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Experiment Settings
Experiment Settings allow you to fine-tune how your experiment runs before it’s launched.
While creating a test only requires a few core steps, these settings give you additional control over when your experiment runs, how visitors are distributed between variations, who should be excluded from participating, and how your experiment is documented for future reference.
Most settings are optional, but taking a few extra minutes to configure them can help improve the quality and reliability of your results.
Scheduling (Automate Plan)
Scheduling allows you to automatically start and stop experiments without manual intervention.
This is especially useful for seasonal campaigns, product launches, marketing promotions, or experiments that need to begin or end at a specific time.
Current scheduling options include:
- Start Date & Time
- End Date & Time
- Automatically stop after reaching a selected confidence level (when enabled)
Scheduling is available with the Bluvia A/B Testing Automate Plan.
Best practices:
- Schedule experiments before major marketing campaigns begin.
- Allow enough time for your experiment to collect meaningful data.
- Avoid ending experiments too early unless statistical confidence has been reached.
Traffic Allocation
Traffic Allocation determines how visitors are distributed between the Control and each Variant.
By default, Bluvia A/B Testing distributes traffic evenly so each variation receives approximately the same number of visitors.
For example:
- Control ā 50%
- Variant 1 ā 50%
Or with three variations:
- Control ā 34%
- Variant 1 ā 33%
- Variant 2 ā 33%
Even traffic distribution provides the most reliable comparison and is recommended for most experiments.
If needed, you can manually adjust the percentage assigned to each variation to gradually introduce a new experience or reduce exposure while testing significant changes.
Best practices:
- Keep traffic evenly distributed whenever possible.
- Only use uneven traffic allocation when you have a specific testing strategy.
- Ensure all percentages total 100%.
Exclusion Rules
Exclusion Rules prevent specific visitors from participating in your experiment.
Excluding internal users and non-human traffic helps ensure your results accurately reflect the behavior of your intended audience.
Current exclusion options include:
Logged-in Users
Exclude visitors who are logged into your WordPress website.
Admin Traffic
Exclude WordPress administrators from participating in the experiment.
This option is recommended for most websites to prevent administrative activity from influencing your results.
IP Address or Range
Exclude individual IP addresses or IP ranges, such as office networks or development environments.
Geographic Regions
Exclude visitors from specific countries or regions.
Note: Geographic exclusions are currently under development and may not be available yet.
Note: Geographic exclusions are currently under development and may not be available yet.
Bots & Crawlers
Prevent search engines and automated bots from participating in your experiment.
Custom Query Parameters
Exclude visitors whose URLs contain specific query parameters.
This is useful for excluding preview links, internal testing URLs, or campaign-specific traffic.
Exclude Converted Users
Prevent visitors who have already completed your selected conversion goal from participating in the experiment.
This is useful when testing experiences intended only for visitors who have not yet converted.
Notes & Hypothesis
The Notes & Hypothesis section allows you to document the purpose of your experiment before it begins.
Although these notes don’t affect how the experiment runs, they provide valuable context when reviewing results or collaborating with your team.
A good hypothesis should answer three simple questions:
- What are you changing?
- Why are you making the change?
- What outcome do you expect?
For example:
Changing the homepage call-to-action button from “Learn More” to “Start Free Trial” is expected to increase button clicks because the new wording is more action-oriented.
Changing the homepage call-to-action button from “Learn More” to “Start Free Trial” is expected to increase button clicks because the new wording is more action-oriented.
Recording your reasoning before launching an experiment makes it easier to determine whether your hypothesis was correct once the results are available.
Best Practices
To improve the quality of your experiments:
- Configure scheduling before launching time-sensitive experiments.
- Keep traffic evenly distributed unless a different allocation supports your testing strategy.
- Exclude administrator and internal traffic whenever possible.
- Filter bots and crawlers to improve data accuracy.
- Write a clear hypothesis before launching every experiment.
- Keep experiment notes concise and focused on the purpose of the test.
Thoughtful configuration helps produce cleaner data, more reliable results, and better optimization decisions over time.
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Continue configuring your experiment:
