It's boilerplate for companies that lose money! Most IPOing companies outside of the tech sector certainly don't have this in their S-1.

It's only not notable because if you've even skimmed the rest of the S-1, you already know whether they make money or not. If you haven't, it's possibly the most notable thing there. It's the single bit of information that tells you most about the company's historical financial performance.

I mean the question isn’t if they’ve made money, but can they make money in the future.

Every investor is looking for a diamond in the rough.

wait till interest rates go negative! everyone here will be able to IPO, if you aren't already doing something similar in the crypto markets!

Agreed but what is noticeable is how much greater the losses are this year (with still three months to go).

2018: $97.2m

2019: $86.0m

2020: $203.2m

If LTV >> CaC then spend.

Assuming your LTV calculations are correct, then this will work out.

LTV models are really, really hard to get right though, and I've seen a bunch of startups go bust because of getting this wrong.

By now they have LTV metrics by cohort surely, no need to model things out in the dark

If you're spending more than you're making, then you're almost certainly projecting LTV.

The big, falsifiable assumption here is that your acquisition sources will keep sending you users of the same quality. Because of the way that ML systems work, this tends to not be true, and if you are using long windows it will both take you a long time to realise this, and cost you a bunch of money.

This is normally how companies go bust/stop growing as a result of LTV models.

While in a vacuum larger losses aren't painting the full picture, but then if you take their revenue growth only increasing by 70% into context it looks even worse!