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3 results found

  1. Default Experiment Metric Auto‑Apply

    Feature: Default Experiment Metric Auto‑Apply

    Automatically apply a predefined default metric to every new experiment created in Optimizely, ensuring that all tests are consistently configured with a core measurement from the outset.

    Today, metrics must be manually added during experiment setup, which introduces variability and increases the risk of inconsistent or incomplete measurement across teams. This feature removes that dependency by embedding a standard metric directly into the experiment creation flow.

    1. Improves experiment quality and consistency
      By ensuring every experiment starts with a core metric, teams align on how success is measured. This directly addresses known challenges around inconsistent metric…

    1 vote

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  2. Support multiple User IDs

    Currently, Optimizely (FX) only supports one User ID.

    However, a user might use different IDs, depending eg. on log-in status or similar. The same way, experiments might require randomization and sending events on any of those IDs.

    This will be a key feature for us going forward.

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  3. Date as an Attribute Type

    For our experiments, we have a custom attribute that represents when a user signed up to our platform. Currently, we encode the values we receive for this as 8 digit numbers (YYYYMMDD) because Feature Experimentation audiences do not allow for attributes to be Date values. It would be a nicer experience for our users to be able to use a Date type rather than a Number type for attributes when creating audiences.

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