Our ability to spot opportunities is limited by our intentions, even when we’re trying to be scientific.
More than a few years ago, a friend of mine posted his startup idea on Reddit, looked to see who engaged, and found that the idea resonated with Indians for some reason. He concluded that it wasn’t a good fit, since his financial model required a higher price point than the Indian market could afford. He was looking for signals from Western markets.
You might have noticed that things in India changed pretty quickly! His assumptions about his target market, and his misunderstanding of the Indian economy prevented him from seeing the opportunity.
I once ran an experiment with Leancamp. Instead of selling event tickets, I offered a yearly membership for a lower price than the single tickets, but the conversion rate was low. When I spoke to people that had shown interest, I learned they were all consultants. That explained it - consultants were happy to buy memberships, but not startup founders.
So I moved on; I was mainly trying to get founders to understand Lean Startup.
I only realised later that engaging consultants in this way could have been extremely powerful for founders too. Now, universities are even talking to me about sarting an institute. I missed the early signs.
There’s evidence that successful entrepreneurs find positive outlooks in negative results; if we get lemons, we make lemonade.
Being hypothesis-driven gives us a better model of the world, to explain what we see. Interpreting data comes from the opposite direction. If challenges our models. If we get data that we don’t like, chances are it’s useful to spot our assumptions.
The data points us towards reality.
The question is, are we listening?
Originally posted at entrepreneur.bg
I’m a new parent, and prioritising my attention on our new rhythms as a family.
Work-wise, I’m trekking along at a cozy pace, doing stuff that doesn’t require meetings :)
I have a few non-exec/advisory roles for engineering edu programs. I’m also having fun making a few apps, going deep with zero-knowledge cryptography, and have learned to be a pretty good LLM prompt engineer.
In the past, I've designed peer-learning programs for Oxford, UCL, Techstars, Microsoft Ventures, The Royal Academy Of Engineering, and Kernel, careering from startups to humanitech and engineering. I also played a role in starting the Lean Startup methodology, and the European startup ecosystem. You can read about this here.
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