Abstract: Methods and system allow for creating rules for a tag management system. One or more implementations create rules for a tag management system can include crawling a page of a website. Additionally, one or more implementations identify the configuration of each of the tags implemented within the page. Further, one or implementations generate one or more rules that enable a tag management system to recreate the configuration of one or more tags implemented within the page. Further still, one or more implementations export the generated one or more rules to a tag management system.

Abstract: Methods and systems allow for using a master tag to monitor and control other tags on a webpage can include identifying a webpage. The method can also include identifying, with a master tag embedded in the webpage, one or more characteristics of at least one other tag embedded within the webpage. Further, the method can include sending a report to a data store that identifies the one or more characteristics of the at least one other tag.

Abstract: Two selected checkpoints define a group of paths represented in an analytics database. One or more events which appear between the two checkpoints on each of a plurality of the paths are identified as common bridge events. Path analysis information is then output, such as a bridge event analysis including a list of website visitor common bridge events that are ranked by their frequency of appearance, the frequencies calculated without regard to where each visitor event appears on a given path.

Abstract: Node sequence data, such as website visitation records, are filtered, analyzed, and summarized in reports. An administrator can designate particular target paths of interest in terms of a checkpoint node sequence. Node sequences are filtered based on the checkpoint node sequence, without regard to any additional or tangential nodes appearing in the sequences. In addition, node sequences can be specified in terms of specific nodes of interest along with wild cards. Reports depict the relative frequency of occurrence of node sequences using visual indicators such as line thickness and/or color.

Abstract: An automated website analysis system includes mechanisms for automatically auditing a website to validate that the scanned web page information conforms to validation rules. In one implementation, an auditing system requests web pages of an identified website pursuant to validating at least a portion of each requested web page. Embodiments include scanning page code of at least one of the web pages to identify scanned web page information, including a page tag. The scanned web page information is validated to determine whether is conforms to at least one validation rule by validating variables of the page tag against validation rules, including a vendor validation rule. Results of the validation are reported.

Abstract: A system for monitoring the “analytics health” or “tracking health” of a web page can include one or more modules that render analytics code on the web page. In one implementation, a monitoring service downloads one or more web pages from a web server. The monitoring service can attempt to render any analytics code on the web pages to see if the analytics code renders or executes as expected. The monitoring service can also perform basic text searches to identify analytics code, even if it cannot be rendered, and to determine if such code is present and correctly written in the web page. For web pages that require form input, the monitoring service can prompt the user for corresponding input, or retrieve pre-recorded user input from a store. The monitoring service can determine analytics health for web pages of interest in real-time.

Abstract: An automated website analysis system includes mechanisms for automatically auditing a website to validate that the scanned web page information conforms to validation rules. In one implementation, an auditing system requests web pages of an identified website pursuant to validating at least a portion of each requested web page. Embodiments include scanning page code of at least one of the web pages to identify scanned web page information, including a page tag. The scanned web page information is validated to determine whether is conforms to at least one validation rule by validating variables of the page tag against validation rules, including a vendor validation rule. Results of the validation are reported.

Abstract: A system for monitoring the “analytics health” or “tracking health” of a web page can include one or more modules that render analytics code on the web page. In one implementation, a monitoring service downloads one or more web pages from a web server. The monitoring service can attempt to render any analytics code on the web pages to see if the analytics code renders or executes as expected. The monitoring service can also perform basic text searches to identify analytics code, even if it cannot be rendered, and to determine if such code is present and correctly written in the web page. For web pages that require form input, the monitoring service can prompt the user for corresponding input, or retrieve pre-recorded user input from a store. The monitoring service can determine analytics health for web pages of interest in real-time.

Abstract: An automated website analysis system includes mechanisms for automatically reviewing a website and identifying various features of the website. In one implementation, the analysis system can rely at least in part on the actual downloading and rendering of each page in the website to determine not only aspects of website content and layout, but also whether various content, such as third party objects or source code, execute as intended. Additional features include recording user input that may be required to progress past web pages where automated site mapping would ordinarily stall. The analysis system can identify various items of interest about each web page to the website owner, including web page parent/child relationships, as well as the extent to which the given page content is consistent with its metadata descriptions.

Abstract: An automated website analysis system includes mechanisms for automatically reviewing a website and identifying various features of the website. In one implementation, the analysis system can rely at least in part on the actual downloading and rendering of each page in the website to determine not only aspects of website content and layout, but also whether various content, such as third party objects or source code, execute as intended. Additional features include recording user input that may be required to progress past web pages where automated site mapping would ordinarily stall. The analysis system can identify various items of interest about each web page to the website owner, including web page parent/child relationships, as well as the extent to which the given page content is consistent with its metadata descriptions.

Abstract: An automated website analysis system includes mechanisms for automatically auditing a website to validate that the scanned web page information conforms to validation rules. In one implementation, an auditing system requests web pages of an identified website pursuant to validating at least a portion of each requested web page. Embodiments include scanning page code of at least one of the web pages to identify scanned web page information, including a page tag. The scanned web page information is validated to determine whether is conforms to at least one validation rule by validating variables of the page tag against validation rules, including a vendor validation rule. Results of the validation are reported.

Abstract: An automated website analysis system includes mechanisms for automatically reviewing a website and identifying various features of the website. In one implementation, the analysis system can rely at least in part on the actual downloading and rendering of each page in the website to determine not only aspects of website content and layout, but also whether various content, such as third party objects or source code, execute as intended. Additional features include recording user input that may be required to progress past web pages where automated site mapping would ordinarily stall. The analysis system can identify various items of interest about each web page to the website owner, including web page parent/child relationships, as well as the extent to which the given page content is consistent with its metadata descriptions.

Abstract: An automated website analysis system includes mechanisms for automatically reviewing a website and identifying various features of the website. In one implementation, the analysis system can rely at least in part on the actual downloading and rendering of each page in the website to determine not only aspects of website content and layout, but also whether various content, such as third party objects or source code, execute as intended. Additional features include recording user input that may be required to progress past web pages where automated site mapping would ordinarily stall. The analysis system can identify various items of interest about each web page to the website owner, including web page parent/child relationships, as well as the extent to which the given page content is consistent with its metadata descriptions.

Abstract: A system for monitoring the “analytics health” or “tracking health” of a web page can include one or more modules that render analytics code on the web page. In one implementation, a monitoring service downloads one or more web pages from a web server. The monitoring service can attempt to render any analytics code on the web pages to see if the analytics code renders or executes as expected. The monitoring service can also perform basic text searches to identify analytics code, even if it cannot be rendered, and to determine if such code is present and correctly written in the web page. For web pages that require form input, the monitoring service can prompt the user for corresponding input, or retrieve pre-recorded user input from a store. The monitoring service can determine analytics health for web pages of interest in real-time.

Abstract: Node sequence data, such as website visitation records, are filtered, analyzed, and summarized in reports. An administrator can designate particular target paths of interest in terms of a checkpoint node sequence. Node sequences are filtered based on the checkpoint node sequence, without regard to any additional or tangential nodes appearing in the sequences. In addition, node sequences can be specified in terms of specific nodes of interest along with wild cards. Reports depict the relative frequency of occurrence of node sequences using visual indicators such as line thickness and/or color.

Abstract: Node sequence data, such as website visitation records, are filtered, analyzed, and summarized in reports. An administrator can designate particular target paths of interest in terms of a checkpoint node sequence. Node sequences are filtered based on the checkpoint node sequence, without regard to any additional or tangential nodes appearing in the sequences. In addition, node sequences can be specified in terms of specific nodes of interest along with wild cards. Reports depict the relative frequency of occurrence of node sequences using visual indicators such as line thickness and/or color.

Abstract: Node sequence data, such as website visitation records, are filtered, analyzed, and summarized in reports. An administrator can designate particular target paths of interest in terms of a checkpoint node sequence. Node sequences are filtered based on the checkpoint node sequence, without regard to any additional or tangential nodes appearing in the sequences. In addition, node sequences can be specified in terms of specific nodes of interest along with wild cards. Reports depict the relative frequency of occurrence of node sequences using visual indicators such as line thickness and/or color.