[Response] Thank you, Alex.
I agree with your comment philosophically. Where the truth lies here is in the specifics.
One way to understand this problem is like Anna Karenina’s first line: “”All happy families are alike; each unhappy family is unhappy in its own way.” Similarly, all successful startups are alike; each failed startup failed in its own way.
What it means is that there’s 10,000 ways a startup can fail. There’s an inordinate amount of things that need to be right for a company to be successful.
Post product/market/channel/model fit is a great moment to join because the risk-adjusted return is highest: the risk has been substantially mitigated, while the return is still high.
In an established company, the growth rate is not going to be very high, so the stock’s value growth won’t be high either. Because a $1B startup growing at 40% YoY is still growing very fast, it can easily keep going up and up and up. Doing a 10x on $200,000 of stock is much much better than 2x on $400,000 of stock in an established company. The pie is growing faster in hypergrowth, and that drives the fact that it ends up bigger.
The problem with pre-product market fit is that the bulk of risk has not been eliminated yet. Out of the 10,000 risks, you still have 9,000. You can try to address as many as possible, but you will never be able to do it completely.
That’s why VCs work the way they do. That’s why they make small investments in lots of early startups: they just don’t know which ones will win. They try to increase the odds by doing their due diligence on the business, but they know there’s a limit to what they can know. And why they rely on what other VCs do: there’s so much that can be missed that looking at what others do is a strong signal.
The later the stage, the more issues have been eliminated, and the more due diligence can uncover potential remaining issues.
Note that my 4 metrics don’t try to analyze the business in depth. It doesn’t try to identify leading metrics. It looks mostly at lagging metrics.
If you want to look at leading metrics, some of what you say becomes relevant. It reminds me a lot of the—defunct—Social Capital’s amazing Growth Accounting series written by Jonathan Hsu.
I would say though that the first three metrics you mention are really good. If a company performs on all 3 really well though, then it should actually not be too far away from the numbers I’m talking about.
For example, if you have loops that are growing but you’re making just $1M, my confidence on your ability to ramp those loops up is small. If you’re seeing 20% growth week over week, of course, that changes the analysis. If retention is through the roof, like Slack had (with negative churn), then again it’s worth looking into it.
You should look at all the metrics as a whole, and when some falter, the others must more than make up for it. The 4 metrics that I mention should be seen in aggregate. Eg, if you’re making $30M ARR but 300% growth YoY, these are amazing numbers and the company is worth considering.
And the farther away you are from these metrics, the more risk you have, and the more you want to do due diligence in other indicators like the ones you call out. But there’s no way around the fact that you won’t be able to fully mitigate the risk. There’s nothing better than cash pouring into the bank.
