# Growth Experiments

*AI Growth and Strategy*

Run tests that actually settle something

Small companies run growth experiments constantly and learn remarkably little from them, because the tests are underpowered, several things change at once, and results get read optimistically.,Your employee designs them properly: one variable, a sample size your traffic can actually resolve, a stated success threshold before it runs, and an honest read afterwards.,It also keeps the record, so the same idea does not get retried every eight months by someone who was not there last time.

## Benefits

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## How It Works

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## At a Glance

- **Powered** Checked against real traffic
- **Pre-set** Threshold, before the data
- **One** Variable per test
- **Recorded** So tests stop repeating

## Most Small-Company Tests Cannot Detect Anything

Detecting a realistic conversion improvement, a few percent relative, requires a sample most small companies do not have in a reasonable window. Tests get run anyway, one variant edges ahead, and the team acts on what is statistically noise. The damage is not only the wrong decision; it is the accumulated confidence in a testing practice that is not producing knowledge. Checking feasibility before running is a five-minute step that either saves the effort or tells you to make the call on judgement instead, which is a perfectly respectable answer.

## Thresholds Set Afterwards Always Pass

When success is defined after the data arrives, tests become remarkably good at succeeding. A small lift becomes promising, a flat result becomes no harm in shipping it, and a negative one becomes a problem with the test. None of that is dishonesty, it is ordinary motivated reasoning, and the only reliable defence is writing down beforehand what result would change what you do. That single habit does more for the quality of growth work than any tooling.

## The Same Ideas Come Back Every Year

Growth experiments are rarely written down anywhere durable, so the knowledge lives in whoever ran them until they move on or simply forget. Eighteen months later the same idea surfaces, sounds fresh, and gets tested again at the same cost. Teams with any real tenure have usually tested their obvious ideas twice without realising. A written record is dull to maintain and is the difference between a company that accumulates knowledge about its own funnel and one that keeps rediscovering it.

## FAQ

### We do not have much traffic. Can we test at all?

Often not statistically, and saying so is more useful than running an underpowered test and treating the noise as a finding. At low volume the honest path is usually to make the change on judgement, watch for something obviously worse, and spend the effort on qualitative feedback instead.

### How long should a test run?

Until it reaches the sample the design called for, and through at least one full weekly cycle since behaviour differs by day. Stopping the moment a result looks good is the most common way teams generate confident false positives.

### What if the result is inconclusive?

That is a legitimate and frequent outcome, and it gets reported as such. A discipline of accepting inconclusive results is what keeps the conclusive ones worth believing.

### Does it run the tests or design them?

It designs, checks feasibility, prepares variants, and reads results. Pushing a change live goes through your normal process, since a growth test is still a change to what customers see.