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Experiments let you compare two or more versions of a workflow path and see which one performs better for your business goal (e.g. reduce cancellations, increase renewals, recover failed payments). An experiment is a split step: it routes each customer into exactly one branch (Variant A, Variant B, …) based on your chosen traffic split. Experiment split example

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How to create an A/B test

In Admin Panel → Workflows:
  1. Create or open a workflow (start from a trigger).
  2. Add an Experiment (A/B test) step where you want the split to happen.
  3. Create 2+ variants (A/B/C…) and name them clearly (e.g. “Discount 10%”, “Offer pause”).
  4. Set a traffic split (typically 50/50 for A/B).
  5. Connect each variant branch to the actions/conditions you want that variant to run.
  6. Save and publish.

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Variants persistence

  • Within a single customer session / run: once a customer is assigned a variant, they stay in that variant while they move through the workflow (even if the run pauses and resumes later).
  • Across separate runs (e.g. the same customer enters the workflow on another day): variant assignment may not be guaranteed to stay the same.

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Reading results

In the Experiment panel you will see:
  • Enrollments: how many customers entered the experiment step per variant
  • Conversion rate (if shown for your workflow): success rate per variant

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Choosing a good traffic split

  • 50/50 is the default for A/B tests and gives the fastest learning.
  • Use 90/10 only when you’re rolling out a risky change and want a smaller exposure.
  • The editor will automatically adjust variant traffic so it sums to 100%.
Traffic split example

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When to use an experiment

Use experiments when you have a clear question like:
  • Does offering 10% off retain more subscribers than offering skip?
  • Is it better to show free product vs discount at step 1?
  • Does changing the copy or button labels increase acceptance?
Avoid experiments when:
  • You’re still unsure what problem you’re solving (start with a single workflow and iterate).
  • You can’t measure success (no clear outcome / metric).
  • You’re planning many changes at once (hard to interpret results).
Make sure each variant branch ends up doing something meaningfully different (offer, copy, timing, channel, etc.).