TIMING COMMERCIAL OFFERS BASED ON LONG-TERM USER DATA

• US 20090198557A1
• Filed: 01/31/2008
• Published: 08/06/2009
• Est. Priority Date: 01/31/2008
• Status: Abandoned Application

• Current Assignee: Intuit, Inc.
• Original Assignee: Intuit, Inc.
• Inventors: Gevelber, Lisa C., Wang, Gang
• Application Number:
  US12/024,020
• Publication Number:
  US 20090198557A1
• Time in Patent Office: Days
• US Class Current: 705/14.61
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0264 based upon schedule
• CPC Class Codes: G06Q 30/0603 Catalogue ordering

Abstract

One embodiment of the present invention provides a system that times commercial offers made to a user. During operation, the system starts by receiving financial history data for the user, wherein the financial history data includes purchase records for a set of purchases. The system then identifies a subset of purchases in the set of purchases, wherein the subset of purchases are semantically linked to a set of predetermined subjects. Next, the system identifies timing patterns in the subset of purchases based on timing information associated with the subset of purchases. The system then presents one or more commercial offers to the user at specific times based on the identified timing patterns.

Claims

1. A method for timing commercial offers made to a user, comprising:

receiving financial history data for the user, wherein the financial history data includes purchase records for a set of purchases;

identifying a subset of purchases in the set of purchases, wherein the subset of purchases are semantically linked to a set of predetermined subjects;

identifying timing patterns in the subset of purchases based on timing information associated with the subset of purchases; and

presenting one or more commercial offers to the user at specific times based on the identified timing patterns.

2. The method of claim 1, wherein identifying the subset of purchases involves:

for each purchase in the set of purchases, performing a semantic analysis on the associated purchase record to determine if the purchase is linked to at least one of the predetermined subjects; and

if so, adding the purchase into the subset of purchases.

3. The method of claim 2, wherein the semantic analysis can involve:

a data-mining technique;

an ontology analysis;

a natural-language processing technique;

a categorization technique; and

a pattern-recognition technique.

4. The method of claim 2, wherein the purchase record for a purchase can include:

a purchase time;

vendor information;

product information;

a cost amount;

automatically defined categorization information;

user-defined categorization information; and

other purchase-related information.

5. The method of claim 2, wherein prior to identifying the timing patterns, the method further comprises:

tagging each purchase in the subset of purchases with one or more semantically linked predetermined subjects; and

grouping the subset of purchases based on the associated predetermined subjects.

6. The method of claim 5, wherein identifying the timing patterns in the subset of purchases based on the timing information involves identifying periodically recurring purchases tagged with the same predetermined subject.

7. The method of claim 6, wherein identifying the timing patterns involves performing a timing analysis on the purchases tagged with the same predetermined subject.

8. The method of claim 7, wherein the timing analysis can include a Fourier analysis and other time-series-analysis techniques.

9. The method of claim 1, wherein making commercial offers to the user at specific times based on the timing patterns involves:

receiving a set of commercial offers, wherein each commercial offer in the set of commercial offers is associated with one or more predetermined subjects;

for an identified timing pattern and associated purchases,

selecting a subset of commercial offers which are associated with the same predetermined subject that matches a subject for the associated purchases;

filtering the subset of commercial offers based on the identified timing pattern to obtain one or more commercial offers having timing constraints which are consistent with the identified timing pattern; and

presenting the one or more commercial offers to the user at a specific time which is determined by the identified timing pattern.

10. The method of claim 9, wherein the method further comprises:

creating a package offer by grouping the one or more coordinated commercial offers; and

presenting the package offer to the user at a specific time determined by the identified timing pattern.

11. The method of claim 1, wherein the predetermined subjects can include:

a family vacation;

a birthday;

an anniversary;

a holiday;

back-to-school purchases;

car maintenance; and

other spending-related events.

12. The method of claim 1, wherein the financial history data for the user is collected over a period of time which is long enough to detect timing patterns.

13. A computer-readable storage medium storing instructions that when executed by a computer cause the computer to perform a method for timing commercial offers made to a user, the method comprising:

receiving financial history data for the user, wherein the financial history data includes purchase records for a set of purchases;

identifying a subset of purchases in the set of purchases, wherein the subset of purchases are semantically linked to a set of predetermined subjects;

identifying timing patterns in the subset of purchases based on timing information associated with the subset of purchases; and

presenting one or more commercial offers to the user at specific times based on the identified timing patterns.

14. The computer-readable storage medium of claim 13, wherein identifying the subset of purchases involves:

for each purchase in the set of purchases, performing a semantic analysis on the associated purchase record to determine if the purchase is linked to at least one of the predetermined subjects; and

if so, adding the purchase into the subset of purchases.

15. The computer-readable storage medium of claim 14, wherein the semantic analysis can involve:

a data-mining technique;

an ontology analysis;

a natural-language processing technique;

a categorization technique; and

a pattern-recognition technique.

16. The computer-readable storage medium of claim 14, wherein the purchase record for a purchase can include:

a purchase time;

vendor information;

product information;

a cost amount;

automatically defined categorization information;

user-defined categorization information; and

other purchase-related information.

17. The computer-readable storage medium of claim 14, wherein prior to identifying the timing patterns, the method further comprises:

tagging each purchase in the subset of purchases with one or more semantically linked predetermined subjects; and

grouping the subset of purchases based on the associated predetermined subjects.

18. The computer-readable storage medium of claim 17, wherein identifying the timing patterns in the subset of purchases based on the timing information involves identifying periodically recurring purchases tagged with the same predetermined subject.

19. The computer-readable storage medium of claim 18, wherein identifying the timing patterns involves performing a timing analysis on the purchases tagged with the same predetermined subject.

20. The computer-readable storage medium of claim 19, wherein the timing analysis can include a Fourier analysis and other time-series-analysis techniques.

21. The computer-readable storage medium of claim 13, wherein making commercial offers to the user at specific times based on the timing patterns involves:

receiving a set of commercial offers, wherein each commercial offer in the set of commercial offers is associated with one or more predetermined subjects;

for an identified timing pattern and associated purchases,

selecting a subset of commercial offers which are associated with the same predetermined subject that matches a subject for the associated purchases;

filtering the subset of commercial offers based on the identified timing pattern to obtain one or more commercial offers having timing constraints which are consistent with the identified timing pattern; and

presenting the one or more commercial offers to the user at a specific time which is determined by the identified timing pattern.

22. The computer-readable storage medium of claim 21, wherein the method further comprises:

creating a package offer by grouping the one or more coordinated commercial offers; and

presenting the package offer to the user at a specific time determined by the identified timing pattern.

23. The computer-readable storage medium of claim 13, wherein the predetermined subjects can include:

a family vacation;

a birthday;

an anniversary;

a holiday;

back-to-school purchases;

car maintenance; and

other spending-related events.

24. The computer-readable storage medium of claim 13, wherein the financial history data for the user is collected over a period of time which is long enough to detect timing patterns.

25. A system for timing commercial offers made to a user, comprising:

a receiving mechanism configured to receive financial history data for the user, wherein the financial history data includes purchase records for a set of purchases;

an identifying mechanism configured to identify a subset of purchases in the set of purchases, wherein the subset of purchases are semantically linked to a set of predetermined subjects;

wherein the identifying mechanism is further configured to identify timing patterns in the subset of purchases based on timing information associated with the subset of purchases; and

a presenting mechanism configured to present one or more commercial offers to the user at specific times based on the identified timing patterns.