Computer architecture and method for supporting and analyzing electronic commerce over the world wide web for commerce service providers and/or internet service providers

• US 6,934,687 B1
• Filed: 11/20/1997
• Issued: 08/23/2005
• Est. Priority Date: 11/20/1997
• Status: Expired due to Term

• Current Assignee: NCR Voyix Corporation
• Original Assignee: NCR Corporation
• Inventors: Papierniak, Karen A., Woodford, Susan L., Chiang, Luo-Jen, Thaisz, James E., Betz, Eugene M.
• Primary Examiner(s): Myhre, James W.
• Application Number:
  US08/975,428
• Time in Patent Office: 2,833 Days
• Field of Search: 705/1, 705/7, 705/10, 709/224
• US Class Current: 705/7.34
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 10/06395 Quality analysis or management
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0201 Market modelling; Market analysis; Collecting market data
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration

Abstract

A computer system that supports and analyzes Internet and/or electronic commerce data includes at least one user station transmitting a user request, and at least one Internet server, connectable to the user station, and providing the user station access to external data sources. The computer system also includes at least one data collection and analysis system. The data collection and analysis system includes at least one analysis module performing statistical and analytical analysis of the Internet and/or electronic commerce data for use by a user in performing one or more business decisions, and at least one Internet and/or electronic commerce data warehouse which is responsively connected to the analysis module and separated from external systems. The data warehouse receives the Internet and/or electronic commerce data, and provides access to the Internet and/or electronic commerce data by the user. The data collection and analysis system also includes at least one data mapping module which searches, collects and transforms the Internet and/or electronic commerce data, and transmits the same to the data warehouse for storage.

Claims

1. A method of supporting and analyzing electronic commerce data for electronic commerce service providers using a computer, comprising the steps of:

(a) determining data elements required for analyzing the Internet and/or electronic commerce over the World Wide Web;

(b) providing a decision support user with one or more options for data searching from multiple data sources in the form of operational activities responsive to decision support user of operational activities responsive to decision support user specified criteria;

(c) structuring and storing the data elements obtained in said step (b), including parsing, categorizing, indexing, and formatting the data elements;

(d) analyzing the data elements stored in said step (c), including recognizing at least one of patterns, trends, exceptions of the data elements based on statistic and analytic manipulation techniques; and

(e) iteratively performing said steps (a), (b), (c), and (d), to provide at least one of solution navigation, iterative learning, and decision guidance.

2. The method according to claim 1, wherein said step (b) further comprises providing the decision support user with one or more options for data collection, the data collection comprising at least one of:

(1) substantially real-time data collection where a first time between locating the data elements and the data collection is substantially a same time,

(2) substantially on-line data collection where a second time between locating the data elements and the data collection is substantially dependent on at least one of the data elements require a certain time interval to accumulate a predetermined volume, and the data collection is not imminent but requires at least some coordination, and

(3) substantially off-line data collection where a third time between locating the data elements and the data collection require no coordination.

3. The method according to claim 2, wherein the decision support user specified criteria include when and how the data collection is executed.

4. The method according to claim 1, wherein said structuring step (c) further includes the step of organizing the data elements in a structured format in accordance with a data layout and segmentation.

5. The method according to claim 1, wherein said analyzing step (d) further includes the step of providing the decision support user with one or more recommended actions for subsequent decision making.

6. The method according to claim 1, wherein said decision support user specified criteria comprise customer-based management-related-criteria for analyzing profile data including at least one of relative value, behavioral characteristics, and preferences of individual subscribers who subscribe to at least one service provided by at least one of the electronic commerce service providers, and non-subscribers who do not subscribe to any service provided by the electronic commerce service providers.

7. The method according to claim 6, wherein the profile data related to the subscribers includes:

company name

company administrator name

subscriber name

address including city, state, zip code

phone number including at least one of day, night and fax

subscriber login name and/or IP address

email address

chosen Point of Presences

credit card information including card type, number, name of the card,

domain name

billing contact

subscriber selection of services including dial-up services, business ISDN services, corporate email service, server hosting, corporate web services, and

subscriber chosen service plans and associated pricing information.

8. The method according to claim 6, wherein the profile data related to the non-subscribers includes non-subscriber profile data, responsive to information a visited application is able to obtain from the non-subscriber and what the non-subscriber is willing to enter into the visited application.

9. The method according to claim 1, wherein the following operational activities are linked including a client activity, an application activity including hosting and commerce services, and access activity.

10. The method according to claim 9, wherein the access activity comprises interfacing with other web-accessible systems, including at least one of modem pools and routers.

11. The method according to claim 9, wherein the client activity comprises the following data:

domain names and IP addresses of systems and/or users making requests,

access names and access IP addresses of client systems accessing a site,

referer lists indicating where users are accessing a server,

most common visitor domains,

most common external references,

first time visitors,

returning visitors,

most frequent visitors,

visitors per visitor category,

visits per visitor category,

client demographics including geography, age, income, profession,

where do people come from when accessing an area, and

where clients go from the area accessed.

12. The method according to claim 9, wherein the application activity comprises the following data:

hits to a site,

new contents for the site,

number of files sent,

hot hits including most frequently accessed files,

most popular pages,

types of transactions,

date and time of transactions,

time spent in a particular area,

average time spent in the area,

number of exits before a first page is transmitted,

details of most popular objects,

details of most popular pages,

details of least popular objects,

details of least popular pages,

details of most popular entrance pages,

details of most popular content categories,

next click analysis,

visits per content category, and

visits to content combinations.

13. The method according to claim 1, wherein said method is implemented in a distributed on-line, and interactive environment including multiple client browsers, or networked clients.

14. The method according to claim 13, wherein the multiple client browsers of networked clients are capable of accessing a SmartEC™

server storing information.

15. The method according to claim 14, wherein the multiple client browsers or networked clients are capable of accessing a SmartEC™

server storing information including customer support material and sales campaign schedules.

16. The method according to claim 1, wherein said step (a) comprises the step of determining whether the data elements are located in open, closed, or registered environments.

17. The method according to claim 1, wherein said decision support user specified criteria comprise business operations management-related criteria for to monitoring and analyzing at least one of:

business metrics including at least one of revenue, expenses, profitability, and subscriber based metrics,

quality of service metrics,

marketing initiative metrics, and

competitive influence metrics.

18. The method according to claim 1, wherein said decision support user specified criteria comprise electronic-commerce management-related criteria for measuring success of at least one of:

electronic-commerce applications to conduct commerce over the internet, and

on-line content applications to add value to the service offering.

19. The method according to claim 1, wherein the data elements are determined dynamically in response to said decision support user specified criteria.

20. A computer system for supporting and analyzing electronic commerce data for electronic commerce service providers, comprising:

at least one decision maker station connectable to

at least one data collection and analysis system including

at least one analysis module providing a mathematical engine to perform statistical and analytical analysis of the electronic commerce data in response to one or more business decision support requests sent from the decision maker station, said mathematical engine generating said analysis of the electronic commerce data being representative of business operational data integrated with web-specific data from multiple data sources to provide decision-support information in a business, rather than a technical, web site specific context;

at least one electronic commerce data warehouse, responsively connected to said at least one analysis module and separated from external operational web-accessible systems including web servers and web-based databases, receiving and storing the electronic commerce data received from the external web-accessible systems for said analysis by said at least one analysis module, wherein the electronic commerce data is stored in said at least one electronic commerce data wave house being time-stamped, associated with a defined period of time, and subject-oriented including customer and product activities;

at least one data mapping module, responsively connected to said at least one electronic commerce data warehouse, searching and transforming the electronic commerce data, and transmitting the electronic commerce data transformed to said at least one electronic commerce data warehouse.

21. The computer system according to claim 20, wherein the electronic commerce data received from the external web-accessible systems via said at least one data mapping module includes system logs including at least one of access logs, agent logs, and referer logs on the web servers, and user profiles including at least one of customers, and visitors.

22. The computer system according to claim 20, wherein change of the electronic commerce data stored in said at least one electronic commerce data warehouse is responsive to changes in said one or more business decision support requests, and update from one of the data sources.

23. The computer system according to claim 20, wherein said at least one electronic commerce data warehouse provides access to an administrator to determine and control said searching and information flow between the external operational web-accessible systems and said at least one electronic commerce data warehouse.

24. The computer system according to claim 23, wherein said at least one electronic commerce data warehouse provides the administrator the ability to initiate at least one of addition, and deletion of the electronic commerce data in said at least one electronic commerce data warehouse according to an appropriate time based on predetermined criteria.

25. The computer system according to claim 23, wherein said at least one electronic commerce data warehouse provides the administrator the ability to initiate a structural change of the electronic commerce data in said at least one electronic commerce data warehouse.

26. The computer system according to claim 20, wherein the electronic commerce data received from the external web-accessible systems via said at least one data mapping module includes an identity of a visitor visiting an area, what the visitor is looking at, and what resources the visitor is using.

27. The computer system according to claim 20, wherein the external data sources include external analysis applications responsive to the electronic commerce data.

28. The computer system according to claim 20, wherein the user profiles further include transient travelers.

29. The computer system according to claim 20, further comprising an electronic commerce service provider station connected to said at least one decision maker station and said at least one data collection and analysis system for transmitting said one or more business decision support requests and said analysis therebetween.

30. The computer system according to claim 29, wherein the electronic commerce service provider station is a web server.