> ## Documentation Index
> Fetch the complete documentation index at: https://docs.fleack.io/llms.txt
> Use this file to discover all available pages before exploring further.

# Results: Reading Bayesian Test Outcomes in Fleack

> Understand how Fleack measures conversion, retention, and revenue metrics, interprets win probability, and tells you when to promote a winner.

Once a test is running and exposures are accumulating, Fleack's results engine computes per-variant statistics and gives you a clear signal: keep running, promote the winner, or stop. Rather than requiring you to calculate p-values or set up your own analytics pipeline, Fleack surfaces a single **win probability** number for each variant — the probability that this variant genuinely outperforms the control. This page explains how that number is computed and what to do with it.

## Metric types

You choose one metric per test when you create it. Fleack supports three types:

### Conversion

**Question:** Did the user call a specific endpoint within a set time window after being exposed to the variant?

You pick the conversion endpoint (e.g. `POST /api/purchase`) and a time window in hours. Fleack counts how many exposed users triggered that endpoint within the window. The win probability is computed using a **Bayesian Beta model** (Jeffreys prior `Beta(0.5, 0.5)`) with Monte Carlo sampling — giving you an interpretable probability rather than a reject/fail p-value.

Only users with a non-null user identity are included in the denominator.

### Retention (day-N)

**Question:** Did the user have any activity on day N after their exposure?

You specify the day number (e.g. day 3, day 7). Fleack checks whether each exposed user generated any event on that calendar day. An eligibility cutoff applies: users who were exposed less than N days ago haven't had the chance to be retained yet, so they're excluded from the calculation until they're measurable.

The same Bayesian win probability model applies as for conversion.

### Revenue / scalar

**Question:** What is the average change in a profile attribute (e.g. `arpu`) between exposure and now?

You pick a scalar profile attribute and an observation window in days. Fleack computes the average delta for each variant relative to the control. This is a **continuous metric** — Fleack reports uplift percentage rather than a binary win probability.

An eligibility cutoff also applies here: users exposed more recently than the observation window are excluded.

## Verdict thresholds

Fleack applies the following thresholds to give each variant a verdict:

| Verdict             | Condition                                                             |
| ------------------- | --------------------------------------------------------------------- |
| **Winner**          | Variant win probability ≥ 90% (binary) or uplift ≥ 5% (scalar)        |
| **Control wins**    | Control win probability ≥ 90% — the variant is performing worse       |
| **No difference**   | Neither side has reached a threshold yet — keep running               |
| **Not enough data** | Fewer than 30 total exposures — the engine declines to give a verdict |

The "not enough data" guard prevents you from acting on noise in the earliest hours of a test. Once you cross 30 exposures, verdicts start appearing.

## Reading the results panel

On the test detail page you'll see a per-variant breakdown:

* **Exposures** — unique users assigned to this variant
* **Conversions / retention / uplift** — the raw metric value
* **Win probability** — for binary metrics, the probability this variant beats the control
* **Verdict** — Winner, Control wins, No difference, or Not enough data

For scalar metrics, win probability is replaced by an **uplift percentage** (e.g. "+8.3% arpu vs control").

## When to promote

Click **Promote** when a variant reaches Winner status — or any time you're ready to commit. Promoting immediately routes 100% of traffic to the winning variant and marks the test as completed. No code deployment, no app release.

<Warning>
  Once you promote, the test is completed and the change is permanent until you create a new test. Make sure you're satisfied with the result before promoting.
</Warning>

<Tip>
  For revenue metrics, a sustained uplift above 5% is the trigger. For conversion and retention, wait for ≥ 90% win probability to act with confidence. If a test has been running for several days with no verdict, consider whether the expected effect size is large enough to detect — a very small change requires a very large sample.
</Tip>