# Post-Test Metrics

Post-Test Metrics is a view available from the **Key Metrics** dropdown in the **Results** tab of a test. It helps you understand what happened *after* your test ended, not just during it.

Where standard test results measure performance within the experiment window, Post-Test Metrics tracks the downstream purchase behavior of customers who converted during the experiment, split by variant. \
\
This makes it possible to ask: **which variant drove more valuable customers over time?**

#### How It Works

Post-Test Metrics looks at customers who converted during the test and tracks their purchase activity after that conversion, broken out by variant.

A few important details:

* Tracking is tied to **customer ID / customer email**, not browser cookie
* Data is available for up to **one year** from test start
* Existing test filters affect which in-test customers are analyzed, but **do not affect post-test orders** (e.g., filtering to orders containing a specific product narrows the set of in-test customers, but post-test orders from those customers reflect all purchases)
* The **Include in-test orders** toggle controls whether the first (in-test) purchase is counted in downstream metrics

#### Post-Test Metrics

* **In-Test Customers:** The number of customers who converted in each variant during the experiment window.
* **Post-Test Orders per Customer:** Average number of orders placed after the test by customers who converted during the experiment, per variant.
* **Post-Test Revenue per Customer:** Average revenue generated after the test by customers who converted during the experiment, per variant.
* **Post-Test Profit per Customer:** Average profit generated after the test by customers who converted during the experiment, per variant.
* **% of Customers with Post-Test Order:** The share of in-test customers who placed at least one additional order after the experiment.
* **Post-Test Revenue per Visitor:** Post-test revenue normalized by the total number of in-test visitors for each variant. This allows fair comparison across variants regardless of size.
* **Post-Test Profit per Visitor:** Post-test profit normalized by the total number of in-test visitors for each variant. With the **Include in-test orders** toggle enabled, this is Intelligems' best approximation of an LTV estimate compared head-to-head between test groups.

#### Include In-Test Orders Toggle

The **Include in-test orders** toggle (checked by default) controls what counts as "post-test" behavior:

* **Checked:** Post-test metrics include the original in-test purchase plus any subsequent orders. This produces an LTV-style view of customer value from the moment of acquisition.
* **Unchecked:** Post-test metrics reflect only orders placed after the test ended, excluding the initial conversion. This isolates repeat purchase behavior.

#### When to Use Post-Test Metrics

Post-Test Metrics is most useful for tests where long-term customer value matters more than immediate conversion, particularly:

* **Pricing tests:** did a lower price attract lower-value customers?
* **Shipping tests:** did free shipping drive more repeat purchases?
* **Subscription tests:** how did variant groups behave after initial sign-up?
* **Merchandising tests:** did one variant drive better repeat behavior?

It's also useful retroactively. Historical tests can be revisited to evaluate downstream impact, as long as the required customer-level data is available.

{% hint style="info" %}
**Note:** Long-term customer behavior can be influenced by many factors after a test ends, especially for brands that run frequent tests or make significant changes between experiments. Post-Test Metrics is most reliable when interpreted in context rather than as a standalone measure.
{% endhint %}