We took a look at the data from our first 150 pre-seed investments to get a sense for the relationship between monthly burn rate and the likelihood that a company will graduate to the seed round.
I think it is a very meaningful analysis. More to the point, what did the companies that were successful in seed financing and those that were not, and what did they spend their money on? I think it would be more meaningful and new discoveries would be made if we could understand the differences.
I also wanted to know if there were any differences between companies that were successful in seed financing and those that were not, as factors in your decision to invest. Because I think that investment decisions in the Pre-Seed stage are extremely dependent on personal intuition and experiences, not on science. There may be some kind of rule of thumb there, or maybe it exists in you, but I thought it would be interesting to visualize it.
This is a great post. Obviously I agree with the thrust of the argument but I am surprised you find the difference in the two groups to be only about $12 k a month. Which is less than one FTE or couple of customer pilots (b2b) that went bad etc. So the mistake in this "under funding" post would appear to be less due to real under allocation- as burning a couple of Pilots may be chalked upto learning investment - and more due to betting on wrong beachhead or persisting in poor beachhead for too long or not driving enough hypotheses based tests early enough etc etc. So, I would want to see if there's another cut of your data that shows the length of experimentation, the user discovery rigor etc. Yet another data point not clear to me is if this is b2b or b2c universe where CAC is so different and expense for pilots etc is very different.
I think it is a very meaningful analysis. More to the point, what did the companies that were successful in seed financing and those that were not, and what did they spend their money on? I think it would be more meaningful and new discoveries would be made if we could understand the differences.
I also wanted to know if there were any differences between companies that were successful in seed financing and those that were not, as factors in your decision to invest. Because I think that investment decisions in the Pre-Seed stage are extremely dependent on personal intuition and experiences, not on science. There may be some kind of rule of thumb there, or maybe it exists in you, but I thought it would be interesting to visualize it.
This is a really insightful read, thank you!
This is a great post. Obviously I agree with the thrust of the argument but I am surprised you find the difference in the two groups to be only about $12 k a month. Which is less than one FTE or couple of customer pilots (b2b) that went bad etc. So the mistake in this "under funding" post would appear to be less due to real under allocation- as burning a couple of Pilots may be chalked upto learning investment - and more due to betting on wrong beachhead or persisting in poor beachhead for too long or not driving enough hypotheses based tests early enough etc etc. So, I would want to see if there's another cut of your data that shows the length of experimentation, the user discovery rigor etc. Yet another data point not clear to me is if this is b2b or b2c universe where CAC is so different and expense for pilots etc is very different.
Thoughts Please?