> For the complete documentation index, see [llms.txt](https://help.usejimo.com/docs/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://help.usejimo.com/docs/analyze/a-b-test.md).
# A/B Test
## Setup experience variations
Improving user onboarding and walkthroughs requires testing different approaches. With Jimo, you can create **experience variations** and let results decide which one works best.
* Try alternative **flows, wording, or visuals**.
* Compare performance against your **success goal** (tour completion or tracked event).
* Deploy the **winning version** to all users with confidence.
This experimentation process helps ensure your tours continuously improve and better support your users.
### A/B Test
The current way to create variations in Jimo is through **A/B testing**.
* You can create **A/B versions of your tours** *(only Tours are supported for now)*.
* Max **3 variants**: Original + Variant A + Variant B.
* One **test per tour** at a time.
* Your **audience is split** across variants according to the distribution you choose (e.g. 50/50).
* As the test runs, Jimo tracks performance for each variant based on your defined goal.
* Once you gather enough data, you can **review results** and declare a winner, making that variant the **default tour** for all future and remaining users.
***
## Start a test
Begin from your tour’s [**Target & Publish → Goal**](/docs/publish/mesure-outcomes-goal.md#a-b-testing-tours-only) section.
* Click **Start A/B Test**.
* Jimo automatically creates:
* The **Original** (your current tour flow).
* A new **Variant A** (duplicate of the Original).
* At this stage, the test is **unpublished**.
* You may **Cancel Test** before publishing (this deletes all variants and resets back to Original only).
***
## Configure variants
Once your test is created, you’ll see the **Variants panel** where all versions of your tour are listed.\
This is where you **manage each variant** — preview and edit their flows, add or remove alternatives, adjust how traffic is split between them, and finally publish your setup.
Think of this step as shaping the actual experiment: defining what’s being tested and how users are distributed.
### Variants list
* Each variant is shown in the list with:
* **Preview** (open a read-only flow modal).
* **Edit** ([open the builder](/docs/build/builders.md#top-bar) on that variant).
* **Delete** (only on Variant A/B; the Original cannot be removed).
### Adding new variants
* Click **Add variant** to create another version.
* Choose to duplicate the **Original** or an existing **Variant**.
* You can test up to **3 versions** in total.
{% hint style="info" %}
#### Builder quick switch
* Inside the builder, use the **top-bar Variant switch** to move between versions.
* Changes made in one variant do **not** affect the others.
{% endhint %}
### Audience distribution
**How it works:** the distribution is applied on top of the **“Who” targeting rules** defined for the tour.
* Jimo will **randomly dispatch all eligible users** (those matching your “Who” field) into the selected proportions.
* By default, if set to 50/50, the full eligible user list is split evenly between the variants.
* No variant may exceed **90%**.
* Each must have at least **10%**.
Use the **slider** to decide how much traffic each version receives.
* The UI shows approximate user counts for each allocation.
### Publishing
* Click **Publish** to make the test live.
* All active variants are then served to users based on your distribution.
* You can **add variants later** to an already live test, but must re-publish.
* If you **Cancel Test** after publishing, you’ll need to publish again to return to a single-variant tour.
***
## Review results
Once live, head to your tour’s [**Analytics → Insights**](/docs/analyze/analytics.md#a-b-test-tours-only) to see performance.
#### Variant filter in Statistics
* Filter the **Experience statistics** by variant: Original / A / B.
* Compare **step drop-off, clicks, completions** across versions.
### A/B Test panel
Dedicated panel for experiment results:
* **Status & Confidence**: gauge shows “Too Early” or rising % confidence.
* **Variant table** with:
* Started
* Goal Reached
* Conversion Rate
* Preview[^1] (Click on a variant.)
* **Set as Default** button
{% tabs %}
{% tab title="Before Publish" %}
{% endtab %}
{% tab title="After Publish" %}
{% endtab %}
{% tab title="Test Ended" %}
{% endtab %}
{% endtabs %}
### Choosing a winner
* When confident, click **Set as Default** on the best performer.
* That variant becomes the **only version** shown to all users.
* Ending a test is **irreversible** – other variants are retired.
* Test data is **archived** in history for later reference.
#### Starting a new test
* Open **Goal → Start A/B Test** again.
* The current tour (default) becomes the new **control**.
* Add a challenger and repeat.
* Only **one test at a time** is allowed per tour.
***
## Best practices & tips
Keep your experiments reliable and easy to interpret:
{% stepper %}
{% step %}
**One change at a time**
Focus your test on a single variable (like copy, step order, or design). This way you know exactly what caused the difference in performance.
{% endstep %}
{% step %}
**Split fairly**
A 50/50 traffic split is usually the best starting point for faster, unbiased results. Use uneven splits (e.g. 80/20) only if you want to limit risk from a bold experiment.
{% endstep %}
{% step %}
**Don’t peek too soon**
Early numbers can be misleading. Wait until enough users have seen each variant and the confidence level is high before picking a winner.
{% endstep %}
{% step %}
**Use the winner as the new baseline**
Once a variant proves better, set it as default and treat it as the new control. From there, you can continue testing new improvements.
{% endstep %}
{% step %}
**Communicate with your team**
Let colleagues know when a test is running, since users may see different versions. This avoids confusion and ensures everyone understands the experiment in progress.
{% endstep %}
{% endstepper %}
[^1]: 