System and method for ranking items

• US 20020004735A1
• Filed: 01/18/2001
• Published: 01/10/2002
• Est. Priority Date: 01/18/2000
• Status: Abandoned Application

• Current Assignee: Oath Inc. (Verizon Communications Inc.)
• Original Assignee: Oath Inc. (Verizon Communications Inc.)
• Inventors: Gross, William
• Application Number:
  US09/765,270
• Publication Number:
  US 20020004735A1
• Time in Patent Office: Days
• US Class Current: 705/10
• CPC Class Codes: G06Q 30/0214 Referral reward systems
• CPC Class Codes: G06Q 30/0234 Rebates after completed purchase
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions
• CPC Class Codes: G06Q 30/0613 Third-party assisted
• CPC Class Codes: G06Q 30/0625 Directed, with specific intent or strategy

Abstract

A system and method for ranking items is disclosed. In one embodiment, the items constitute offerings offered by at least one on-line vendor. The system includes a ranking module that estimates the likelihood that a user will select the offerings and the likelihood that the user will purchase the items offered in the offerings. Based on this information, the ranking module calculates the expected revenue to be generated by the offerings. The ranking module then ranks the offerings relative to one another so as to increase income received by the system administrator.

Claims

1. A method of ranking offerings offered by at least one on-line vendor, comprising:

operating a ranking module affiliated with a first entity; and

ranking, with the ranking module, a first offering from an on-line vendor relative to a second offering from an on-line vendor so as to increase income received by the first entity.

2. The method of claim 1, further comprising:

calculating an estimated first selection revenue that corresponds to the revenue received by the first entity when a user selects the first offering; and

calculating an estimated second selection revenue that corresponds to the revenue received by the first entity when the user selects the second offering.

3. The method of claim 2, wherein calculating an estimated first selection revenue further comprises estimating a first selection likelihood that corresponds to the likelihood that the user will select the first offering.

4. The method of claim 3, wherein calculating an estimated second selection revenue further comprises estimating a second selection likelihood that corresponds to the likelihood that the user will select the second offering.

5. The method of claim 1, further comprising:

calculating an estimated first purchase commission that corresponds to the commission received by the first entity when a user purchases an item offered in the first offering; and

calculating an estimated second purchase commission that corresponds to the commission received by the first entity when a user purchases an item offered in the second offering.

6. The method of claim 5, wherein calculating an estimated first purchase commission further comprises estimating a first purchase likelihood that corresponds to the likelihood that the user will purchase the item offered in the first offering.

7. The method of claim 6, wherein calculating an estimated second purchase commission further comprises estimating a second purchase likelihood that corresponds to the likelihood that the user will purchase the item offered in the second offering.

8. A method of ranking offerings offered by at least one on-line vendor, comprising:

operating a ranking website affiliated with a first entity;

estimating, with the ranking website, a selection likelihood that corresponds to the likelihood that a user will select a first offering from an on-line vendor;

calculating, with the ranking website, an estimated selection revenue that corresponds to the revenue received by the first entity when the user selects the first offering; and

ranking, with the ranking website, the first offering relative to another offering so as to increase income received by the first entity.

9. The method of claim 8, further comprising:

estimating, with the ranking website, a second selection likelihood that corresponds to the likelihood that the user will select a second offering from an on-line vendor; and

calculating, with the ranking website, an estimated second selection revenue that corresponds to the revenue received by the first entity when the user selects the second offering.

10. A method of ranking offerings offered by at least one on-line vendor, comprising:

operating a ranking website affiliated with a first entity;

estimating, with the ranking website, a purchase likelihood that corresponds to the likelihood that a user will purchase an item offered in a first offering from an on-line vendor;

calculating, with the ranking website, an estimated purchase commission that corresponds to the commission received by the first entity when the user purchases the item offered in the first offering; and

ranking, with the ranking website, the first offering relative to another offering so as to increase income received by the first entity.

11. The method of claim 10, further comprising:

estimating, with the ranking website, a second purchase likelihood that corresponds to the likelihood that the user will purchase an item offered in a second offering from an on-line vendor; and

calculating, with the ranking website, an estimated second purchase commission that corresponds to the commission received by the first entity when the user purchases the item offered in the second offering.

12. A method of ranking hyperlinks to websites affiliated with at least one on-line vendor, comprising:

operating a ranking website affiliated with a first entity;

estimating, with the ranking website, a click likelihood that corresponds to the likelihood that a user will click on a first hyperlink to a website affiliated with an on-line vendor;

calculating, with the ranking website, an estimated click revenue that corresponds to the revenue received by the first entity when the user clicks on the first hyperlink;

estimating, with the ranking website, a purchase likelihood that corresponds to the likelihood that the user will purchase an item offered on the website associated with the first hyperlink;

calculating, with the ranking website, an estimated purchase commission that corresponds to the commission received by the first entity when the user purchases the item offered on the website associated with the first hyperlink; and

ranking, with the ranking website, the first hyperlink relative to another hyperlink so as to increase income received by the first entity.

13. The method of claim 12, further comprising:

estimating, with the ranking website, a second click likelihood that corresponds to the likelihood that the user will click on a second hyperlink to a website affiliated with an on-line vendor;

calculating, with the ranking website, an estimated second click revenue that corresponds to the revenue received by the first entity when the user clicks on the second hyperlink;

estimating with the ranking website, a second purchase likelihood that corresponds to the likelihood that the user will purchase an item offered on the website associated with the second hyperlink; and

calculating, with the ranking website, an estimated second purchase commission that corresponds to the commission received by the first entity when the user purchases the item offered on the website associated with the second hyperlink.

14. A method of operating a website that ranks referrals to at least one on-line vendor, comprising:

operating a ranking module affiliated with a first entity;

estimating a first click likelihood that corresponds to the likelihood that a user will click on a first referral to an on-line vendor;

calculating an estimated first click revenue that corresponds to the revenue received by the first entity when the user clicks on the first referral;

estimating a first purchase likelihood that corresponds to the likelihood that the user will purchase an item mentioned in the first referral;

calculating an estimated first purchase commission that corresponds to the commission received by the first entity when the user purchases the item mentioned in the first referral;

estimating a second click likelihood that corresponds to the likelihood that the user will click on a second referral to an on-line vendor;

calculating an estimated second click revenue that corresponds to the revenue received by the first entity when the user clicks on the second referral;

estimating a second purchase likelihood that corresponds to the likelihood that the user will purchase an item mentioned in the second referral;

calculating an estimated second purchase commission that corresponds to the commission received by the first entity when the user purchases the item mentioned in the second referral;

ranking with the ranking module the first referral relative to the second referral so as to increase income received by the first entity; and

displaying the first referral and the second referral on a website.

15. A system that ranks offerings offered by at least one on-line vendor, comprising:

a first offering from an on-line vendor;

a second offering from an on-line vendor; and

a ranking module stored in a computer readable storage medium, wherein the ranking module is affiliated with a first entity, and wherein the ranking module ranks the first offering relative to the second offering so as to increase income received by the first entity.

16. The system of claim 15, wherein:

the ranking module calculates an estimated first selection revenue that corresponds to the revenue received by the first entity when a user selects the first offering; and

the ranking module calculates an estimated second selection revenue that corresponds to the revenue received by the first entity when the user selects the second offering.

17. The system of claim 16, wherein:

the ranking module estimates a first selection likelihood that corresponds to the likelihood that the user will select the first offering; and

the ranking module estimates a second selection likelihood that corresponds to the likelihood that the user will select the second offering.

18. The system of claim 15, wherein:

the ranking module calculates an estimated first purchase commission that corresponds to the commission received by the first entity when a user purchases an item offered in the first offering; and

the ranking module calculates an estimated second purchase commission that corresponds to the commission received by the first entity when a user purchases an item offered in the second offering.

19. The system of claim 18, wherein:

the ranking module estimates a first purchase likelihood that corresponds to the likelihood that the user will purchase the item offered in the first offering; and

the ranking module estimates a second purchase likelihood that corresponds to the likelihood that the user will purchase the item offered in the second offering.

20. A system that ranks offerings offered by at least one on-line vendor, comprising:

a first offering from an on-line vendor;

a second offering from an on-line vendor; and

a ranking module stored in a computer readable storage medium, wherein the ranking module is affiliated with a first entity, and wherein the ranking module;

estimates a first selection likelihood that corresponds to the likelihood that a user will select the first offering, calculates an estimated first selection revenue that corresponds to the revenue received by the first entity when the user selects the first offering,

estimates a second selection likelihood that corresponds to the likelihood that the user will select the second offering,

calculates an estimated second selection revenue that corresponds to the revenue received by the first entity when the user selects the second offering, and

ranks the first offering relative to the second offering so as to increase income received by the first entity.

21. A system that ranks offerings offered by at least one on-line vendor, comprising:

a first offering from an on-line vendor;

a second offering from an on-line vendor; and

a ranking module stored in a computer readable storage medium, wherein the ranking module is affiliated with a first entity, and wherein the ranking module;

estimates a first purchase likelihood that corresponds to the likelihood that a user will purchase an item offered in the first offering,

calculates an estimated first purchase commission that corresponds to the commission received by the first entity when the user purchases the item offered in the first offering,

estimates a second purchase likelihood that corresponds to the likelihood that the user will purchase an item offered in the second offering,

calculates an estimated second purchase commission that corresponds to the commission received by the first entity when the user purchases the item offered in the second offering, and

ranks the first offering relative to the second offering so as to increase income received by the first entity.

22. A system that ranks offerings offered by at least one on-line vendor, comprising:

a first offering from an on-line vendor;

a second offering from an on-line vendor; and

a ranking module stored in a computer readable storage medium, wherein the ranking module is affiliated with a first entity, and wherein the ranking module;

estimates a first selection likelihood that corresponds to the likelihood that a user will select the first offering,

calculates an estimated first selection revenue that corresponds to the revenue received by the first entity when the user selects the first offering,

estimates a first purchase likelihood that corresponds to the likelihood that the user will purchase an item offered in the first offering,

calculates an estimated first purchase commission that corresponds to the commission received by the first entity when the user purchases the item offered in the first offering,

estimates a second selection likelihood that corresponds to the likelihood that the user will select the second offering,

calculates an estimated second selection revenue that corresponds to the revenue received by the first entity when the user selects the second offering,

estimates a second purchase likelihood that corresponds to the likelihood that the user will purchase an item offered in the second offering,

calculates an estimated second purchase commission that corresponds to the commission received by the first entity when the user purchases the item offered in the second offering, and

ranks the first offering relative to the second offering so as to increase income received by the first entity.