Optimizely records a decision event when a user is exposed to an experiment variation provided by Optimizely. Specifically, Optimizely logs a decision through the following sequence:
- An experiment is activated via the Activate, Is Feature Enabled or Decide methods.
- As a result, an SDK decision event is sent asynchronously to the Optimizely Event API. If the decision event indicates that the user is bucketed into an experiment, Optimizely logs the impression.
Decision events are used to generate the visitor counts shown on the Results page. They also serve as the denominator for measuring conversion rates and are used to determine your impression total.
Generally speaking, decision events are triggered automatically when you call Activate or Is Feature Enabled or Get Enabled Features for a user that Optimizely determines qualifies for a running experiment. No decision events are triggered for flag rollouts.
- When the user is bucketed into a feature test via the Is Feature Enabled or Get Enabled Features method, regardless of whether the feature is enabled or disabled in the feature test variation.
- When a user is bucketed into an A/B test via the Activate method.
- A new visitor lands on a page and is exposed to an experiment.
- A visitor refreshes a page and is exposed to the experiment again.
- A return visitor is exposed to the experiment again.
- Any time the Activate method returns
nullbecause the user didn't qualify for any experiment.
- If the user is only bucketed into a feature rollout (via the Is Feature Enabled or Get Enabled Features method) and there is no running feature test associated with the feature
- If neither a test nor rollout is running.
Depending on your application logic, your users may trigger rapid bursts of decision events. To ensure that your billing impression consumption is aligned to your end users' experience, Optimizely uses fixed-interval deduplication of decision events to calculate impression consumption. All decision events received within fixed 5-second intervals count as one impression for each user in an experiment. Optimizely buckets events into the fixed time windows based on when Optimizely received the event.
For more information on how impressions are triggered specifically, see What is an impression in Optimizely.
Starting September 2020, you have to option to choose a plan that is billed based on the number of unique monthly active users (MAU), rather than impression-based billing. MAU-based billing better enables you to run large-scale experiments at 100% traffic in order to reach statistical significance more quickly. For more information, see What are monthly active users.
Updated over 1 year ago