Dashboard Template Builder for Website Performance Detection
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Solution Overview
Problem
Existing digital monitoring systems lack the ability to accurately and efficiently identify and alert website owners about performance issues, necessitating improved systems and methods for detecting and notifying problems in website performance.
Innovation Solution
A dashboard builder system that allows clients to select templates based on search criteria, populate dashboards with user session data, and generate metrics for visualizing website performance insights, including alerts when thresholds are exceeded.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If digital monitoring of user interactions is implemented to track website performance, then the ability to detect website issues is improved, but the complexity of the monitoring system increases
Solution Approach 1:
The monitoring system is segmented into modular template components, each handling specific aspects of website performance monitoring. Templates can be independently selected, configured, and combined based on specific monitoring needs, reducing overall system complexity while maintaining comprehensive detection capabilities.
Solution Approach 2:
The system automatically processes user session data and generates performance metrics without requiring manual configuration for each monitoring scenario. The automated data processing and metric generation reduce the operational complexity of the monitoring system while improving detection reliability.
2Measurement precision
If comprehensive user session data is collected and processed to generate detailed performance metrics, then the precision of website performance measurement is improved, but the processing time and computational resources increase
Solution Approach 1:
Templates are pre-configured with specific metric definitions and data processing logic before deployment. This preliminary preparation allows the system to quickly generate precise performance metrics by simply applying pre-defined templates to collected data, rather than configuring each metric from scratch during analysis.
Solution Approach 2:
The system efficiently processes comprehensive user session data by transforming it through standardized parameter definitions specified in templates. These parameter transformations enable precise metric generation while optimizing computational efficiency through consistent data processing routines.
Data Source
AI summary
Techniques are described herein for selecting a template for efficient generation of dashboards for the template that derive insights into website performance. A client can provide search criteria, and, in response, the client can view and select a template that matches the context in which the client would like insights into the website data. The client can interact with the selected template to populate dashboards for the selected template. An identification of a metric can be detected for a placeholder field for a dashboard, and a specification of event type(s) to be used in populating the metric can be obtained. The dashboard can be loaded in memory, and user session data can be processed to detect events in the user session data. Metrics can be generated in the dashboard using the events in the user session data. The metric in the dashboard can be displayed at the client device.