Calculated metrics let you combine metrics to create mathematical and statistical operations that are used as new metrics. These can be segmented and created for any report to which you add metrics.
Often, the truth in your data is hidden. What you see using standard metrics may not always be what you need to see. You need a way to flex your analytical creativity and to look at the data through the lens you choose.
Advanced calculated (or derived) metrics let you build, manage and curate your own metrics, so you can ask questions of your data without changing your Adobe Analytics implementation. This helps you to manage and dissect your data to shape a more informed customer experience.
Create metrics throughout Adobe Analytics, including in Analysis Workspace, Anomaly Detection and Contribution Analysis.
Create new metrics for specific characteristics. For example, create a metric for “new visitors” with a count of people who are visiting for the first time.
Build metrics based on currency, per cent or time. Use basic functions such as mean, multiply or divide or advanced functions like regression, t-score and others.
Learn how to create calculated metrics, segments and date ranges for comparison or breakdown directly within Analysis Workspace.
See how to build calculated metrics on the fly within Analysis Workspace.
Get to know how dimensions can be added to any formula to create internal segments quickly.
Visit the Adobe Experience Cloud Help page on Advanced Calculated Metrics for details on features, videos, FAQs and more.
With our Analysis Workspace feature, you get a robust, flexible canvas for building customised analysis projects. Drag and drop any number of data tables, visualisations and components (channels, dimensions, metrics, segments and time granularities) to a project.
Statistical modelling automatically finds unexpected trends in your data by analysing metrics and determining a lower bound, upper bound and expected range of values. When an unexpected spike or drop occurs, the system alerts you in the report.
Discovers hidden patterns within your data to explain statistical anomalies and identify correlations behind unexpected customer actions, out-of-bound values and sudden spikes or dips for metrics across audience segments.