# Analytics & Reporting

### Tracking A/B Test Segmentation

Tracking which group a user is assigned to (e.g. Control or Treatment) is important if you want to compare each cohort's performance. This is even more evident for long-term metrics such as LTV and user churn.

To determine which group a user was assigned to, can use the following code:

{% tabs %}
{% tab title="iOS" %}

```swift
let modelInfo = ContextManager.getCustomModel(for: "your_upsell_flow")
let isControl = modelInfo?.isControl ?? true
```

{% endtab %}

{% tab title="Android" %}
Not yet supported in Android. Reach out to our team to request this feature.
{% endtab %}

{% tab title="Flutter" %}
Not yet supported in Flutter. Reach out to our team to request this feature.
{% endtab %}

{% tab title="Unity" %}
Not yet supported in Unity. Reach out to our team to request this feature.
{% endtab %}

{% tab title="React Native" %}
Not yet supported in React Native. Reach out to our team to request this feature.
{% endtab %}
{% endtabs %}

When the model info is `nil`, it means the ML model hasn't been deployed yet (i.e. we're still in calibration phase). When present, a ML model has already been deployed, and we can access the `isControl` property.

### Tracking OTA Model Rollouts

To track which over-the-air model is currently active in the app, ContextDecision exposes a `ContextManager.currentAppliedCustomModelVersion` function. This returns a unique identifier that gets updated every time the app receives a new model version. You can track this in your own analytics to observe model rollouts.

During calibration phase, this function will always return `"calibration"`, and when opting for [custom SDK binaries](/context-decision/advanced/model-distribution-methods.md), it will return the SDK version.


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