Dynamic Product/Service Recommendations

• US 20120173324A1
• Filed: 12/15/2011
• Published: 07/05/2012
• Est. Priority Date: 12/29/2010
• Status: Abandoned Application

• Current Assignee: PayPal, Inc. (PayPal Holdings, Inc.)
• Original Assignee: eBay Inc.
• Inventors: Vallery, Christina Marie, Leddy, William
• Application Number:
  US13/326,548
• Publication Number:
  US 20120173324A1
• Time in Patent Office: Days
• US Class Current: 705/14.25
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0224 based on user history
• CPC Class Codes: G06Q 30/0269 based on user profile or attribute
• CPC Class Codes: G06Q 30/0631 Item recommendations

Abstract

Systems and methods according to one or more embodiments facilitate electronic commerce over a network. In an embodiment, a method comprises creating a user profile comprising information including data entered by a primary user related to a product or service on a user device as well as data from other users that are related to or have common interests with the primary user, wherein the user profile dynamically changes based on, at least in part, new actions by the primary user as well as new actions by the other users. The method also comprises weighing the information in the user profile to determine targeted recommendations for the primary user. And the method further comprises providing the targeted recommendations to the primary user based on the user profile.

Claims

1. A method for facilitating electronic commerce over a network, the method comprising:

creating a user profile comprising information including data entered by a primary user related to a product or service on a user device as well as data from other users that are related to or have common interests with the primary user, wherein the user profile dynamically changes based on, at least in part, new actions by the primary user as well as new actions by the other users;

weighing the information in the user profile to determine targeted recommendations for the primary user; and

providing the targeted recommendations to the primary user based on the user profile.

2. The method of claim 1, further comprising delivering relevant notifications to the primary user about desired products or services, wherein the delivering further comprises delivering deals or finds on the desired products or services directly to the user device and allowing the primary user to either purchase the desired products or services using a payment provider, explore auctions, or tell the other users about the deals.

3. The method of claim 1, further comprising allowing the primary user to enter search information for the product or service on the user device via a standard search, via a product code search or via a like or vague item search.

4. The method of claim 3, further comprising:

if there is a deal available for the product or service upon entering of the search information, delivering the deal for the product or service to the primary user on the user device;

if there is no deal available for the product or service upon entering of the search information, allowing the primary user to save the search information for the product or service, and alerting the primary user as soon as a deal comes available.

5. The method of claim 4, further comprising allowing the primary user to share with the other users when a deal is available, wherein the allowing the primary user to share further comprises allowing the user to post and receive messages, via the user device, to the other users by sending a message directly to one of the other users, or posting to an associated website or social media.

6. The method of claim 1, wherein the user profile comprises at least one of user search information, user purchases, user-entered data, user past preferences, or purchases and searches from the other users.

7. The method of claim 1, wherein the creating the user profile that is dynamically changing further comprises continually changing the user profile with the new actions by the other users, wherein the information in the user profile is weighted based on how closely aligned another one of the other users is with the primary user.

8. The method of claim 1, further comprising allowing the primary user to see information on products or services that the other users have found.

9. The method of claim 1, wherein the weighing further comprises determining a score for a new product or service based on attributes of the new product or service compared to data in the user profile and filtering the score against a threshold, wherein the providing of the targeted recommendations to the primary user is made if the threshold is met.

10. The method of claim 1, further comprising matching one or more like-minded twin users having similar preferences as the primary user, and sharing recommendations between the primary user and the one or more twin users.

11. A system comprising:

a client device interacting with at least one or more processors over a network; and

one or more memories adapted to store a plurality of machine-readable instructions which when executed by the one or more processors are adapted to cause the system to;

load an application on the client device wherein a primary user of the client device is allowed to enter data related to a product or service using the client device;

create a user profile comprising information including the data entered by the primary user as well as information from other users that are related to or have common interests with the primary user, wherein the user profile dynamically changes based on, at least in part, new actions by the primary user as well as new actions by the other users;

weigh the information in the user profile to determine targeted recommendations for the primary user; and

provide the targeted recommendations to the primary user based on the weighted information of the user profile.

12. The system of claim 11, wherein the plurality of machine-readable instructions are further adapted to cause the system to retrieve information to find relevant search results contributing to one or more keywords.

13. The system of claim 11, wherein the plurality of machine-readable instructions are further adapted to cause the system to parse data received from at least one data stream that identifies new products or services, and changes to products or services, and extracts relevant keywords.

14. The system of claim 13, wherein the plurality of machine-readable instructions are further adapted to cause the system to take the extracted relevant keywords and apply them as attributes against a particular product or service, and compare the particular product or service attributes against attributes stored in the user profile to determine how closely the particular product or service matches interests of the primary user.

15. The system of claim 14, wherein the plurality of machine-readable instructions are further adapted to cause the system to weigh the attributes stored in the user profile, and sum all the attributes to determine a score for the primary user, and if there are no attributes stored in the user profile, derive an initial value of an attribute by summing an attribute weighting from the other users.

16. The system of claim 15, wherein the plurality of machine-readable instructions are further adapted to cause the system to compare the score with a threshold to determine if the particular product or service is to be recommended to the primary user now or later.

17. The system of claim 13, wherein the plurality of machine-readable instructions are further adapted to cause the system to keep each product or service through a lifecycle managed by a state machine.

18. A system comprising:

a user device having an application downloaded therein that allows a primary user to enter information related to products or services;

at least one storage device that stores a user profile comprising the information entered by the primary user, and community user information of other users, wherein the other users have an affinity with the primary user based on comparisons of distance or attribute preferences between the primary user and the other users;

at least one processor that interacts with the user device and the at least one storage device, wherein the at least one processor executes a plurality of machine-readable instructions adapted to cause the system to;

create the user profile comprising information including the information entered by the primary user as well as information from the other users based on their affinity with the primary user, wherein the user profile dynamically changes based on, at least in part, new actions by the primary user as well as new actions by the other users;

weigh the information in the user profile to determine targeted recommendations for the primary user; and

provide the targeted recommendations to the primary user based on the user profile.

19. The system of claim 18, further comprising a webscraper that retrieves information to find relevant search results contributing to one or more keywords, wherein the information retrieved by the webscraper is supplemented with user personal information.

20. The system of claim 18, further comprising a parser that parses data received from at least one data stream that identifies new products or services, and changes to products or services, and extracts relevant keywords.

21. The system of claim 20, further comprising a keyword matcher and a keyword manager that take the extracted relevant keywords from the parser and apply them as attributes against a particular product or service.

22. The system of claim 21, wherein the at least one processor executes a plurality of machine-readable instructions further adapted to cause the system to compare the particular product or service attributes against attributes in the user profile stored in the storage device to determine how closely the particular product or service matches interests of the primary user.

23. The system of claim 22, wherein the at least one processor executes a plurality of machine-readable instructions further adapted to cause the system to weigh the user profile attributes, and uses a sum of all the attributes to determine a score for the primary user, and if there are not user profile attributes, an initial value of an attribute is derived by summing an attribute weighting from the other users based on the affinity between the primary user and the other users.

24. The system of claim 23, wherein the at least one processor executes a plurality of machine-readable instructions further adapted to cause the system to compare the score with a threshold to determine if the particular product or service is to be presented to the primary user now or later.

25. The system of claim 21, wherein the application further allows the primary user to provide feedback on the particular product or service, wherein the feedback is recorded for the particular product or service and applied to associated attributes, wherein the at least one processor executes a plurality of machine-readable instructions adapted to cause the system to analyze the feedback to determine a user'"'"'s relative value per attribute.