Aye Moah

They are very high effort experiments that are quite simple to run.

You just have a very clean two cohorts run it versus they are something that's like a small simple change, but the cohort setup can be very complicated or very easy to mess up.

So one thing we learned in the experimentation framework that we pick up is take rice,

But C is now, instead of confidence, it's complexity.

And the I is really tall.

I wanted to get this visual in your mind and bring it home because impact basically beats everything else.

If you have a high impact result or hypothesis that you can know that can bring you a very high leverage thing, start there.

One impact being equal, you can kind of

you know, figure out what's easy, what's risky.

And then the risk part, if you're starting out, you don't have that many customer, you don't have that many revenue, don't worry about it.

For us, it does matter because we have, you know, tons of thousands of customers, subscribers, millions of users, and several millions of ARR to protect.

So we needed the gut real and really estimating the risk.

This is our experiment dashboard.

I am happy to share this with folks.

It's one through about four to five iterations as we go through.

Templates and checklists to retain the learning from every mistake that you make.

Trust me, you'll make it regardless of how much, like,

preparation and thinking through and planning, you'll still make mistakes once you run.

We actually have a proposal template.

Anyone can propose an experiment if they write up the proposal.