Automated Electronic Commerce Data Extracting and Analyzing System

• US 20080262960A1
• Filed: 04/16/2008
• Published: 10/23/2008
• Est. Priority Date: 04/18/2007
• Status: Abandoned Application

• Current Assignee: Transmend I2 Incorporated
• Original Assignee: Transmend I2 Incorporated
• Inventors: Malone, Wade, Herbst, Stephen, Frohwein, Robert, Ku, Tze Ming
• Application Number:
  US12/104,346
• Publication Number:
  US 20080262960A1
• Time in Patent Office: Days
• US Class Current: 705/37
• CPC Class Codes: G06Q 30/0601 Electronic shopping [e-shopping]
• CPC Class Codes: G06Q 30/08 Auctions
• CPC Class Codes: G06Q 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

A method, apparatus, and computer readable storage to implement an automatic e-commerce site monitoring system. Data can be automatically gathered from online e-commerce sites such as online auctions and analyzed and stored in a database. A merchant can query the database to find all e-commerce sites selling their products. Suspicious transactions can automatically be identified to the merchant who then may have the option to shut down the particular offending sales. A suspicious transaction may be one that has characteristics likely of some prohibited activity, such as selling counterfeit or grey market goods.

Claims

1. A computer implemented method to display auction data, the method comprising:

automatically visiting at least one online auction site using a robot and automatically retrieving auction data from the at least one online auction site, the auction data comprising individual sales and their respective sales information, and storing the auction data in a database;

receiving sales properties from a user; and

retrieving a subset of the sales data from the database based on the properties and displaying the subset to the user.

2. The method as recited in claim 1, wherein the automatically visiting comprises visiting at least two different online auction sites.

3. The method as recited in claim 2, wherein the properties comprise identities of two different auction sites and the displaying merges auction data from the two different auction sites into a single display.

4. The method as recited in claim 1, further comprising

automatically applying rules to a particular auction in the auction database to determine whether the particular auction has characteristics associated with undesirable activity, and if so, then associating a high warning level to the particular auction;

and

displaying the high warning level along with data relating to the particular auction.

5. The method as recited in claim 4, wherein a low warning level can also be associated to the particular auction if the characteristics of the particular auction do not meet a threshold needed for the high warning level.

6. The method as recited in claim 1, further comprising:

automatically applying rules to a plurality of the auctions in the auction data to determine an irregular auction list and outputting the irregular auction list.

7. The method as recited in claim 1, wherein the retrieving auction data comprises automatically submitting a keyword search in the online auction site and retrieving all results of the keyword search.

8. The method as recited in claim 1, wherein the properties comprise a particular warning level and the displaying limits output to only auctions associated with the particular warning level.

9. The method as recited in claim 8, wherein the auction data comprises auctions from at least two different auction sites.

10. A computer implemented method to determine suspicious activity on an e-commerce site, the method comprising:

reviewing first data comprising information on a first online sale offer offered by a username on an e-commerce site; and

applying rules to the first data and additional sales data stored in a database to determine a warning level for the first online sale offer, the additional sales data comprising data describing transactions aside from the first online sale offer.

11. The method as recited in claim 10, wherein the applying determines whether there is a correlation between the username and a flagged sale in the additional sales data, the flagged sale flagged as violating or having been suspected of violating the e-commerce site'"'"'s or merchant rules.

12. The method as recited in claim 10, wherein the first online sale offer is conducted at a different e-commerce site than at least one transaction in the additional sales data.

13. The method as recited in claim 10, wherein the applying evaluates whether the username correlates to a seller involved in another transaction in the additional sales data while using a different username.

14. The method as recited in claim 13, wherein the applying compares a time the first online sale offer was created with times that other transactions in the additional sales data were completed.

15. The method as recited in claim 13, wherein the applying compares a time the seller of the first online sale offer was created with times that sellers of other transactions in the additional sales data were banned or their auction shut down.

16. The method as recited in claim 10, wherein the applying compares item descriptions in the first online auction with item descriptions in other transactions in the sales data.

17. The method as recited in claim 10, wherein the applying compares a price of the first online sale offer to prices of similar or identical goods in other transactions in the additional sales data.

18. The method as recited in claim 10, wherein the e-commerce site is an online auction site.

19. A computer implemented method to retrieve auction data, the method comprising:

automatically visiting an online auction site and automatically retrieving individual auction data for an individual auction;

ascertaining a seller of the individual auction;

determining that the seller is not in a database storing auction data;

automatically placing a nominal bid on an item for auction in the individual auction;

receiving additional seller data from the online auction site; and

storing the additional seller data in the database.

20. The method as recited in claim 19, wherein the seller is identified by the seller'"'"'s username on the online auction site.