Phil Carter

I think one perfect example of this is Jason Vandermeer, who now is the Director of Growth Engineering at Strava. He was an early engineer at Strava. He didn't join to build their growth team. But it turned out he was very good at figuring out, along with others on the team, how to run growth experiments that accelerated the growth of the business or certain parts of the product.

I think one perfect example of this is Jason Vandermeer, who now is the Director of Growth Engineering at Strava. He was an early engineer at Strava. He didn't join to build their growth team. But it turned out he was very good at figuring out, along with others on the team, how to run growth experiments that accelerated the growth of the business or certain parts of the product.

I think one perfect example of this is Jason Vandermeer, who now is the Director of Growth Engineering at Strava. He was an early engineer at Strava. He didn't join to build their growth team. But it turned out he was very good at figuring out, along with others on the team, how to run growth experiments that accelerated the growth of the business or certain parts of the product.

And so then he just became a natural fit to be one of the founding members of their growth team. I think that's often what you can see.

And so then he just became a natural fit to be one of the founding members of their growth team. I think that's often what you can see.

And so then he just became a natural fit to be one of the founding members of their growth team. I think that's often what you can see.

I think the degree to which you should be taking big swings that maybe have lower confidence but much higher impact if they hit versus smaller optimizations is largely a function of the maturity of your company. Or maybe said a different way, you often hear within the growth community this idea of an S-curve.

I think the degree to which you should be taking big swings that maybe have lower confidence but much higher impact if they hit versus smaller optimizations is largely a function of the maturity of your company. Or maybe said a different way, you often hear within the growth community this idea of an S-curve.

I think the degree to which you should be taking big swings that maybe have lower confidence but much higher impact if they hit versus smaller optimizations is largely a function of the maturity of your company. Or maybe said a different way, you often hear within the growth community this idea of an S-curve.

So you launch a product, you're at the early part of the S-curve, it's just starting to get adoption, you find your early adopter group, then you hit a tipping point growth takes off, you're in the steep part of the S-curve where you're getting hyper growth. And then at some point, you start to saturate that market and you hit the upper end of the S-curve where it flattens out and growth stalls.

So you launch a product, you're at the early part of the S-curve, it's just starting to get adoption, you find your early adopter group, then you hit a tipping point growth takes off, you're in the steep part of the S-curve where you're getting hyper growth. And then at some point, you start to saturate that market and you hit the upper end of the S-curve where it flattens out and growth stalls.

So you launch a product, you're at the early part of the S-curve, it's just starting to get adoption, you find your early adopter group, then you hit a tipping point growth takes off, you're in the steep part of the S-curve where you're getting hyper growth. And then at some point, you start to saturate that market and you hit the upper end of the S-curve where it flattens out and growth stalls.

So if you're in the early part of that S-curve, which by definition means any seed or series A startup, you should not be focusing on small optimizations. It's a waste of time for a couple of reasons. One, because it's not going to move the needle enough to make a difference. Two, you should still have lots of low hanging fruit.

So if you're in the early part of that S-curve, which by definition means any seed or series A startup, you should not be focusing on small optimizations. It's a waste of time for a couple of reasons. One, because it's not going to move the needle enough to make a difference. Two, you should still have lots of low hanging fruit.

So if you're in the early part of that S-curve, which by definition means any seed or series A startup, you should not be focusing on small optimizations. It's a waste of time for a couple of reasons. One, because it's not going to move the needle enough to make a difference. Two, you should still have lots of low hanging fruit.

If you're still that early, you're either working on the wrong product, you don't have product market fit, you're working on the wrong solution. Or you should have lots of low hanging fruit left to optimize, which means you should be taking bigger swings.

If you're still that early, you're either working on the wrong product, you don't have product market fit, you're working on the wrong solution. Or you should have lots of low hanging fruit left to optimize, which means you should be taking bigger swings.

If you're still that early, you're either working on the wrong product, you don't have product market fit, you're working on the wrong solution. Or you should have lots of low hanging fruit left to optimize, which means you should be taking bigger swings.

And then the third reason is, oftentimes, even for consumer businesses, and certainly for B2B businesses, if you're that early, you simply don't have enough users to be able to measure a statistically significant difference in a small optimization type of an A-B test. And so you're much better served taking these big swings.

And then the third reason is, oftentimes, even for consumer businesses, and certainly for B2B businesses, if you're that early, you simply don't have enough users to be able to measure a statistically significant difference in a small optimization type of an A-B test. And so you're much better served taking these big swings.