Web page associated with a node in a website traffic pattern

• US 9,386,109 B1
• Filed: 08/23/2013
• Issued: 07/05/2016
• Est. Priority Date: 01/11/2012
• Status: Expired due to Fees

• Current Assignee: Google LLC (Alphabet Inc.)
• Original Assignee: Google Inc. (Alphabet Inc.)
• Inventors: Kent, James
• Primary Examiner(s): Dyer, Andrew
• Application Number:
  US13/974,904
• Time in Patent Office: 1,047 Days
• Field of Search: 715/205, 715/206, 705/7.11, 705/7.12, 705/7.22, 705/7.26, 705/7.27, 705/14.43, 705/14.45, 705/14.6, 709223-226, 717/124
• US Class Current: 1/1
• CPC Class Codes: H04L 67/02 based on web technology, e.g. hypertext transfer protocol [HTTP]
• CPC Class Codes: H04L 67/535 Tracking the activity of the user network monitoring arrangements H04L43/00; recording of computer activity G06F11/34

Abstract

A method of improving a traffic pattern through web page nodes of a website is provided, including selecting web page nodes. The traffic pattern includes a sequence of nodes. Each node represents a first page having a link to a second page in a subsequent node. A visitor to a node prior to a conversion node either navigates to a subsequent node or fails to progress to a subsequent node. The method also includes, for each web page, identifying display elements on the web page node that are associated with a decreased probability that the user progresses through the traffic pattern to a subsequent web page node in the predetermined traffic pattern, determining a metric representing an impact on a conversion attributable to the display elements, ranking the plurality of web page nodes based on the metrics for each web page node.

Claims

1. A method of improving a traffic pattern through a plurality of media application nodes, the method comprising:

receiving, at a processor, the traffic pattern, the traffic pattern including the plurality of media application nodes and a goal media application node, the traffic pattern including a predetermined sequence of media application nodes beginning with a first media application node of the plurality of media application nodes and ending with the goal media application node,

wherein each media application node of the plurality of media application nodes is associated with a user interface having a link to another user interface, wherein the another user interface is associated with another media application node of the plurality of media application nodes of the traffic pattern that is subsequent to the media application node associated with the user interface in the predetermined sequence of media application nodes;

for each media application node of the plurality of media application nodes;

receiving, at the processor, data indicative of a user interface associated with the each media application node,

identifying, using the processor, a display element of the user interface associated with the each media application node that is associated with a decreased probability that a user progresses from the user interface associated with the each media application node to a subsequent user interface associated with a subsequent media application node according to the predetermined sequence of the traffic pattern, and

determining, using the processor, a metric for the each media application node representing an impact on a conversion attributable to the display element, wherein the conversion is associated with the goal media application node;

ranking, using the processor, the plurality of media application nodes based on the determined metric for each media application node;

storing, in a non-transitory computer-readable medium, information about the ranking;

selecting a media application node of the plurality of media application nodes of the traffic pattern to improve; and

modifying a display element of a user interface associated with the selected media application node to increase a probability that the user will progress to the subsequent media application node of the traffic pattern.

2. The method according to claim 1, wherein identifying the display element is performed based on an expected change in a conversion rate of the traffic pattern associated with modifying the display element, wherein the expected change in the conversion rate represents a probability that the user will progress to the goal media application node of the traffic pattern.

3. The method according to claim 1, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is a ratio of a first number of links that navigate out of the traffic pattern to a second number of links that progress through the traffic pattern according to the predetermined sequence.

4. The method according to claim 1, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is representative of an amount of content of a user interface associated with the media application node that is relevant to the goal media application node of the traffic pattern.

5. The method according to claim 1, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is an expected dollar impact associated with increasing a probability that a user will progress to a subsequent media application node of the traffic pattern.

6. The method according to claim 1, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is based, at least in part, on empirically observed data relating to percentages of users of the traffic pattern who progress through the traffic pattern to a subsequent media application node of the traffic pattern.

7. The method according to claim 1, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is a percentage of space on a user interface associated with the media application node that is associated with content that is relevant to the goal media application node of the traffic pattern.

8. A non-transitory computer-readable medium, having machine instructions stored therein, the instructions being executable by one or more processors to cause the one or more processors to perform operations comprising:

receiving a traffic pattern, the traffic pattern including a plurality of media application nodes and a goal media application node, the traffic pattern including a predetermined sequence beginning with a first media application node of the plurality of media application nodes and ending with the goal media application node,

wherein each media application node of the plurality of media application nodes is associated with a user interface having a link to a second user interface, wherein the second user interface is associated with a media application node of the plurality of media application nodes of the traffic pattern that is subsequent to the media application node associated with the first user interface in the predetermined sequence;

for each media application node of the plurality of media application nodes;

receiving data indicative of a user interface associated with the each media application node,

determining a first number of display elements of the user interface that link to a subsequent user interface associated with a subsequent media application node according to the predetermined sequence of the traffic pattern,

determining a total number of display elements of the user interface that link to other user interfaces,

determining a ratio of the first number of display elements to the total number of display elements,

identifying a display element of the user interface associated with the each media application node that is associated with a decreased probability that a user progresses from the user interface associated with the each media application node to a subsequent user interface associated with a subsequent media application node according to the predetermined sequence of the traffic pattern;

determining a metric for the each media application node representing an impact on a conversion attributable to the display element and based, at least in part, on the determined ratio, wherein the conversion is associated with the goal media application node;

ranking the plurality of media application nodes based on the determined metric for each media application node;

storing information about the ranking;

selecting a media application node of the plurality of media application nodes of the traffic pattern to improve; and

modifying a display element of the user interface associated with the selected media application node to increase a probability that the user will progress to a subsequent media application node of the traffic pattern.

9. The non-transitory computer-readable medium according to claim 8, wherein identifying the display element is further performed based on an expected change in a conversion rate of the traffic pattern associated with modifying the display element, wherein the expected change in the conversion rate represents a probability that the user will progress to the goal media application node of the traffic pattern.

10. The non-transitory computer-readable medium according to claim 8, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined ratio.

11. The non-transitory computer-readable medium according to claim 8, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is representative of an amount of content on a user interface associated with the media application node that is relevant to the goal media application node of the traffic pattern.

12. The non-transitory computer-readable medium according to claim 8, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is an expected dollar impact associated with increasing a probability that the user will progress to a subsequent media application node of the traffic pattern.

13. The non-transitory computer-readable medium according to claim 8, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is based, at least in part, on empirically observed data relating to percentages of users of the traffic pattern who progress through the traffic pattern to a subsequent media application node of the traffic pattern.

14. The non-transitory computer-readable medium according to claim 8, wherein selecting a media application node of the plurality of media application nodes of the traffic pattern to improve is based on the determined metric, wherein the determined metric is a percentage of space on a user interface associated with the media application node that is associated with content that is relevant to the goal media application node of the traffic pattern.

15. A system for improving a traffic pattern through media application nodes, the system comprising:

a processor;

a memory; and

a communication interface, in communication with the memory and configured to transmit data between the memory and the processor, wherein the processor is configured to process instructions to;

receive the traffic pattern, the traffic pattern including a plurality of media application nodes and a goal media application node, the traffic pattern including a predetermined sequence beginning with a first media application node of the plurality of media application nodes and ending with the goal media application node,

wherein each media application node of the plurality of media application nodes is associated with a user interface having a link to a subsequent user interface, wherein the subsequent user interface is associated with a media application node of the plurality of media application nodes of the traffic pattern that is subsequent to the media application node associated with the user interface in the predetermined sequence,

for each media application node of the plurality of media application nodes;

receive data indicative of a user interface associated with the each media application node,

identify a display element of the user interface associated with the each media application node that is associated with a decreased probability that a user progresses from the user interface associated with the each media application node to a subsequent user interface associated with a subsequent media application node according to the predetermined sequence of the traffic pattern, and

determine a metric for the each media application node representing an impact on a conversion attributable to the display element, wherein the conversion is associated with the goal media application node,

rank the plurality of media application nodes based on the determined metric for each media application node,

select a media application node of the plurality of media application nodes of the traffic pattern to improve based on the ranking of the plurality of media application nodes, and

modify a display element of a user interface associated with the selected media application node to increase a probability that the user will progress to the subsequent media application node of the traffic pattern.

16. The system according to claim 15, wherein identifying the display element is performed based on an expected change in a conversion rate of the traffic pattern associated with modifying the display element, wherein the expected change in the conversion rate represents a probability that the user will progress to the goal media application node of the traffic pattern.

17. The system according to claim 15, wherein the determined metric is a ratio of a first number of links that navigate out of the traffic pattern to a second number of links that progress through the traffic pattern according to the predetermined sequence.

18. The system according to claim 15, wherein the determined metric is representative of an amount of content a user interface associated with the media application node is relevant to the goal media application node of the traffic pattern.

19. The system according to claim 15, wherein the determined metric is an expected dollar impact associated with increasing a probability that the user will progress to a subsequent media application node of the traffic pattern.

20. The system according to claim 15, wherein the determined metric is based, at least in part, on empirically observed data relating to percentages of users of the traffic pattern who progress through the traffic pattern to a subsequent media application node of the traffic pattern.

21. The system according to claim 15, wherein the determined metric a percentage of space on a user interface associated with the media application node that is associated with content that is relevant to the goal media application node of the traffic pattern.