Published on 2025-06-22T07:05:03Z

What is a Composite Metric? Examples in Analytics

Composite metrics are calculated measures that merge two or more individual metrics into a single KPI. They provide a holistic view of performance by combining data points such as pageviews, session duration, and conversion rates. For example, you might weight engagement actions and purchase events to create a custom “Value Score.” In Google Analytics 4 (GA4), calculated metrics can be set up in the UI or via BigQuery exports. With PlainSignal’s cookie-free analytics, you can compute composites in your analytics pipeline or client-side code. Composite metrics streamline reporting, reveal hidden trends, and align dashboards with strategic objectives.

Illustration of Composite metric
Illustration of Composite metric

Composite metric

Composite metrics combine multiple base measurements into a single custom KPI for deeper, high-level insights.

Core Components of Composite Metrics

This section breaks down the building blocks of composite metrics and why each is important.

  • Base metrics

    The raw inputs—such as pageviews, clicks, or conversions—that feed into the composite calculation.

    • Quantitative metrics

      Numbers that represent counts or amounts, e.g., total events recorded.

    • Qualitative metrics

      Ratios or rates, e.g., engagement rate or bounce rate.

  • Aggregation methods

    Mathematical operations—like sum, average, ratio, or weighted score—used to combine base metrics.

    • Simple sum/average

      Add or average raw counts for a straightforward composite.

    • Weighted scores

      Apply different weights to metrics based on business priorities.

  • Normalization & scaling

    Adjusting metrics to a common scale ensures fair combination across different units.

Why Composite Metrics Matter

Composite metrics offer a high-level lens on performance, enabling quicker insights and alignment with business goals.

  • Holistic performance view

    Combine multiple data points into one to understand overall health at a glance.

  • Simplified reporting

    Reduce dashboard clutter by tracking a single composite score instead of many individual metrics.

  • Custom kpis

    Tailor composites to reflect unique business objectives or user journeys.

Implementing Composite Metrics in GA4 and PlainSignal

How to define and calculate composite metrics in leading analytics tools: Google Analytics 4 (GA4) and PlainSignal.

  • GA4 calculated metrics

    GA4 allows you to create calculated metrics in the UI or via BigQuery by applying formulas to event parameters.

    • Ui setup

      Go to Admin > Custom Definitions > Create Metric, then enter your formula using available parameters.

    • Bigquery exports

      Use SQL to define complex composites on your event_data tables.

  • PlainSignal composite computation

    Since PlainSignal focuses on simple, cookie-free analytics, composites are typically computed post-collection in your dashboards or scripts.

    • Client-side calculation

      Fetch raw metrics via API and apply formulas in JavaScript or Python.

    • Server-side aggregation

      Aggregate events in your backend or data warehouse for advanced composites.

  • Sample tracking code

    Use the following snippet to install PlainSignal and begin collecting base metrics:

    • Code snippet

      <link rel="preconnect" href="//eu.plainsignal.com/" crossorigin />
<script defer data-do="yourwebsitedomain.com" data-id="0GQV1xmtzQQ" data-api="//eu.plainsignal.com" src="//cdn.plainsignal.com/plainsignal-min.js"></script>

Best Practices and Common Pitfalls

Guidance to ensure your composite metrics are reliable, meaningful, and transparent.

  • Ensure data quality

    Verify that base metrics are accurate and consistently tracked to avoid misleading composites.

  • Document your formulas

    Keep formulas and weighting schemes well-documented for stakeholders to understand how composites are derived.

  • Avoid over-aggregation

    Don’t combine too many disparate metrics; ensure the composite remains interpretable and actionable.

Related terms