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Deleting Tests

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Updated
ByEmily Gomez
Tests you no longer need can be moved to Trash from the Test Library in Bluvia A/B Testing.
Before removing an experiment, consider whether you may want to reference its setup or results in the future. If you want to keep the experiment for historical reference, consider archiving it instead.

Moving a Test to Trash

To remove an individual test:
  1. Navigate to Bluvia A/B Testing ā†’ Test Library.
  2. Find the experiment you want to remove.
  3. Open the experiment’s available actions.
  4. Select the option to move or delete the test.
  5. Confirm the action if prompted.
The experiment will be moved to the Trash section of your Test Library.
You can also access available management actions from the individual test progress page.

Removing Multiple Tests

You can move multiple experiments to Trash at the same time using Bulk Actions.
To remove multiple tests:
  1. Navigate to Bluvia A/B Testing ā†’ Test Library.
  2. Select the checkbox beside each experiment you want to remove.
  3. Open the Bulk actions menu.
  4. Select Move to Trash.
  5. Select Apply.
The selected experiments will be moved to Trash.

Viewing Tests in Trash

Tests moved to Trash can be found using the Trash filter at the top of the Test Library.
This keeps removed experiments separate from the tests you’re actively managing.
Before permanently removing an experiment, make sure you no longer need its configuration, results, or history.

Deleting vs. Archiving

Deleting and archiving serve different purposes.
Archive a test when you’re finished actively working with it but want to preserve the experiment and its history.
Move a test to Trash when you no longer need the experiment in your Test Library.
When you’re unsure whether an experiment will be useful later, archive it instead.

Before Removing an Experiment

Previous experiments can provide useful context when planning future tests.
Before removing one, consider whether you may need to:
  • Review its previous results.
  • Reference its hypothesis.
  • Compare it with a future experiment.
  • Duplicate its setup later.
  • Understand what your team has already tested.
Keeping useful experiment history can prevent repeated work and provide valuable context as your optimization program grows.

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