Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

Abstract: Methods, systems, and apparatus, including computer programs encoded on a computer storage medium, for providing conversion path performance measures and reports. In one aspect, user interaction data are obtained, were the user interaction data specify user interactions for a plurality of conversions. User interactions that are associated with each conversion are selected from the user interaction data, where the associated user interactions for each conversion are user interactions with a converting user during the conversion cycle for the conversion. Using the user interaction data for the selected user interactions, a quantity of user interactions that are associated with each conversion and occurred during the conversion cycle for the conversion are determined. In turn, conversion path performance measures are computed and reports specifying the conversion path performance measures are generated.

Abstract: A server system stores time series data for a data source. The time series data comprises a plurality of time-value pairs, each pair including a value associated with an attribute of the data source and a time. For a particular attribute, the server system generates a plurality of forecasting models for characterizing the time-value pairs, each model including an estimated attribute value and an associated error-variance. For a time-value pair, the server system determines a plurality of differences between the value of the time-value pair and respective estimated attribute values of the plurality of forecasting models and tags the time-value pair as an anomaly if the differences for at least a first subset of the forecasting models are greater than the corresponding error variances. In response to a request from a client application, the server system returns at least a subset of the time-value pairs tagged as anomalies.

Abstract: A server system stores web analytics data for a web page in a device. The web analytics data comprises a plurality of prior time-value pairs, each pair including a value of an attribute associated with the web page and a time associated with the value. For a particular attribute, the server system collects a new time-value pair including a new value associated with the web page and a new time indicating when the value was determined. The server system estimates a predicted value for the attribute and an associated error-variance at the new time by applying a forecasting model to the prior time-value pairs in respective subsets of the web analytics data. The collected new time-value pair is tagged if its value is outside the error variance of the predicted value for the particular attribute.

Abstract: A graphical user interface is used for presenting time series data and anomalies associated with a data source on a computer display. The graphical user interface has first and second windows. The first window includes a graph of time series data values for an attribute of the data source and a histogram of anomalies of the data source, each corresponding to a value of a respective attribute that is substantially different from an expected value of the attribute. The second window includes a list of automatic alerts characterizing a set of anomalies of the data source at a particular time. In response to a user adjustment of a sensitivity threshold, a new histogram of anomalies is rendered to replace the existing histogram of anomalies in the first window and a new list of automatic alerts is rendered to replace the existing list of automatic alerts in the second window.

Abstract: A system and method for presenting custom variables to a user of a web analytics system. An activity file of a web server is received, wherein the activity file includes activity file hit records that provide information about respective requests for documents made by visitors of web sites. A custom variable tag of an activity file hit record in the activity file is identified. Attribute-value pairs of the custom variable tag are then extracted. The attribute-value pairs of the custom variable tag are stored in a database hit record of a database of the server. One or more attribute-value pairs of a plurality of custom variable tags assigned to the custom variable of the web site are then prepared to be presented to a user, wherein the user is separate and distinct from the authors of the documents of the web site.