When configuring Unified Audiences within Optimizely Feature Experimentation, we currently lack immediate visibility into the estimated audience size before an experiment goes live.

Currently, this creates a workflow bottleneck for non-technical users. Experimenters are often forced to rely on technical team members to manually "rebuild" or cross-reference the same audience logic within the Profile tab or ODP just to obtain a preliminary size estimate. This dependency on technical support for simple validation prevents independent exploration and slows down the experimentation lifecycle.Without a real-time or pre-launch estimate of how many users qualify for a specific cohort, it is difficult to accurately calculate:

1. Minimum Detectable Effect (MDE)
2. Estimated Experiment Duration
3. Traffic Allocation Strategy

Our audiences are often highly segmented based on attributes and audiences from Segment. Launching a test "blind" to the audience volume can lead to experiments running significantly longer than expected or failing to reach statistical significance.

We would like to see a pre-launch audience size estimator directly within the FX Audience Builder for Unified Audiences. This should include the count of qualified users; a real-time count of unique identifiers that currently match the audience criteria.

Business Impact & Value

• Self-Service Empowerment: Enables non-technical users to iterate on and validate targeting conditions independently without needing technical teams to verify audience counts in separate systems.
• Operational Efficiency: Experimenters can refine targeting before engineering implementation or flag activation.
• Data Accuracy: Reduces the risk of "underpowered" experiments that waste traffic and time.
• Decision Speed: Faster identification of whether a test is viable based on volume, allowing us to pivot or broaden targeting early.