Abstract: Analytics system onboarding of web content is described. In one example, an analytics onboarding system is configured to process web content to generate recommendations, automatically and without user intervention. The recommendations are configured to assist in mapping of web content variables in web content to data elements supported by an analytics system to generate metrics that describe occurrence of events as part of user interaction with web content.

Abstract: Certain embodiments involve augmenting project data with searchable metadata for facilitating project queries. A method includes receiving metadata of the set of projects and identifying a filter within the metadata. The method also includes generating a first vector representing a first project of the set of projects and generating a second vector representing a second project of the set of projects. Further, the method includes grouping the first vector and the second vector into a project cluster based on the first vector and the second vector being within a threshold distance. The project cluster represents a set of filters associated with a subset of projects. Additionally, the method includes assigning a searchable tag to the project cluster based on the filter being a majority filter of the project cluster. The searchable tag includes metadata that facilitates locating the projects responsive to a query to the set of projects.

Abstract: Analytics system onboarding of web content is described. In one example, an analytics onboarding system is configured to process web content to generate recommendations, automatically and without user intervention. The recommendations are configured to assist in mapping of web content variables in web content to data elements supported by an analytics system to generate metrics that describe occurrence of events as part of user interaction with web content.

Abstract: Certain embodiments involve augmenting project data with searchable metadata for facilitating project queries. A method includes receiving metadata of the set of projects and identifying a filter within the metadata. The method also includes generating a first vector representing a first project of the set of projects and generating a second vector representing a second project of the set of projects. Further, the method includes grouping the first vector and the second vector into a project cluster based on the first vector and the second vector being within a threshold distance. The project cluster represents a set of filters associated with a subset of projects. Additionally, the method includes assigning a searchable tag to the project cluster based on the filter being a majority filter of the project cluster. The searchable tag includes metadata that facilitates locating the projects responsive to a query to the set of projects.