Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for determining zone identification reliability. The program and method provide for receiving plural page samples of a webpage or page group, each page sample of the plural page samples corresponding to a respective pageview of the webpage or page group; determining, for each page sample of the plural page samples, zone identification information for the page sample, the zone identification information indicating targets and zones identified by the targets for the page sample; detecting any identification errors with respect to the zone identification information for the plural page samples; and determining, based on the detecting, a reliability of the zone identification information.

Abstract: Systems and techniques may be used for generating an alert for a website based on user interactions at the website using a machine learning trained model. A technique may include receiving user interaction metrics corresponding to the user interactions, determining, using the machine learning trained model, whether a trajectory of a metric of the user interaction metrics is predicted to traverse a threshold, and in response to determining that the trajectory is predicted to traverse the threshold at a particular time, generating the alert. The technique may include evaluating a set of subsegments of the metric, each subsegment of the set of subsegments corresponding to respective metric source attributes, determining, based on the evaluation, at least one subsegment of the set of subsegments that most contributed to the trajectory, and outputting an indication for display, the indication including identification of the at least one subsegment with the alert.

Abstract: A system and method for identifying and correcting webpage zone target misidentification are provided. The method includes clustering a plurality of webpage nodes based on at least zoning information derived from a webpage to identify at least two similar webpage node clusters, wherein the clustered webpage nodes are included in the zoning information, and wherein at least two webpage node clusters indicates at least a zone target misidentification; generating at least a zone identification issue fix suggestion for each identified zone target misidentification, wherein a zone identification issue fix suggestion is a suggestion providing a correction for a respective zone target misidentification; and applying each of the generated zone target misidentifications on a respective zone target misidentification.

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for determining zone identification reliability. The program and method provide for receiving plural page samples of a webpage or page group, each page sample of the plural page samples corresponding to a respective pageview of the webpage or page group; determining, for each page sample of the plural page samples, zone identification information for the page sample, the zone identification information indicating targets and zones identified by the targets for the page sample; detecting any identification errors with respect to the zone identification information for the plural page samples; and determining, based on the detecting, a reliability of the zone identification information.

Abstract: Systems and techniques may be used website error detection. An example technique may include identifying an error corresponding to a website, retrieving a first set of user sessions where the error occurred and a second set of user sessions where the error did not occur, and determining, for an access category, whether members of a set of values of the access category are correlated to the error, using the first set of user sessions and the second set of user sessions. The example technique may include comparing a characteristic of at least one member of the set of values that was determined to be correlated to the error to a threshold. The example technique may include displaying an indication of the error and an indication of the at least one member of the set of values.

Abstract: Systems and techniques may be used for providing website change detection. An example technique may include processing snapshots of a website, for example on a first day and a second day to produce a set of features of the website. The technique may include comparing at least one of the set of features from the first day to at least one of the set of features from the second day, for example using a distance function. A change score may be determined, the change score corresponding to at least one of a deleted feature, an added feature, or an unchanged feature of the website from the first day to the second day. The technique may include outputting the change score (e.g., for display).

Abstract: Aspects of the present disclosure involve a system comprising a computer-readable storage medium storing a program and method for determining zone types of a webpage. The program and method provide for generating, for at least one node a first webpage, a vector including HTML content corresponding to the at least one node; providing the vector as input to a machine learning model configured to output a predicted node type based on the vector, the machine learning model having been trained with plural vectors including HTML content corresponding to plural nodes of second webpages; and determining, based on the output of the machine learning model, the predicted node type of the vector, to classify the at least one node.

Abstract: A system and method for detecting webpage zones of interest. A method includes receiving at least one webpage analysis request, wherein the received at least one webpage analysis request includes at least one webpage in a website; identifying, in the at least one webpage, at least one zone, wherein the at least one zone is a content element of a webpage; classifying the at least one zone into a category of interest, wherein the classification is based on a trained machine learning model configured to classify DOM elements of the least one webpage, and wherein a category of interest is a category determined based on a functionality of the website; and storing the classification by indicating the category of interest for each zone.

Abstract: A system and method for detecting webpage zones of interest. A method includes receiving at least one webpage analysis request, wherein the received at least one webpage analysis request includes at least one webpage in a website; identifying, in the at least one webpage, at least one zone, wherein the at least one zone is a content element of a webpage; classifying the at least one zone into a category of interest, wherein the classification is based on a trained machine learning model configured to classify DOM elements of the least one webpage, and wherein a category of interest is a category determined based on a functionality of the website; and storing the classification by indicating the category of interest for each zone.

Abstract: A system and method for detecting webpage zones of interest. A method includes receiving at least one webpage analysis request, wherein the received at least one webpage analysis request includes at least one webpage in a website; identifying, in the at least one webpage, at least one zone, wherein the at least one zone is a content element of a webpage; classifying the at least one zone into a category of interest, wherein the classification is based on a trained machine learning model configured to classify DOM elements of the least one webpage, and wherein a category of interest is a category determined based on a functionality of the website; and storing the classification by indicating the category of interest for each zone.

Abstract: A system and method for identifying and correcting webpage zone target misidentification are provided. The method includes clustering a plurality of webpage nodes based on at least zoning information derived from a webpage to identify at least two similar webpage node clusters, wherein the clustered webpage nodes are included in the zoning information, and wherein at least two webpage node clusters indicates at least a zone target misidentification; generating at least a zone identification issue fix suggestion for each identified zone target misidentification, wherein a zone identification issue fix suggestion is a suggestion providing a correction for a respective zone target misidentification; and applying each of the generated zone target misidentifications on a respective zone target misidentification.

Abstract: A system and method for detecting webpage zones of interest. A method includes receiving at least one webpage analysis request, wherein the received at least one webpage analysis request includes at least one webpage in a website; identifying, in the at least one webpage, at least one zone, wherein the at least one zone is a content element of a webpage; classifying the at least one zone into a category of interest, wherein the classification is based on a trained machine learning model configured to classify DOM elements of the least one webpage, and wherein a category of interest is a category determined based on a functionality of the website; and storing the classification by indicating the category of interest for each zone.