---
slug: experimente
title: "How do I measure what the advertising actually achieved?"
category: attribution
locale: en
updated: 2026-10-17
keywords: ["experiment","incrementality","effect","holdout","switchback","switchback trial","geo","confidence interval","Growth","Scale","plan"]
questions: ["Can Metrunio measure the effect of advertising, not just assign it?","Measure incrementality","What does the channel really contribute?","Holdout test","A/B test for advertising","Causal advertising effect","Which plan includes experiments?","Why are experiments locked for me?","Which plan includes the switchback trial?","Is my Meta advertising worth it at all?","Pause advertising and compare","On-off test for advertising"]
url: https://bench.metrunio.com/en/help/experimente
---

# How do I measure what the advertising actually achieved?

**Can Metrunio measure the effect of advertising, not just assign it?**

With an experiment: the switchback trial is available from Growth, two campaign groups from Scale and on the agency plan. An experiment compares two groups that should differ in exactly one thing and measures the difference along with its uncertainty. Attribution does not answer this: it says which touchpoint a conversion is credited to, not whether it would have happened without the advertising.

> **Note:** The switchback trial comes with Growth, two campaign groups with Scale and the agency plan. On Start and Pro, “Experiments” shows in the navigation with a lock; the page there says what it does and leads to “Plan & usage”. On Growth, “Two campaign groups” shows in the selection with a lock “from Scale”. The “measured” level under “Check budget” comes only from two campaign groups. Experiments you created stay stored and reappear as soon as your plan includes them.

| Design | What is compared | For what | From plan |
| --- | --- | --- | --- |
| Switchback trial (on and off) | periods of the same scope | Does this channel contribute at all? | Growth |
| Two campaign groups | two groups in the same period | Which of the two setups works? | Scale |

1. Open “Experiments” and create one with a hypothesis: what you expect, written down before the result.
2. For the switchback trial, enter the periods when the advertising ran and when it was off. Switch at least twice.
3. For the group comparison, assign each group its campaigns.
4. Wait out the period and read the result. It states the verdict in one sentence, the numbers behind it, and the caveat.

## What “no measurable difference” means

A full result, not an error and not a placeholder. It means: the observed difference cannot be told apart from noise. Metrunio then extrapolates nothing either. “Plus four per cent” from twelve conversions reads like a result and is not one.

> **Caution:** For small shops a switchback trial often ends with “no measurable difference” or “not enough data yet”. It takes at least 100 opportunities per group and 10 conversions in total, and considerably more for a narrow interval. With around 100 orders a month, the difference made by a single campaign is usually smaller than the noise. The result then says “not shown”, not “does not work”. The planning from “Check budget” tells you beforehand how long the trial would need to run at your pace.

## Why this is not a geo experiment

There is no separate design for it, because Metrunio does not know the region of a visit: it stores no IP address. If you target geographically, split your campaigns into two groups; then “two campaign groups” measures exactly that. It is not a geo experiment in the strict sense: that would need a control region with no ad exposure at all, and Metrunio would only see its purchases if measurement ran there anyway. Comparing two advertised groups tells you which did better, not what would have happened without advertising. The region sits in the campaign instead of in a guessed attribution.

> **Caution:** No calculation can check whether the groups differed only in the thing being tested. A promotion, a public holiday, a press mention: all of it would land in the result. The caveat therefore sits on every result, so that it travels with it when you pass it on.

> **Note:** The confidence interval follows from the principle that every figure says what it rests on: it states explicitly how certain a measured number is. Without an interval the difference would be a claim.

## Also asked

- Measure incrementality
- What does the channel really contribute?
- Holdout test
- A/B test for advertising
- Causal advertising effect
- Which plan includes experiments?
- Why are experiments locked for me?
- Which plan includes the switchback trial?
- Is my Meta advertising worth it at all?
- Pause advertising and compare
- On-off test for advertising

## Related

- https://bench.metrunio.com/en/help/attributionsmodelle
- https://bench.metrunio.com/en/help/messgrenzen
- https://bench.metrunio.com/en/help/gemessen-zugeordnet-geschaetzt
- https://bench.metrunio.com/en/help/budget-entscheiden
- https://bench.metrunio.com/en/help/tarife