotion modeling; (x) predictive science; (xi) credit risk analysis; and (xii) fraud analytics.
According to an aspect of the present invention, there is a method for gathering information about customers of an enterprise. The method includes the following steps (not necessarily in the following order): (i) receiving information about the customers from the enterprise; (ii) performing customer community analytics on the received information; and (iii) generating a machine readable customer community analytics graph based, at least in part, upon the customer community analytics performed at the performing step. At least the performing step and the generating step are performed by computer software running on computer hardware.
The DETAILED DESCRIPTION section will be divided into the following sub-sections: (i) The Hardware and Software Environment; (ii) Operation of Embodiment(s) of the Present Invention; (iii) Further Comments And/Or Embodiment(s); and (iv) Definitions.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or computer program product. Accordingly, aspects of the present invention may take the form of an entirely hardware embodiment, an entirely software embodiment (including firmware, resident software, micro-code, etc.) or an embodiment combining software and hardware aspects that may all generally be referred to herein as a “circuit,” “module” or “system.” Furthermore, aspects of the present invention may take the form of a computer program product embodied in one or more computer-readable medium(s) having computer readable program code/instructions embodied thereon.
Any combination of computer-readable media may be utilized. Computer-readable media may be a computer-readable signal medium or a computer-readable storage medium. A computer-readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any suitable combination of the foregoing. More specific examples (a non-exhaustive list) of a computer-readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or Flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer-readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer-readable signal medium may include a propagated data signal with computer-readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer-readable signal medium may be any computer-readable medium that is not a computer-readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer-readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java (note: the term(s) “Java” may be subject to trademark rights in various jurisdictions throughout the world and are used here only in reference to the products or services properly denominated by the marks to the extent that such trademark rights may exist), Smalltalk, C++ or the like and conventional procedural programming languages, such as the “C” programming language or similar programming languages. The program code may execute entirely on a user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the latter scenario, the remote computer may be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or the connection may be made to an external computer (for example, through the internet using an Internet Service Provider).
Aspects of the present invention are described below with reference to flowchart illustrations and/or block diagrams of methods, apparatus (systems) and computer program products according to embodiments of the invention. It will be understood that each block of the flowchart illustrations and/or block diagrams, and combinations of blocks in the flowchart illustrations and/or block diagrams, can be implemented by computer program instructions. These computer program instructions may be provided to a processor of a general purpose computer, special purpose computer, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, create means for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
These computer program instructions may also be stored in a computer-readable medium that can direct a computer, other programmable data processing apparatus, or other devices to function in a particular manner, such that the instructions stored in the computer-readable medium produce an article of manufacture including instructions which implement the function/act specified in the flowchart and/or block diagram block or blocks.
The computer program instructions may also be loaded onto a computer, other programmable data processing apparatus, or other devices to cause a series of operational steps to be performed on the computer, other programmable apparatus or other devices to produce a computer-implemented process such that the instructions which execute on the computer or other programmable apparatus provide processes for implementing the functions/acts specified in the flowchart and/or block diagram block or blocks.
The present invention will now be described in detail with reference to the Figures.
As shown in
Server computer sub-system 102 may be a laptop computer, tablet computer, netbook computer, personal computer (PC), a desktop computer, a personal digital assistant (PDA), a smart phone, or any programmable electronic device capable of communicating with the client sub-systems via network 114. Software 240 is a representative set of program(s) in the form of a collection of machine readable instructions and data that is used to create, manage and control certain software functions that will be discussed in detail below.
Computer sub-system 102 is capable of communicating with other computer sub-systems via network 114 (see
It should be appreciated that
As shown in
Memory 208 and persistent storage 210 are computer-readable storage media. In general, memory 208 can include any suitable volatile or non-volatile computer-readable storage media. It is further noted that, now and/or in the near future: (i) external device(s) 214 may be able to supply, some or all, memory for computer sub-system 102; and/or (ii) devices external to computer sub-system 102 may be able to provide memory for use by computer sub-system 102.
Software 240 is in many respects representative of the various software of the present invention and is stored in persistent storage 210 for access and/or execution by one or more of the respective computer processor(s) 204, usually through one or more memories of memory 208. Persistent storage 210 is at least more persistent than a signal in transit is, but the persistent storage may, of course, be substantially less persistent than permanent storage. Software 240 may include both machine readable and performable instructions and/or substantive data (that is, the type of data stored in a database). In this particular embodiment, persistent storage 210 includes a magnetic hard disk drive. To name some possible variations, persistent storage 210 may include a solid state hard drive, a semiconductor storage device, read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, or any other computer-readable storage media that is capable of storing program instructions or digital information.
The media used by persistent storage 210 may also be removable. For example, a removable hard drive may be used for persistent storage 210. Other examples include optical and magnetic disks, thumb drives, and smart cards that are inserted into a drive for transfer onto another computer-readable storage medium that is also part of persistent storage 210.
Communication unit 202, in these examples, provides for communications with other data processing systems or devices external to sub-system 102, such as client computer sub-systems 104, 106, 108, 110, 112. In these examples, communication unit 202 includes one or more network interface cards. Communication unit 202 may provide communications through the use of either or both physical and wireless communications links. Any software modules discussed herein may be downloaded to a persistent storage device (such as persistent storage device 210) through a communications unit (such as communications unit 202).
I/O interface(s) 206 allows for input and output of data with other devices that may be connected locally in data communication with server computer 200. For example, I/O interface(s) 206 provides a connection to external device set 214. External device set 214 will typically include devices such as a keyboard, keypad, a touch screen, and/or some other suitable input device. External device set 214 can also include portable computer-readable storage media such as, for example, thumb drives, portable optical or magnetic disks, and memory cards. Software and data used to practice embodiments of the present invention, for example, mod 240, can be stored on such portable computer-readable storage media. In these embodiments the relevant software may (or may not) be loaded, in whole or in part, onto persistent storage device 210 via I/O interface(s) 206. I/O interface(s) 206 also connects in data communication with display device 212.
Display device 212 provides a mechanism to display data to a user and may be, for example, a computer monitor or a smart phone display screen.
The programs described herein are identified based upon the application for which they are implemented in a specific embodiment of the invention. However, it should be appreciated that any particular program nomenclature herein is used merely for convenience, and thus the invention should not be limited to use solely in any specific application identified and/or implied by such nomenclature.
“Customer community analytics,” is a term used herein to describe methods and/or associated machine logic that discovers how customers are connected with other customers of an enterprise and/or with third parties who may, or may not, have direct dealings with the enterprise. The exact link connecting customers with other customers varies from enterprise to enterprise and with the analytics scenario. For example, in the banking industry, one of the links connecting banking customers with each other is the payment/fund exchanged between or among them. There can be multiples of such groups or communities consisting of customers linked with each other. The link is a vector because it generally consists of several attributes such as: (i) amount of funds transferred; (ii) direction of transfer; (iii) mode of transfer (for example, electronic transfer, check, recurring transfer, etc.); and/or (iv) transfer of funds between customers belonging to different industries, geographies, etc.
The customer community also consists of other business entities such as entities offering banking support products (for example, credit cards, term deposit, insurance, etc.) to whom customers have transacted with and have made certain payment/funds transfer towards such products. For example, the quarterly payment made towards vehicle insurance establishes a link between the customer and that product, and, therefore, such products are also included in the customer communities discovered by the proposed method. The method that will now be described also discovers links between the customers of an enterprise with other customers and business entities outside the enterprise. For example in banking, if a customer having his account in Bank A purchases insurance from Insurance Company B and makes premium payments for the insurance policy from his Bank A account, then the customer community inferred in this case will also include the external products subscribed by this customer. Similarly, any payments or fund transfers made to other customers outside the bank are also inferred by the method and such entities are also included in the customer community analysis. The customers include all types of customers of an enterprise. In banking, for example, the customer set includes retail, corporate, small and medium enterprises (SME), etc.
The customer community analysis in the method to now be described assists the enterprise to infer customer communities of interest and relevant entities in each such community with any hot spot (the concept of a “hot spot” will be discussed further, below, in connection with step S336 of process 300a shown in
The method embodiment of the invention to be described below goes beyond customer analytics segmenting customers and inferring customer behavior. The method to be described below is relevant and applicable to industries where customers are connected and/or linked to each other. The customer community analytics of the method to be described below is founded on such links among customers and therefore goes beyond merely performing analytics on individual customer data.
As shown in
Processing begins at step S301 where enterprise software 240 (see
Processing proceeds to step S302 where analyze customer related data mod 402 (see
Processing proceeds to step S303 where generate graph sub-mod 403 of community graph mod 404 based on the customer community analytics of step S302. This graph (not shown in
Processing proceeds to step S310 where social interactions sub-mod 410 (see
Processing proceeds to step S312 where personalized recommendations, cross-sell, up-sell sub-mod 412 (see
Processing proceeds to step S314 where customer care sub-mod 414 (see
Processing proceeds to step S320 where financial supply chain pattern sub-mod 420 of financial supply chain mod 418 (see
Processing proceeds to step S322 where discover financial product sub-mod 422 uses the financial supply chain pattern to discover a financial services product used by a financial services customer.
Processing proceeds to step S324 where risk analytics mod 424 (see
Processing proceeds to step S330 where collect data sub-mod 430 of market and/or social media data mod 429 (see
Processing proceeds to step S332 where marketing plan sub-mod 432 (see
Processing proceeds to step S334 where acquire new customers sub-mod 434 acquires new SME and/or retail customers based, at least in part, upon the graph generated at step S303 and/or the market and/or social media data collected at step S330.
It is noted that each and every step of the foregoing process 300 will be performed and re-performed (not necessarily in order) as the bank enterprise does business through its website with its numerous customers. The graph generated by step S303 will tend to be expanded and enriched over time, as will the financial supply chain patterns discovered at step S320 and the market and/or social media data collected at step S330. This will generally work to the benefit of the customer in both the financial aspect and the social aspect of the customer's experience at the bank's website.
Processing proceeds to step S336 where hot spot mod 436 (see
To continue the example of the popular third party credit card issuer, the enterprise performing customer community analytics can: (i) easily identify this “concentration point” in the customer community; and (ii) leverage this concentration information for various types of responsive actions.
An example of an action taken in response to identification of a hot spot will now be discussed. A bank enterprise uses the identification of a third party credit card issuer hot spot to determine that the third party's credit card product is popular for a given set of customers (and/or potential customers) of the bank. In response, the bank enterprise: (i) identifies the beneficial features of the third party issuer's card; (ii) designs its own credit card similar features; and (iii) targets its customers (especially customers who have the third party credit card, or who share salient characteristics with those who have the third party credit card) to obtain the bank's new credit card. This is just one example of responding to a hot spot, and it will be understood that there are a great multitude of use cases and inferences that an enterprise can draw and use from hot spot analysis of a customer community analytics graph.
As a final note on hot spots, not every node which has many nodes connected to it will necessarily be considered as a “hot spot.” For example, many, many bank customers may make payments through the bank to the same electrical utility company, especially if only one company supplies electricity in the area in which the bank's customers are located. This is why “hot spot” was defined, above, in terms of an “unexpectedly” large number of connections, rather than merely as a large number of connections.
The flowchart and block diagrams in the foregoing Figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present invention. In this regard, each block in the flowchart or block diagrams may represent a module, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems that perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
In today's extremely competitive environment, enterprises want to understand their customer needs and behavior better for many reasons, such as: (i) to offer personalized recommendations; (ii) cross/up sell, etc.; (iii) to prevent any opportunity loss; and/or (iv) to improve customer care. Some embodiments provide customer community analytics that analyze transactions and other customer related data in the enterprise information systems to discover how and where customers are linked among each other and with other products/offerings or enterprises and the nature of this association. Some embodiments use this customer-relation (community) graph so that the enterprise can seamlessly understand potential customers and needs of existing customers to cross/up sell and also to retain customers.
As shown in
The process for discovering the customer community represented by graph 600 is called customer community analytics and this process involves analyzing transactions and/or other data to discover customer entities and business entities which are linked among each other by transactional relationships, personal relationships, employment relationships, contractual relationships and/or other relationships. It is noted that all of the node and relationship data of graph 600 is discovered by analyzing the data owned and controlled by the Bank entity and that graph 600 does not rely on external data.
Possible entities include: (i) individual customers of an enterprise (for example, bank, retail store, etc.); and (ii) other entities, not owned by the enterprise, such as SMEs (small and medium enterprises) and third party financial institutions.
Some embodiments provide for connecting customers for a personalized experience, for purposes such as acquiring new customers, cross/up sell, etc. In some embodiments, social networking tools are employed to connect similar customers.
One example of these features will now be set forth using an example involving a banking enterprise that sells insurance policies: (i) a retail banking customer B buys an insurance policy; (ii) using business rules (for example, edge-analytics), a pre-configured message is shown to customer B on website of the retail bank with an option to “share” the policy benefits with other customers (without disclosing identity); (iii) the “shared” message appears on the web site of the retail bank for relevant customers likely to buy insurance products; and (iv) these customers can connect and blog with customer B on the community portal to engage in discussion, learn more details, benefits, process, etc. about the policy. With regard to item (iii) in the foregoing example, relevant customers are determined based on community analytics, rules, etc. With regard to item (iv) in the foregoing example, the other customers can connect and blog with customer B by simply clicking the shared message that appears to them per item (iii). The blog provides a common platform for customers to discuss issues related to purchases made through the enterprise.
Another example of these features will now be set forth using an example involving a banking enterprise that refinances housing loans: (i) retail customer A “shares” a pre-configured message about the benefits of refinancing housing loan (without disclosing her real-world identity); (ii) the shared message appears on the website of the banking enterprise to ‘relevant’ customers having existing housing loan from a third party bank (a bank other than the banking enterprise); and (iii) the customers connect and blogs with customer A on the community portal. With regard to item (iii) in the foregoing example, customers may go to the community portal: (a) to learn more about the process, new EMI (equal monthly installment), etc.; and (b) by simply clicking on the message shown them per item (ii).
Some embodiments provide for connecting customers for a personalized experience (to acquire new SME and retail customers). In these embodiments, new products and new tools establish (soft) business relationships with potential new customers. Some examples of these new tools and/or new products will be discussed in the following paragraphs.
One such new product is a new bank check printed and/or displayed with names of transacting SMEs. In current check-printing practice, only the name and account number of a bank's customer is printed on the check. For example, if a Customer C has an account with Bank A, then a check for Customer C's account will be printed with Customer C's name and account number. However, according to some embodiments of the present invention: (i) the bank can infer entities to whom a customer frequently writes checks; and (ii) using this information, the bank can also print the name of such entity on the ‘Pay To’ section of at least some of the customer's checks. For example, a bank can issue pre-printed checks with the name of a customer's apartment company where that customer makes a monthly rent payment by check. In the corporate sector, such scenarios are more prominent—especially in supply chain, retail, manufacturing, insurance etc., where the customer issues the check to the same company repeatedly a few times a month.
Another such new product is a new bank check printed and/or displayed with a link to access transaction reports online for: (i) transactions between two companies (for example, companies called X and K); and/or (ii) transactions with a single, particular company. An example of this is shown in
One example of a new tool is a tool to manage and track purchase orders, invoices, payments, reports and BI (business intelligence).
A process for enriching customer community profiles and/or data will now be discussed with reference to
As shown in
In graph 800: (i) potential customers C and D 802, 804 do not have accounts with the Bank; (ii) customers A and B 810, 812 are customers of the Bank; (iii) SMEs L, J and K 806, 830, 832 are not customers of the Bank; (iv) SMEs X, Y and Z 828, 835, 834 are customers of the bank; (v) housing finance company 822 is a third party (that is, not part of the enterprise) that offers a third party product; (vi) credit card company 826 is a third party that offers a third party product; (vii) fixed deposit 850 is an existing product of the Bank enterprise; (viii) management and employees node sets 852, 854 are management and employees of J SME and K SME, respectively, who may or may not be bank customers themselves; and (ix) congratulatory communication node 860 represents a communication made between customer A 810 and non-customer D 804 on a third party social media site.
Using the customer community information of the types shown in
Some specific examples of discovery of enriched customer community data in graph 800 of
Some embodiments have one or more of the following features: (i) discovery of a customer community (of an enterprise) based on financial transactions; (ii) discovery of a financial supply chain pattern in the customer community; (iii) discovery of a third party financial product used by a financial services customer; (iv) cross-sell and/or up-sell analytics based on a customer community and/or a financial supply chain pattern; (v) risk analytics based on a customer community and/or a financial supply chain pattern; (vi) inferring customer community/links within a bank-type enterprise (herein simply referred to as a “bank”; (vii) discovery of a customer community within a bank; (viii) self-discovery of a customer community within a bank by analyzing transactions of customers; (ix) discovery of a financial supply chain pattern among the customers within the discovered community; (x) discovery of third party products/services subscribed to by community members; (xi) cross-sell and/or up-sell offers for community members; (xii) discovery of a transaction relationship among the community members; and/or (xiii) risk alerts/analytics.
It is noted that
Present invention: should not be taken as an absolute indication that the subject matter described by the term “present invention” is covered by either the claims as they are filed, or by the claims that may eventually issue after patent prosecution; while the term “present invention” is used to help the reader to get a general feel for which disclosures herein that are believed as maybe being new, this understanding, as indicated by use of the term “present invention,” is tentative and provisional and subject to change over the course of patent prosecution as relevant information is developed and as the claims are potentially amended.
Embodiment: see definition of “present invention” above—similar cautions apply to the term “embodiment.”
And/or: non-exclusive or; for example, A and/or B means that: (i) A is true and B is false; or (ii) A is false and B is true; or (iii) A and B are both true.
User: includes, but is not necessarily limited to, the following: (i) a single individual human; (ii) an artificial intelligence entity with sufficient intelligence to act as a user; and/or (iii) a group of related users.
