Method for contact stream optimization

• US 20030110119A1
• Filed: 12/11/2001
• Published: 06/12/2003
• Est. Priority Date: 12/11/2001
• Status: Active Grant

• Current Assignee: Maplebear Inc.
• Original Assignee: International Business Machines Corporation
• Inventors: Crites, Robert
• Granted Patent: US 10,706,428 B2
• Time in Patent Office: Days
• US Class Current: 705/37
• CPC Class Codes: G06Q 30/02 Marketing; Price estimation or determination; Fundraising
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0247 Calculate past, present or future revenues
• CPC Class Codes: G06Q 30/0249 based upon budgets or funds
• CPC Class Codes: G06Q 40/04 Trading; Exchange, e.g. stocks, commodities, derivatives or currency exchange

Abstract

Techniques for determining a prioritized listing of offers for use to contact potential customers are described. The technique includes generating an ordered listing of offers from a set of offers, by which to contact a potential customer from a group of potential customers by considering the potential customer independently from others of the potential customers in the group, during generating of the ordered listing of offers for the potential customer.

Claims

1. A method of determining a prioritized listing of offers for use to contact potential customers, the method comprises:

generating an ordered listing of offers from a set of offers, by which to contact a potential customer from a group of potential customers by considering the potential customer independently from others of the potential customers in the group, during generating of the ordered listing of offers for the potential customer.

2. The method of claim 1 wherein generating further comprises:

eliminating from the list offers that are mutually exclusive.

3. The method of claim 1 wherein the ordered list is prioritized based on highest expected profit.

4. The method of claim 1 wherein generating operates on the set of offers for all members of the group of potential customers, by considering each potential customer independently from others of the potential customers in the group.

5. The method of claim 1 wherein if the number of offers exceeds the number of offers allocated for customer, the method further comprises:

producing an alternative list having the best n offers.

6. The method of claim 1 wherein generating the ordered listing is performed independently for each potential customer in the group of potential customers to produce a list for each potential customer.

7. A method of determining a prioritized number of contacts to customers from a group of customers, the method comprises:

determining an ordered set of offers to be sent to each customer, and for each customer,

eliminating any offers that are not applicable to the customer based on eligibility rules for the offers or offers for which an expected profit for the customer is below a threshold amount; and

ordering remaining offers by expected profit.

8. The method of claim 7 further comprising:

producing a proposed solution having the best n offers where n is the lesser of the total remaining offers and the maximum number of offers allowed for the customer.

9. The method of claim 8 wherein the proposed solution is represented as a bit string of a length that is equal to the total of the viable offers.

10. The method of claim 9 wherein the proposed solution is checked against rules of the form (M,S) meaning at most M offers from set S can be sent to a customer.

11. The method of claim 10 wherein if an (M,S) rule is violated, a list of new alternative proposed solutions is generated by:

determining the number of bits T>

M from a set S that indicate offers should be sent in the proposed solution;

generating new alternative proposed solutions that all contain new alternative offers, represented in a bit string by setting T−

M number of bits that are not a part of set S, and which immediately follow a last one R1 of the “

1”

bits in the proposed solution.

12. The method of claim 11 further comprising:

generating alternative proposed solutions based on all combinations of the T “

1”

bits up to R1 and any “

0”

bits in set S between R1 and R2 containing M bits set to “

1”

.

13. The method of claim 12 wherein the new alternative proposed solutions are each merged with any preceding list of proposed solutions.

14. The method of claim 13 wherein the list of proposed solutions is checked in decreasing order of profitability.

15. The method of claim 13 further comprising:

accommodating a budget by sorting all offers chosen for all customers by return on investment and truncating the bottom of the list.

16. The method of claim 13 further comprising:

flagging customers who are truncated for each offer; and

rerunning flagged customers after removing exhausted offers and offers that the flagged customers were already approved for, while lowering their max number of allowed offers.

17. The method of claim 13 wherein truncating occurs at a boundary defined by a constraint on the method.

18. The method of claim 13 wherein truncating is selectable by the user.

19. The method of claim 18 wherein truncating occurs based on individual variance of profit from each customer with customers having low variance being truncated for certain offers before customers having high variance.

20. A computer program product residing on a computer readable medium for determining a prioritized number of offers to contact customers from a group of customers, comprises instructions to cause a computer to:

determine an ordered set of offers to be sent to each customer, and for each customer,

eliminate any offers that are not applicable to the customer based on eligibility rules for the offers or offers for which an expected profit for the customer is below a threshold amount; and

order remaining offers by expected profit.

21. The computer program product of claim 20 further comprising instructions to:

produce a proposed solution having the best n offers where n is the lesser of the total remaining offers and the maximum number of offers allowed for the customer.

22. The computer program product of claim 20 wherein the proposed solution is represented as a bit string of a length that is equal to the total number of the viable offers.

23. The computer program product of claim 20 further comprising instructions to:

check a proposed solution against rules of the form (M,S) meaning at most M offers from set S can be sent to a customer.

24. The computer program product claim 23 wherein if an (M,S) rule is violated,

the computer program product further comprises instructions to:

generate a list of new alternative proposed solutions by instructions that;

determine the number of bits T>

M from a set S that indicate offers should be sent in the proposed solution;

generate new alternative proposed solutions that all contain new alternative offers, represented in a bit string by setting T−

M number of bits that are not a part of set S, and which immediately follow a last one R1 of the “

1”

bits in the proposed solution.

25. The computer program product of claim 24 further comprising instructions to:

generate alternative proposed solutions based on all combinations of the T “

1”

bits up to R1 and any “

0”

bits in set S between R1 and R2 containing M bits set to “

1”

.

26. The computer program product of claim 25 wherein the new alternative proposed solutions are merged with any preceding list of proposed solutions.

27. The computer program product of claim 20 further comprising instructions to:

accommodate a budget by sorting all offers chosen for all customers by return on investment and truncating the bottom of the list.

28. A system for determining a prioritized number of offers to send to customers from a group of customers, the system comprises:

a computer; and

a computer readable medium storing a computer program product for determining the prioritized number of offers, comprises instructions to cause the computer to;

determine an ordered set of offers to be sent to each customer, and for each customer,

eliminate any offers that are not applicable to the customer based on eligibility rules for the offers or offers for which an expected profit for the customer is below a threshold amount; and

order remaining offers by expected profit.

29. The system of claim 28 wherein the proposed solution is represented as a bit string of a length that is equal to the total number of the viable offers.

30. The system of claim 28 wherein the proposed solution is checked against rules of the form (M,S) meaning at most M offers from set S can be sent to a customer.