VIDEO: Experiment Design: From A to Z

VIDEO: Experiment Design: From A to Z

Cool Growth Hack:

Experiment Design: From A to Z

In this video, we will guide you through experiment design from beginning to end.

We start with why you should experiment in the first place. And then we move on to the G.R.O.W.S process, which is the framework and the process that will help you experiment and make sure that you set every single step up correctly in order to experiment.

Then, we move on to types of experiments, we’ll see what are the different types that we can try, the most common experimentation pitfalls and advice on some things that you shouldn’t be doing.

So let’s do it!


Resources mentioned in the Video:


So the first thing is why experiment in the first place? We need to experiment because we need to de-risk ideas, and experiments need to be something that will help us validate our ideas. So it’s impossible to predict how people will react in a fast-changing world.

Now we know why we need to experiment and what kind of mindset we need to adopt – enter the G.R.O.W.S process. This is what we need to be able to experiment correctly. It’s a five-step process that will help us set the stage for the right experiments.

Step number one is gathering ideas, and how do we gather ideas, again, we rely on previous data.

Step number two is ranking ideas. If you have 50 amazing ideas right now you cannot try them all at once, what you have to do is prioritise.

Step number three involves outlining the experiment. For this, you can use the experiment design canvas, the link is in the resources above.

Step number four – this is when we get shit done. So make sure that you do, and make sure that you’re tracking everything, make sure that you’re studying the data, because at the end of the day if we do not learn from this experiment, nothing will matter!

And finally, we study the results so we can see what worked and what did not. And in turn, what experiments will come next as a result.


We hope this video will give you a clearer view of how to build experiments, from beginning to end.

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