Method and System for Predicting Purchases

• US 20070271141A1
• Filed: 03/01/2007
• Published: 11/22/2007
• Est. Priority Date: 03/01/2006
• Status: Abandoned Application

• Current Assignee: Paul Vickers Storm
• Original Assignee: Paul Vickers Storm
• Inventors: Storm, Paul V.
• Application Number:
  US11/680,715
• Publication Number:
  US 20070271141A1
• Time in Patent Office: Days
• US Class Current: 705/16
• CPC Class Codes: G06Q 20/20 Point-of-sale [POS] network systems
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions

Abstract

Some traditional brick-and-mortar stores, such as grocery stores, have encountered difficulties in using the online marketplace. There are a litany of reasons for this, but one reason is that the online marketplace is simply inconvenient. One purpose for the online marketplace is to make the lives of customers easier. These traditional stores can take advantage of this by utilizing purchasing data to generate lists to predict purchases for delivery, pick up, or simply as a reminder. By transmitting predicted shopping lists to consumers, more consumers would be more inclined to utilize the online and delivery services because the load on the consumers would be greatly reduced. Therefore, the predictive message service provided herein provides many benefits that have not, to this point, been available.

Claims

1. A method in an electronic data processing system, comprising:

calculating a purchase probability and a purchase frequency for at least one item of a plurality of items as a function of previous purchases associated with a customer identifier;

generating at least one list as a function of said purchase probability and said purchase frequency that includes at least one item;

transmitting at least one electronic message to a customer associated with said customer identifier; and

providing said list in said electronic message.

2. The method of claim 1, wherein the method further comprises inquiring in said electronic message if any item on said list is to be prepared for pick up.

3. The method of claim 1, wherein said item is selected from the group consisting of a product group and a product.

4. The method of claim 1, wherein the step of transmitting further comprises sequentially transmitting a plurality of electronic messages to said customer associated with said customer identifier, wherein the period between each of said plurality of electronic messages for said customer is predetermined as a function of said purchase probability and said purchase frequency.

5. The method of claim 4, wherein the step of calculating further comprises:

calculating said purchase probability by dividing the total number of item purchases by the number of purchase events; and

calculating said purchase frequency by determining the average period between sequential purchases of said item.

6. The method of claim 1, wherein the step of calculating further comprises:

populating a database with a plurality of purchase entries;

associating each purchase entry with at least one item of said plurality of items and with at least one customer identifier of a plurality of customer identifiers;

calculating a purchase frequency for each customer identifier; and

calculating a plurality of purchase probabilities for each item, wherein each purchase probability is associated with at least one customer identifier.

7. The method of claim 1, wherein the method further comprises inquiring in said electronic message if any item on said list is to be delivered.

8. The method of claim 7, wherein the step of inquiring further comprises inquiring in said electronic message if any other items are to be delivered.

9. The method of claim 1, wherein the method further comprises:

recognizing a mobile station of a customer associated with said customer identifier upon entering a store; and

transmitting a reminder list to said mobile station.

10. A computer program, comprising:

computer code for calculating a purchase probability and a purchase frequency for at least one item of a plurality of items as a function of previous purchases associated with a customer identifier;

computer code for generating at least one list as a function of said purchase probability and said purchase frequency that includes at least one item;

computer code for transmitting at least one electronic message to a customer associated with said customer identifier; and

computer code for providing said list in said electronic message.

11. The method of claim 10, wherein the computer program further comprises computer code for inquiring in said electronic message if any item on said list is to be prepared for pick up.

12. The computer program of claim 10, wherein said item is selected from the group consisting of a product group and a product.

13. The computer program of claim 10, wherein the computer code for transmitting further comprises computer code for sequentially transmitting a plurality of electronic messages to said customer associated with said customer identifier, wherein the period between each of said plurality of electronic messages for said customer is predetermined as a function of said purchase probability and said purchase frequency.

14. The computer program of claim 13, wherein the computer code for calculating further comprises:

computer code for calculating said purchase probability by dividing the total number of item purchases by the number of purchase events; and

computer code for calculating said purchase frequency by determining the average period between sequential purchases of said item.

15. The computer program of claim 10, wherein the computer code for calculating further comprises:

computer code for populating a database with a plurality of purchase entries;

computer code for associating each purchase entry with at least one item of said plurality of items and with at least one customer identifier of a plurality of customer identifiers;

computer code for calculating a purchase frequency for each customer identifier; and

computer code for calculating a plurality of purchase probabilities for each item, wherein each purchase probability is associated with at least one customer identifier.

16. The computer program of claim 10, wherein the computer program further comprises computer code for inquiring in said electronic message if any item on said list is to be delivered.

17. The computer program of claim 16, wherein the computer code for inquiring further comprises computer code for inquiring in said electronic message if any other items are to be delivered.

18. The computer program of claim 10, wherein the computer program further comprises:

computer code for recognizing a mobile station of a customer associated with said customer identifier upon entering a store; and

computer code for transmitting a reminder list to said mobile station.

19. A system comprising:

a purchase database having at least one entry for at least one item purchase, wherein said entry is associated with a customer identifier;

a first engine for calculating a purchase probability and a purchase frequency for said item as a function of previous purchases associated with said customer identifier;

a marketing database that receives said entry, said customer identifier, said purchase probability, and said purchase frequency; and

a second engine that mines said marketing engine to;

generate at least one list as a function of said purchase probability and said purchase frequency;

transmit at least one electronic messages to a customer associated with said customer identifier; and

provide said list in said electronic message.

20. The system of claim 19, wherein said second engine inquires, through said electronic message, if any item on said list is to be prepared for pick up.

21. The system of claim 19, wherein said item is selected from the group consisting of a product group and a product.

22. The system of claim 19, wherein said second engine sequentially transmits a plurality of electronic messages to said customer associated with said customer identifier, wherein the period between each of said plurality of electronic messages for said customer is predetermined as a function of said purchase probability and said purchase frequency.

23. The system of claim 22, wherein said first engine:

calculates said purchase probability by dividing the total number of item purchases by the number of purchase events; and

calculates said purchase frequency by determining the average period between sequential purchases of said item.

24. The system of claim 19, wherein the system further comprises:

a third engine to;

populate said purchase database with a plurality of purchase entries; and

associate each purchase entry with at least one item of said plurality of items and with at least one customer identifier of a plurality of customer identifiers.

25. The system of claim 19, wherein said second engine inquires, through said electronic message, if any item on said list is to be delivered.

26. The method of claim 25, wherein said second engine inquires through said electronic message if any other items are to be delivered.

27. The system of claim 19, wherein the system further comprises:

a fourth engine to;

recognize a mobile station of a customer associated with said customer identifier upon entering a store; and

transmit a reminder list to said mobile station.