Dynamic control system for managing redirection of requests for content

• US 8,738,733 B1
• Filed: 09/25/2007
• Issued: 05/27/2014
• Est. Priority Date: 09/25/2007
• Status: Expired due to Fees

• Current Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Original Assignee: Amazon Technologies, Inc. (Amazon.com, Inc.)
• Inventors: Brauwerman, Michael R., Betz, Stephan G., Walters, Christopher Kenfield, Finkel, Avram
• Primary Examiner(s): LI, SUN M
• Application Number:
  US11/861,155
• Time in Patent Office: 2,436 Days
• Field of Search: 705/14, 705/14.49, 705/14.52, 705/14.53, 707 1- 10, 709/218, 709/224
• US Class Current: 709/218
• CPC Class Codes: G06F 16/24578 using ranking
• CPC Class Codes: G06F 16/951 Indexing; Web crawling techniques
• CPC Class Codes: G06F 16/9535 Search customisation based on user profiles and personalisation
• CPC Class Codes: G06F 16/958 Organisation or management of web site content, e.g. publishing, maintaining pages or automatic linking
• CPC Class Codes: G06F 16/972 Access to data in other repository systems, e.g. legacy data or dynamic Web page generation

Abstract

Requests for content are received, for example, an HTTP request for a web page is received. Each request has a landing context, which may include information about the user sending the request, the request itself, the referrer, or another subject. This information can be found in the requests or external to the requests. The information of the landing context is compared to appropriate triggering criteria. For requests that satisfy the appropriate triggering criteria, a destination is provided based on one or more weighted treatments. The request is directed to the provided destination. The results of the requests are subsequently analyzed and used to adjust the treatments in an automated fashion.

Claims

1. A computer implemented method for managing requests for content, comprising:

receiving multiple requests for a landing page of a web site at one or more processors;

determining by the one or more processors whether said requests include an experiment identification;

for requests having said experiment identification, automatically accessing multiple sets of triggering criteria associated with said experiment identification, each set of triggering criteria is associated with two or more landing pages that each have a weight, the weight associated with each landing page specifying a percentage chance that each particular landing page will be chosen as the landing page for a particular request, and said automatically accessing being performed by the one or more processors;

for requests having said experiment identification, automatically determining whether user landing contexts of said requests satisfy any of said sets of said triggering criteria, said automatically determining whether user landing contexts of said requests satisfy any of said sets of said triggering criteria is performed by the one or more processors;

for each request having user landing context that satisfies any of said sets of said triggering criteria, automatically identifying said set of triggering criteria satisfied by a respective landing context and choosing one landing page from the two or more landing pages associated with said set of triggering criteria satisfied by a respective landing context, said choosing is based on said weights for said landing pages, said automatically identifying and said choosing being performed by the one or more processors;

for each request having user landing context that satisfies one of said sets of said triggering criteria, automatically directing said request to said chosen landing page in response to said choosing, said automatically directing being performed by the one or more processors;

automatically analyzing results of said requests having user landing contexts that satisfy one of said sets of triggering criteria, said automatically analyzing being performed by the one or more processors; and

automatically adjusting said one or more weights based on said analyzing results, said automatically choosing is performed before and after said automatically adjusting said one or more weights, said automatically adjusting being performed by the one or more processors.

2. A method according to claim 1, wherein:

said user landing contexts include information in said requests and information that is not in said request; and

said requests are HTTP requests.

3. A method according to claim 1, further comprising:

accessing user identifications in a subset of said requests; and

using said user identifications to access a data structure external to said requests, user landing contexts include information that is in said data structure.

4. A computer implemented method for managing requests for content, comprising:

receiving a request for a web page by one or more processors;

automatically determining by the one or more processors that said request includes an identification of an experiment;

identifying by the one or more processors a set of criteria associated with said experiment from multiple sets of criteria;

automatically determining by the one or more processors whether user landing context associated with said request satisfies said set of criteria;

automatically choosing a page from two or more pages associated with said set of criteria based on a weight associated with each page of said two or more pages if said user landing context associated with said request satisfies said set of criteria, said weight associated with each page specifying a percentage chance that each particular page will be chosen as the page for a particular request, said automatically choosing a page is performed by the one or more processors;

automatically providing said chosen page in response to said choosing, said providing being performed by the one or more processors; and

automatically adjusting said weight based on results of at least a subset of said requests for content, said automatically choosing a page is performed before and after said automatically adjusting said rule, said automatically adjusting being performed by the one or more processors.

5. A method according to claim 4, wherein:

said automatically choosing said page includes choosing a destination for said request.

6. A method according to claim 4, wherein:

said automatically choosing a page includes randomly selecting a page based on said weights.

7. A method according to claim 4, wherein:

said user landing context includes information about a referring web site.

8. A method according to claim 4, further comprising:

accessing an indication of a user in said request; and

using said indication of said user to access a user data structure external to said request, said user landing context includes information that is in said user data structure.

10. The computing device of claim 7, further comprising:

access user identifications in a subset of the requests; and

use the user identifications to access a data structure external to the requests, the user landing contexts include information that is in the data structure.

9. A computing device, comprising:

at least one computing device processor;

a communication interface;

a storage device that includes triggering criteria and two or more treatments that indicate content to provide in response to an incoming request for content if at least a subset of the triggering criteria is satisfied by the incoming request, each treatment is associated with a weight; and

a memory device including instructions that, when executed by the at least one computing device processor, enable the computing device to;

receive multiple requests for a landing page of a web site;

determine whether the multiple requests include an experiment identification;

for requests having the experiment identification, automatically access multiple sets of triggering criteria associated with the experiment identification, each set of triggering criteria is associated with two or more landing pages that each have a weight, the weight associated with each landing page specifying a percentage chance that each particular landing page will be chosen as the landing page for a particular request;

for requests having the experiment identification, automatically determine whether user landing contexts of the requests satisfy any of the sets of the triggering criteria;

for each request having the user landing context that satisfies any of the sets of the triggering criteria, automatically identify the set of triggering criteria satisfied by a respective landing context and choosing one landing page from the two or more landing pages associated with the set of triggering criteria satisfied by a respective landing context;

for each request having the user landing context that satisfies one of the sets of the triggering criteria, automatically direct the request to the chosen landing page in response to the choosing;

automatically analyze results of the requests having the user landing contexts that satisfy one of the sets of triggering criteria; and

automatically adjust the one or more weights based on the analyzing results, the automatically choose performed before and after the automatically adjust the one or more weights.

11. The computing device of claim 9, wherein the user landing contexts include information in the requests and information that is not in the request and the requests are HTTP requests.

12. The computing device of claim 9, wherein the user landing context includes information about a referring web site.

13. The computing device of claim 9, wherein the instructions, when executed to choose one landing page, further cause the computing device to:

choose a destination for the request.

14. The computing device of claim 9, wherein the instructions, when executed to choose one landing page, further cause the computing device to:

randomly select a page based on the weights.

15. A non-transitory computer-readable storage medium storing instructions that, when executed by at least one computing device processor, cause a computing device to:

receive multiple requests for a landing page of a web site;

determine whether the multiple requests include an experiment identification;

for requests having the experiment identification, automatically access multiple sets of triggering criteria associated with the experiment, each set of triggering criteria being associated with two or more landing pages that each have a weight, the weight associated with each landing page specifying a percentage chance that each particular landing page will be chosen as the landing page for a particular request;

for requests having the experiment identification, automatically determine whether user landing contexts of the requests satisfy any of the sets of the triggering criteria;

for each request having the user landing context that satisfies any of the sets of the triggering criteria, automatically identify the set of triggering criteria satisfied by a respective landing context and choose one landing page from the two or more landing pages associated with the set of triggering criteria satisfied by a respective landing context, the choosing is based on the weights for the landing pages;

for each request having the user landing context that satisfies one of the sets of the triggering criteria, automatically direct the request to the chosen landing page in response to the choosing;

automatically analyze results of the requests having the user landing contexts that satisfy one of the sets of triggering criteria; and

automatically adjust the one or more weights based on the analyzing results, the automatically choosing is performed before and after the automatically adjusting the one or more weights.

16. The non-transitory computer-readable storage medium of claim 15/, wherein the instructions, when executed by at least one computing device processor, further cause the computing device to:

access user identifications in a subset of the requests; and

use the user identifications to access a data structure external to the requests, the user landing contexts include information that is in the data structure.

17. The non-transitory computer-readable storage medium of claim 15, wherein the user landing contexts include information in the requests and information that is not in the request, and wherein the requests are HTTP requests.

18. The non-transitory computer-readable storage medium of claim 15, wherein the user landing context includes information about a referring web site.

19. The non-transitory computer-readable storage medium of claim 15, wherein the instructions, when executed to choose one landing page further cause the computing device to:

choose a destination for the request.

20. The non-transitory computer-readable storage medium of claim 15, wherein the instructions, when executed to choose one landing page further cause the computing device to:

randomly select a page based on the weights.