Method and system for dynamic pricing

• US 7,330,839 B2
• Filed: 03/13/2001
• Issued: 02/12/2008
• Est. Priority Date: 03/13/2000
• Status: Expired due to Term

• Current Assignee: Intellions, Inc.
• Original Assignee: Intellions, Inc.
• Inventors: Srinivasan, Kannan, Shamos, Michael I.
• Primary Examiner(s): Hayes; John W.
• Assistant Examiner(s): NELSON, FREDA ANN
• Application Number:
  US09/804,729
• Publication Number:
  US 20010051932A1
• Time in Patent Office: 2,527 Days
• Field of Search: 705/1, 705/14, 705/10, 705 26- 27, 705/400
• US Class Current: 705/400
• CPC Class Codes: G06Q 30/0239 Online discounts or incentives
• CPC Class Codes: G06Q 30/0244 Optimization
• CPC Class Codes: G06Q 30/0273 Determination of fees for advertising
• CPC Class Codes: G06Q 30/0283 Price estimation or determination
• CPC Class Codes: G06Q 30/06 Buying, selling or leasing transactions

Abstract

The method and system of the present invention enables Internet businesses to conduct real-time, online experiments on a sample of transactions to determine marketplace sensitivities. Analysis of the results of the experiments reveal optimal values of key market decision variables such as price, content of banner ads, promotion levels, quantity discount schemes, etc. The experiments may be automatically conducted on an on-going basis, or may be conducted on a periodic basis. The method and system of the present invention preferably allow users to modify the nature of the experiment and the propagation of optimal values. The method and system of the current invention can be used for a pure diagnostic purpose or to automate the setting of key market variables. The dynamic experimentation used by the inventive system reveals the relative stability (or instability) of the networked market within which the business operates. The translation of an optimal value for a key variable (for example, price) to the entire market can be done on a real-time basis.

Claims

1. A computer-implemented method for dynamically determining an optimal price to be charged for a product on an Internet website operated by an Internet merchant, said method comprising the steps of:

(a) receiving configuration data from the Internet merchant, wherein such configuration data comprises a sample size of visitors to the Internet website who are to participate in experiments and time-related information concerning the experiments;

(b) randomly choosing visitors to the website to participate in the experiments according to the configuration data;

(c) running the experiments according to the configuration data on the randomly chosen visitors to create a model that reflects current market sensitivities concerning the product;

(d) determining the optimal price for the product using the model acquired in step (c) by electronic manipulation using a processor; and

(e) displaying the optimal price to the Internet merchant.

2. The method of claim 1, wherein said configuration data includes sampling parameters.

3. The method of claim 1, wherein said configuration data includes potential prices that are offered to the sampled population in step (c).

4. The method of claim 1, wherein said configuration data includes whether the sampling is to be performed continuously or at discrete intervals.

5. The method of claim 1, wherein said configuration data includes data for segmenting the population into clusters.

6. The method of claim 1, wherein said configuration data includes a minimum threshold for automatically propagating an optimal price.

7. The method of claim 1, wherein said random sampling is performed on the entire population of visitors to the website.

8. The method of claim 1, wherein visitors to the website are grouped, and each group is sampled separately.

9. The method of claim 1, wherein an optimal price is determined for each group.

10. The method of claim 9, additionally comprising updating the website such that a visitor is offered the optimal price determined in step (d)according to the visitor'"'"'s group.

11. The method of claim 9, wherein groups are determined based upon prior purchasing behavior.

12. The method of claim 9, wherein groups are determined based upon demographic characteristics.

13. The method of claim 1, wherein step (d) comprises determining a price that optimizes profit.

14. The method of claim 1, additionally comprising:

(f) automatically updating the website to use the optimal price determined in step (d).

15. The method of claim 1, additionally comprising:

(f) automatically updating the website to use the optimal price determined in step (d) if the optimal price meets a minimum threshold.

16. The method of claim 15, wherein the minimum threshold is that the optimal price determined in step (d) is a predetermined percentage better than a currently offered price for the product.

17. The method of claim 1, wherein step (d) comprises determining a price that optimizes revenue.

18. The method of claim 1, wherein step (d) comprises determining a price that optimizes market share.

19. The method of claim 1, wherein step (d) comprises determining a price that optimizes customer satisfaction.

20. The method of claim 1, wherein step (d) comprises determining a price that optimizes a resource selected from the group consisting essential of shipping resources and manufacturing resources.