DETERMINING TARGETED INCENTIVES BASED ON CONSUMER TRANSACTION HISTORY

• US 20100280880A1
• Filed: 05/04/2010
• Published: 11/04/2010
• Est. Priority Date: 05/04/2009
• Status: Active Grant

• Current Assignee: Visa International Service Association (Visa, Inc.)
• Original Assignee: Visa International Service Association (Visa, Inc.)
• Inventors: Faith, Patrick, Siegel, Kevin P.
• Granted Patent: US 9,727,868 B2
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 10/04 Forecasting or optimisation specially adapted for administrative or management purposes, e.g. linear programming or "cutting stock problem" market predictions or forecasting for commercial activities G06Q30/0202
• CPC Class Codes: G06Q 10/06375 Prediction of business process outcome or impact based on a proposed change
• CPC Class Codes: G06Q 20/40 Authorisation, e.g. identification of payer or payee, verification of customer or shop credentials; Review and approval of payers, e.g. check credit lines or negative lists
• CPC Class Codes: G06Q 20/4016 involving fraud or risk level assessment in transaction processing
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0204 Market segmentation
• CPC Class Codes: G06Q 30/0205 Location or geographical consideration
• 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 40/00 Finance; Insurance; Tax strategies; Processing of corporate or income taxes
• CPC Class Codes: G06Q 40/12 Accounting

Abstract

Systems, apparatus, and methods for determining incentives based on consumer history. When, how, and to whom incentives are sent can be determined. For example, an incentive can be sent to a consumer to encourage a transaction at a time when the particular consumer is predisposed to initiate the transaction. Also, an incentive for a transaction can be sent to a consumer when that transaction has a high likelihood of leading to other transactions. An incentive can also be sent after a consumer initiates a transaction that is known to not have many subsequent transaction correlated to it.

Claims

1. A method of providing an incentive to a consumer, the method comprising:

receiving data corresponding to previous transactions;

a computer system determining one or more patterns of the previous transactions;

based on the determined patterns of the previous transactions, determining a likelihood for the future transaction at a plurality of times;

based on the likelihoods at the plurality of times, predicting a time window when the consumer is likely to initiate a future transaction; and

sending an incentive associated with the future transaction to the consumer such that the consumer receives the incentive at a time correlated with the predicted time window.

2. The method of claim 1, wherein determining one or more patterns of the previous transactions includes:

associating one or more keys with each previous transaction;

correlating pairs of previous transactions, each correlated pair associated with a particular pair of keys; and

for each correlated pair, determining time intervals between the transactions of the correlated pair; and

for each key pair;

tracking numbers of occurrences of correlated pairs having time intervals within specified time ranges, the transactions of the correlated pairs being associated with corresponding keys of the key pair.

3. The method of claim 1, further comprising:

specifying specific values for categories associated with the future transaction, wherein the time window is when the consumer is likely to initiate a future transaction having the specified values.

4. The method of claim 1, wherein the time window is not of a predetermined duration.

5. The method of claim 1, wherein the previous transactions are associated with the consumer and/or with one or more other consumers similar to the consumer.

6. The method of claim 5, wherein the time window when the consumer is likely to initiate the future transaction is based on a likelihood of the one or more other consumers initiating the future transaction.

7. The method of claim 1, wherein predicting the time window includes identifying a time when the likelihood is above a first threshold.

8. The method of claim 7, wherein the computer system determining a pattern of the previous transactions includes tracking a plurality of likelihood values of the future transaction, each likelihood value corresponding to a different frequency for the occurrence of the future transaction.

9. The method of claim 7, wherein the start of the time window is at a predetermined time relative to the identified time when the likelihood is above the first threshold.

10. The method of claim 7, wherein predicting the time window further includes identifying a time when the likelihood is below a second threshold and above the first threshold.

11. The method of claim 1, further comprising:

predicting a merchant at which the future transaction is to occur, wherein the incentive is for a first product that is available at the merchant, wherein the first product is a different product than a product predicted for the future transaction.

12. The method of claim 1, wherein the consumer receives the incentive during the predicted time window.

13. The method of claim 1, wherein the incentive is sent at a predetermined time before the predicted time period.

14. The method of claim 1, wherein the incentive is valid only during the predicted time window.

15. The method of claim 1, further comprising:

after predicting a time window when the consumer is likely to initiate a future transaction, determining a cost associated with the future transaction and/or a plurality of incentives;

determining an incentive to send based on an analysis of a likelihood of the future transaction and the cost.

16. The method of claim 1, wherein sending the incentive for the transaction to the consumer includes sending an electronic message to the consumer, wherein the electronic message is selected from the group consisting of an SMS message, an MMS message, and an e-mail.

17. The method of claim 1, further comprising:

determining a peak time of the plurality of times where the likelihood is a maximum, wherein the time window is correlated to the peak time.

18. The method of claim 17, wherein the time window is centered around the peak time.

19. A computer program product comprising a tangible computer readable medium storing a plurality of instructions for controlling one or more processors to perform the method of claim 1.

20. A computer system comprising:

one or more processors; and

the computer program product of claim 19.

21. A method of providing an incentive to a consumer, the method comprising:

a computer system determining a likelihood of any transaction occurring after a first type of transaction initiated by the consumer; and

sending, to the consumer, an incentive for a future transaction of the first type based on the likelihood being greater than a threshold.

22. The method of claim 21, wherein a transaction of the first type is for a specific merchant.

23. The method of claim 21, further comprising:

receiving data corresponding to transactions associated with the consumer;

correlating a first group of transactions to respective transactions of the first type, wherein a correlated transaction of the first group occurs after a respective transaction of the first type, wherein determining the likelihood uses a number of the correlated transactions of the first group.

24. The method of claim 23, further comprising:

tracking time intervals between the correlated transactions and the transactions of the first type, wherein determining the likelihood includes;

determining a number of correlated transactions having time intervals within a specified range, and wherein the incentive is sent when the number of correlated transactions having time intervals within a specified range is above a threshold.

25. The method of claim 23, further comprising;

increasing a value when a correlated transaction occurs after a transaction of the first type, the value stored associated with an identifier of the first type of transaction.

26. The method of claim 25, further comprising:

decreasing the value when a decline of a correlated transaction occurs after a transaction of the first type.

27. The method of claim 25, further comprising:

decreasing the value when a correlated transaction does not occur after a transaction of the first type during each of one or more time periods.

28. The method of claim 25, wherein the value is an imaginary part of a complex number, wherein the real part determines a likelihood of a transaction of the first type occurring.

29. The method of claim 28, wherein the value is associated with a particular time of a transaction of the first type occurring, and wherein the incentive is sent at a time correlated with the particular time.

30. The method of claim 29, wherein the correlated transactions are correlated specifically to a transaction of the first type occurring at the particular time.

31. A method of providing an incentive to a consumer, the method comprising:

a computer system determining an amount of transactions that are correlated to a first transaction type and that occur after the first transaction type; and

after a transaction of the first transaction type occurs, sending an incentive for any transaction based on the amount being below a threshold.

32. The method of claim 31, wherein the incentive is for a merchant near the merchant for the transaction of the first type.

33. The method of claim 31, wherein the incentive is for a future transaction that is likely to occur after a transaction of the first transaction type by a group of consumers that are similar to the consumer.

34. The method of claim 33, further comprising:

determining a time window relative to a transaction of the first transaction type in which the future transaction is likely for the group of consumers, wherein the incentive is sent at a time that is correlated to the time window relative to the occurrence of the transaction of the first transaction type by the consumer.