Predicting Individual Customer Returns in e-Commerce

• US 20160321683A1
• Filed: 04/30/2015
• Published: 11/03/2016
• Est. Priority Date: 04/30/2015
• Status: Active Application

• Current Assignee: International Business Machines Corporation
• Original Assignee: International Business Machines Corporation
• Inventors: Ji, Hao, Ren, Chang R., Zheng, Xiaobo, Chen, Xuan, He, Miao, Shao, Bing, Tian, Qi M.
• Application Number:
  US14/700,512
• Publication Number:
  US 20160321683A1
• Time in Patent Office: Days
• US Class Current: 1/1
• CPC Class Codes: G06Q 30/0202 Market predictions or forecasting for commercial activities
• CPC Class Codes: G06Q 30/0208 Trade or exchange of goods or services in exchange for incentives or rewards

Abstract

A mechanism is provided for predicting and reducing product return. For a historical regular product purchase associated with a current product purchase by a customer, a distribution of a number of product purchases and a distribution of a number of product returns is generated. A determination is made of a probability of return of the current product as a function of the number of product purchases, the number of product returns, a distance, and a browsing time. Responsive to the identified probability of return being greater than a predetermined threshold, the identified probability of return is used to reduce the probability of return of the product through one or more interactions with the product.

Claims

1-9. -9. (canceled)

10. A computer program product comprising a computer readable storage medium having a computer readable program stored therein, wherein the computer readable program, when executed on a computing device, causes the computing device to:

for a historical regular product purchase associated with a current product purchase by a customer;

generate a distribution of a number of product purchases g₁ (D, T), wherein D represents a deviation or distance of the purchased product from a customer'"'"'s preference for the current product and wherein T represents a time the customer spent browsing a website for the current product; and

generate distribution of a number of product returns, g₂ (D, T);

determine a probability of return (Prob(return)) of the current product as a function of the number of product purchases (g₁), the number of product returns (g₂), the distance D, and the browsing time T, Prob(return)=f(g₁, g₂, D, T); and

responsive to the identified probability of return being greater than a predetermined threshold, use the identified probability of return to reduce the probability of return of the product through one or more interactions with the product.

11. The computer program product of claim 10, wherein the computer readable program further causes the computing device to:

present the identified probability of return to a user.

12. The computer program product of claim 10, wherein the current product is identified as a product for which the identified probability of return is to be determined based on a filtering process that filters out products purchased by the customer that are non-regular product purchases.

13. The computer program product of claim 10, wherein a non-regular product purchase is at least one of a product purchase for another person as identified by utilization of a shipping address other than an address recorded for the customer or a purchase of a product that is the same as the current product within a predetermined time frame.

14. The computer program product of claim 10, wherein the computer readable program to reduce the probability of return of the product further causes the computing device to:

responsive to the probability of return being over the predetermined threshold, reduce future orders of the current product.

15. The computer program product of claim 10, wherein the computer readable program to reduce the probability of return of the product further causes the computing device to:

responsive to the probability of return being over the predetermined threshold, instantiate a product improvement resulting in a better product with a lower probability of return.

16. The computer program product of claim 10, wherein the computer readable program to reduce the probability of return of the product further causes the computing device to:

responsive to the probability of return being over the predetermined threshold, present a preemptive notice to the customer causing the customer to review the product one last time before finalization of purchase of the current product.

17. The computer program product of claim 10, wherein the computer readable program to reduce the probability of return of the product further causes the computing device to:

responsive to the probability of return being over the predetermined threshold, instantiate an improvement to a product description page associated with the product in order to reduce purchasing mistakes.

18. The computer program product of claim 10, wherein the computer readable program to reduce the probability of return of the product further causes the computing device to:

responsive to the probability of return being over the predetermined threshold, send out reward coupons to incentivize the customer to keep the current product.

19. An apparatus comprising:

a processor; and

a memory coupled to the processor, wherein the memory comprises instructions which, when executed by the processor, cause the processor to;

for a historical regular product purchase associated with a current product purchase by a customer;

generate a distribution of a number of product purchases g₁ (D, T), wherein D represents a deviation or distance of the purchased product from a customer'"'"'s preference for the current product and wherein T represents a time the customer spent browsing a website for the current product; and

generate distribution of a number of product returns, g₂ (D, T);

determine a probability of return (Prob(return)) of the current product as a function of the number of product purchases (g₁), the number of product returns (g₂), the distance D, and the browsing time T, Prob(return)=f(g₁, g₂, D, T); and

responsive to the identified probability of return being greater than a predetermined threshold, use the identified probability of return to reduce the probability of return of the product through one or more interactions with the product.

20. The apparatus of claim 19, wherein the instructions further cause the processor to:

present the identified probability of return to a user.

21. The apparatus of claim 19, wherein the current product is identified as a product for which the identified probability of return is to be determined based on a filtering process that filters out products purchased by the customer that are non-regular product purchases.

22. The apparatus of claim 19, wherein a non-regular product purchase is at least one of a product purchase for another person as identified by utilization of a shipping address other than an address recorded for the customer or a purchase of a product that is the same as the current product within a predetermined time frame.

23. The apparatus of claim 19, wherein the instructions to reduce the probability of return of the product further causes the processor to:

responsive to the probability of return being over the predetermined threshold, reduce future orders of the current product.

24. The apparatus of claim 19, wherein the instructions to reduce the probability of return of the product further causes the processor to:

responsive to the probability of return being over the predetermined threshold, instantiate a product improvement resulting in a better product with a lower probability of return.

25. The apparatus of claim 19, wherein the instructions to reduce the probability of return of the product further causes the processor to:

responsive to the probability of return being over the predetermined threshold, present a preemptive notice to the customer causing the customer to review the product one last time before finalization of purchase of the current product.

26. The apparatus of claim 19, wherein the instructions to reduce the probability of return of the product further causes the processor to:

responsive to the probability of return being over the predetermined threshold, instantiate an improvement to a product description page associated with the product in order to reduce purchasing mistakes.

27. The apparatus of claim 19, wherein the instructions to reduce the probability of return of the product further causes the processor to:

responsive to the probability of return being over the predetermined threshold, send out reward coupons to incentivize the customer to keep the current product.