Method and system for clickpath funnel analysis

Claim 2

A computer-implemented method for extracting at least one web usage analysis funnel from at least one input clickstream (CS) for analyzing user interactions with a web site, said computer-implemented method comprising: identifying an ordered path of web pages P 1 to P N as the web pages are successively viewed by a user, said identified ordered path constituting a CS; storing each ordered path within the CS in one of up to N tree structures, each of said tree structures having a root node P i corresponding to one of pages P 1 to p N and having successive child nodes corresponding to the successive pages after P i of P i+1 to P i+x , said X representing a specified depth criterion; and extracting a list of stored paths from each of the tree structures, each of the stored paths in the extracted list representing the web pages successively viewed by users from the root node P i to each end node P i+x as a function of the specified depth criterion.

Claim 3

The computer-implemented method of claim 1 , wherein storing comprises incrementing a counter associated with each node in each ordered path as the ordered path is stored, and further comprising analyzing each stored path in each tree structure using the counters to identify the stored paths that satisfy one or more input criteria.

Claim 4

The computer-implemented method of claim 2 , wherein the input criteria is selected from a group consisting of a width criterion for the child nodes, a starting page criterion, and an end page criterion, said width criterion representing a retention rate, said starting page criterion specifying a set of pages in CS from which P i is selected, and said end page criterion specifying a set of pages in CS that can serve as end nodes in each of the tree structures.

Claim 5

The computer-implemented method of claim 3 , wherein the retention rate is a function of a frequency relative to one of the following: the root node or the previous child node.

Claim 6

The computer-implemented method of claim 3 , wherein the retention rate is a function of an absolute frequency.

Claim 7

The computer-implemented method of claim 3 , wherein the width criterion specifies one or more of the following: a minimum width and a maximum width.

Claim 8

The computer-implemented method of claim 1 , wherein the depth criterion specifies a maximum depth.

Claim 9

The computer-implemented method of claim 1 , wherein the depth criterion represents a desired number of pages in each stored path.

Claim 10

The computer-implemented method of claim 1 , wherein P i corresponds to one of P 1 to P N specified as starting page criterion.

Claim 11

The computer-implemented method of claim 1 , wherein the stored path is a subpath.

Claim 12

The computer-implemented method of claim 1 , wherein storing comprises scanning the CS one time.

Claim 13

The computer-implemented method of claim 1 , further comprising automatically generating a report of the extracted list of stored paths.

Claim 14

The computer-implemented method of claim 1 , wherein one or more computer-readable media have computer-executable instructions for performing the computer-implemented method recited in claim 1 .

Claim 15

A computer-implemented method for analysis of web usage analysis funnels in at least one input clickstream (CS) for analyzing user interactions with a web site, said computer-implemented method comprising: identifying an ordered path of web pages as the web pages are successively viewed by a user, said identified ordered path constituting a CS; storing one or more paths within the CS satisfying a first input criterion in one or more tree structures; and analyzing each of the tree structures to identify any of the paths that satisfy a second input criterion, said second input criterion representing a width criterion.

Claim 16

A computer-implemented method for analysis of web usage analysis funnels in at least one input clickstream (CS) for analyzing user interactions with a web site, said computer-implemented method comprising: identifying an ordered path of web pages as the web pages are successively viewed by a user, said identified ordered path constituting a CS; storing one or more paths within the CS satisfying a first input criterion in one or more tree structures; and analyzing each of the tree structures to identify any of the paths that satisfy a second input criterion, said second input criterion representing a width criterion.

Claim 17

The computer-implemented method of claim 14 , wherein the first input criterion comprises one or more of the following: a depth criterion specifying a maximum number of pages in each stored path and a starting page criterion specifying a set of pages in the CS that can serve as a root node in one of the tree structures.

Claim 18

The computer-implemented method of claim 14 , wherein the stored path is a subpath.

Claim 19

The computer-implemented method of claim 14 , wherein storing comprises: creating a tree structure for each starting page of the one or more paths; and creating one or more branches in each of the tree structures for each path that starts with one of the starting pages.

Claim 20

The computer-implemented method of claim 14 , wherein one or more computer-readable media have computer-executable instructions for performing the computer-implemented method recited in claim 14 .

Claim 21

A computer-implemented method for extracting at least one web usage analysis funnel from one or more input clickstreams for analyzing user interactions with a web site, said computer-implemented method comprising: identifying an ordered path of web pages as the web pages are successively viewed by a user, said identified ordered path constituting one of the input clickstreams; creating a tree structure for storing the identified ordered path for each of the clickstreams, each tree structure having a root node corresponding to the first page of the clickstream and having a child node corresponding to each of the successive pages in the clickstream; for each input starting page, searching each tree structure to identify any stored path that starts at a node associated with the input starting page and satisfies an input depth requirement, said input depth requirement representing a desired number of pages in each path; storing each identified path in a temporary tree; and recursing through the temporary tree to identify any path that satisfies an input width requirement, said input width requirement representing a retention rate.

Claim 22

A computer-implemented method for extracting at least one web usage analysis funnel from one or more input clickstreams for analyzing user interactions with a web site, said computer-implemented method comprising: identifying an ordered path of web pages as the web pages are successively viewed by a user, said identified ordered path constituting one of the input clickstreams; creating a tree structure for storing the identified ordered path for each of the clickstreams, each tree structure having a root node corresponding to the first page of the clickstream and having a child node corresponding to each of the successive pages in the clickstream; for each input starting page, searching each tree structure to identify any stored path that starts at a node associated with the input starting page and satisfies an input depth requirement, said input depth requirement representing a desired number of pages in each path; storing each identified path in a temporary tree; and recursing through the temporary tree to identify any path that satisfies an input width requirement, said input width requirement representing a retention rate.

Claim 23

The computer-implemented method of claim 19 , wherein the identified path is a subpath.

Claim 24

The computer-implemented method of claim 19 , wherein the recursed path is a subpath.

Claim 25

The computer-implemented method of claim 19 , wherein storing comprises incrementing a counter associated with each node in each path as the path is stored.

Claim 26

The computer-implemented method of claim 19 , wherein one or more computer-readable media have computer-executable instructions for performing the computer-implemented method recited in claim 19 .

Claim 27

A computer-readable medium having computer-executable components for extracting at least one web usage analysis funnel from at least one input clickstream (CS) for analyzing user interactions with a web site, said components comprising: an identification component for identifying an ordered path of web pages P 1 to P N as the web pages are successively viewed by a user, said identified ordered path constituting a CS; a repository component for storing each ordered path within the CS in one or more tree structures up to N tree structures, each of said tree structures having a root node P i corresponding to one of pages P 1 to P N and having successive child nodes corresponding to the successive pages after P i of P i+1 to P i+x , said X representing a specified depth criterion; a support component for incrementing a counter associated with each node in each ordered path as the ordered path is stored; a funnel component for extracting a list of stored paths from each of the tree structures, each of the stored paths in the extracted list representing the web pages successively viewed by users from the root node P i to each end node P i+x as a function of the specified depth criterion; and a criteria component for analyzing each stored path in each of the tree structures using the counters to identify the stored paths that satisfy one or more input criteria.

Claim 28

A computer-readable medium having computer-executable components for extracting at least one web usage analysis funnel from at least one input clickstream (CS) for analyzing user interactions with a web site, said components comprising: an identification component for identifying an ordered path of web pages P 1 to P N as the web pages are successively viewed by a user, said identified ordered path constituting a CS; a repository component for storing each ordered path within the CS in one or more tree structures up to N tree structures, each of said tree structures having a root node P i corresponding to one of pages P 1 to P N and having successive child nodes corresponding to the successive pages after P i of P i+1 to P i+x , said X representing a specified depth criterion; a support component for incrementing a counter associated with each node in each ordered path as the ordered path is stored; a funnel component for extracting a list of stored paths from each of the tree structures, each of the stored paths in the extracted list representing the web pages successively viewed by users from the root node P i to each end node P i+x as a function of the specified depth criterion; and a criteria component for analyzing each stored path in each of the tree structures using the counters to identify the stored paths that satisfy one or more input criteria.

Claim 29

The computer-readable medium of claim 24 , wherein the input criteria is selected from a group consisting of a width criterion, a starting page criterion, and an end page criterion, said width criterion represents a retention rate, said starting page criterion specifies a set of pages in CS from which P i is selected, and said end page criterion specifies a set of pages in CS that can serve as end nodes in each of the tree structures.

Claim 30

A computer-readable medium having stored thereon a data structure for a particular node in a tree structure storing at least one click path from one or more input clickstreams representing an ordered path of successively viewed web pages P 1 to P N of a user for analyzing user interactions with a web site, said tree structure having a root node, each particular node associated with one of the viewed web pages, said data structure comprising: a first field including data identifying a page name for the viewed web page associated with the particular node; and a second field storing a support value representing a frequency of appearance for a particular path including the viewed web page identified in the first field, said particular path starting with the root node of the tree structure and including the particular node.

Claim 31

A computer-readable medium having stored thereon a data structure for a particular node in a tree structure storing at least one click path from one or more input clickstreams representing an ordered path of successively viewed web pages P 1 to P N of a user for analyzing user interactions with a web site, said tree structure having a root node, each particular node associated with one of the viewed web pages, said data structure comprising: a first field including data identifying a page name for the viewed web page associated with the particular node; and a second field storing a support value representing a frequency of appearance for a particular path including the viewed web page identified in the first field, said particular path starting with the root node of the tree structure and including the particular node.

Claim 32

The computer-readable medium of claim 26 , wherein the data structure is created for each distinct web page in the input clickstreams as the clickstream is scanned.

Claim 33

A computer-implemented method for extracting at least one web usage analysis funnel from at least one input clickstream (CS) for analyzing user interactions with a web site, said computer-implemented method comprising: identifying an ordered path of web pages P 1 to P N as the web pages are successively viewed by a user, said identified ordered path constituting a CS; reading through CS from P 1 to P x , wherein X is less than or equal to N and represents an input depth; creating a first tree with a root node associated with page P 1 , and with successive child nodes associated with pages P 2 to P x , wherein P x represents a child node with parent P x−i ; incrementing a counter associated with each node in the first tree as the node is created; creating a second tree with a root node associated with page P 2 , and with successive child nodes associated with pages P 3 to P x+i ; incrementing a counter associated with each node in the second tree as the node is created; creating additional trees rooted at each page P N−x+2 to P N for all subpaths in CS starting with pages P N−x+2 ; storing the subpaths that start at each page and ending at P N in the respective tree so that new trees are created only when the trees or nodes have not already been created; and running through all paths in each tree to extract and output only paths that satisfy input depth and input width criteria.

Claim 34

A computer-implemented method for extracting at least one web usage analysis funnel from at least one input clickstream (CS) for analyzing user interactions with a web site, said computer-implemented method comprising: identifying an ordered path of web pages P 1 to P N as the web pages are successively viewed by a user, said identified ordered path constituting a CS; reading through CS from P 1 to P x , wherein X is less than or equal to N and represents an input depth; creating a first tree with a root node associated with page P 1 , and with successive child nodes associated with pages P 2 to P x , wherein P x represents a child node with parent P x−i ; incrementing a counter associated with each node in the first tree as the node is created; creating a second tree with a root node associated with page P 2 , and with successive child nodes associated with pages P 3 to P x+i ; incrementing a counter associated with each node in the second tree as the node is created; creating additional trees rooted at each page P N−x+2 to P N for all subpaths in CS starting with pages P N−x+2 ; storing the subpaths that start at each page and ending at P N in the respective tree so that new trees are created only when the trees or nodes have not already been created; and running through all paths in each tree to extract and output only paths that satisfy input depth and input width criteria.

Claim 35

The computer-implemented method of claim 28 , further comprising processing another clickstream according to the computer-implemented method described in claim 28 .

Claim 36

The computer-implemented method of claim 28 , wherein the tree for a page P i is only created if P i is part of an input starting page criterion.

Claim 37

The computer-implemented method of claim 28 , wherein one or more computer readable media have computer-executable instructions for performing the computer-implemented method recited in claim 28 .