# 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.

<figure><img src="/files/sR5hJwrODg0K916F8Dwz" alt=""><figcaption></figcaption></figure>

***

## 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**.<br>

<figure><img src="/files/tmTBdjnwFil7kGCNPlWE" alt=""><figcaption></figcaption></figure>

* Jimo automatically creates:
  * The **Original** (your current tour flow).
  * A new **Variant A** (duplicate of the Original).

<figure><img src="/files/BwjxOvynXLRVrdnr6hrJ" alt=""><figcaption></figcaption></figure>

* At this stage, the test is **unpublished**.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.

<figure><img src="/files/h87xISdyKune3D1IcvmX" alt=""><figcaption></figcaption></figure>

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).

<figure><img src="/files/J4D5RxkMSXCuv8uw7rq1" alt=""><figcaption></figcaption></figure>

### 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.

<figure><img src="/files/mqcZxCrHsCAZnPUu2YOz" alt=""><figcaption></figcaption></figure>

{% 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.

![](/files/qKjGWxTEPp1HXyrWLc23)
{% 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.

<figure><img src="/files/CyUx8czp2ySU5IsCfTvH" alt=""><figcaption></figcaption></figure>

* 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.

<figure><img src="/files/7lF06Roof4M8NsnSpnOM" alt=""><figcaption></figcaption></figure>

* 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.

<figure><img src="/files/1uyCQloeUuFZXeSDWNie" alt=""><figcaption></figcaption></figure>

#### Variant filter in Statistics

* Filter the **Experience statistics** by variant: Original / A / B.
* Compare **step drop-off, clicks, completions** across versions.

<figure><img src="/files/FUZJkw7QYIiAiBART6A3" alt=""><figcaption></figcaption></figure>

### 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" %}

<figure><img src="/files/h7XDzaJzC7zk5EoO8MNd" alt=""><figcaption></figcaption></figure>
{% endtab %}

{% tab title="After Publish" %}

<figure><img src="/files/luqjlh2UJJK7WP6vvq6L" alt=""><figcaption></figcaption></figure>
{% endtab %}

{% tab title="Test Ended" %}

<figure><img src="/files/JIfZSLl8WJE58HACTVa6" alt=""><figcaption></figcaption></figure>
{% endtab %}
{% endtabs %}

### Choosing a winner

* When confident, click **Set as Default** on the best performer.

<figure><img src="/files/3y39OeZ16aooWTDDUOBi" alt=""><figcaption></figcaption></figure>

* 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.

<figure><img src="/files/qxjZJW96q4HIs0hiUrSn" alt=""><figcaption></figcaption></figure>

#### 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]: ![](/files/lQwLSur9YObhJu8fyQRs)


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