Experiment Scorecard
Outline
What is an Experiment Scorecard?
The Experiment Scorecard bridges your experimentation data with the broader context of your business metrics. It integrates Optimizely Experimentation with your data warehouse to deliver high-confidence results in a secure, centralized environment.
Because Analytics is built on a warehouse-native architecture, you can take advantage of your existing data models and governance, ensuring analysis is both scalable and accurate.
Prerequisites
Before creating an Experiment Scorecard in Analytics, make sure the following setup steps are complete:
Your data sources are connected.
A decision dataset is created.
Your Optimizely account ID is added in the app settings
You’ve created an experiment in Optimizely.
Build an Experiment Scorecard
Experiment Scorecards make it easy to compare experiment variations against business metrics that already live in your warehouse. This enables teams to draw actionable insights from experimentation and drive decisions aligned with user behavior and company goals.
For instance, a team at a streaming service might use this to evaluate whether personalized content boosts viewer retention and subscription revenue.
Follow this walkthrough to build your own Experiment Scorecard: https://optimizely.navattic.com/vl5t0ftv.
Understand the Scorecard Interface
The Experiment Scorecard template includes the following modules:
Measure module – Select key outcomes to measure experiment performance.
Experiment module – Define which Optimizely experiment to analyze.
Metrics module – Link variations to business metrics.
Segmentation module – Filter by user segments to uncover deeper insights.
Filters module – Apply additional dataset filters.
Visualization module – Configure and preview the results.
Learn more about each module in the Scorecard UI here: Understand your Experiment Scorecard