What's the best way to manage risks in customer discovery and validation?

At 0-1 stage, your job as founder, PM, corporate innovator is to A. Validate: - Market segment chosen - Problem faced by market - How your product solves the product or B. Discover: - New market segment that resonates - New problems that fits the product - How else to solve the problems differently.

When you talk to someone, the entire focus of the conversation should be to learn the pain-points of the "potential" customer. If we have a hammer, everything looks like a nail. We should keep our hyothesis to ourselves and listen to the customer with an open mind. I would say it is a good idea to go deep in these conversations and take notes. At this stage, it is difficult to validate much. The objective should be to listen. This is not to say that you should not have a hypothesis, in fact the very fact that you are talking to someone means that you have a hypothesis :-)

1. Precision Over Ambiguity: Clearly defined hypotheses remove ambiguity, ensuring you don't waste resources. 2. Iterate Regularly: Business landscapes change, so hypotheses must not be static. 3. Embrace Negative Outcomes: Validating what doesn't work is as crucial as confirming what does. 4. Balance Quantitative & Qualitative Data: While numbers can show user preferences, qualitative feedback explains the reasons behind those preferences. 5. Guard Against Biases: Feedback biases can lead startups astray. Well-defined hypotheses act as both a roadmap and a compass, directing them to genuine market needs and steering them clear of assumptions.

There are several factors to take into account when risk-grading your hypothesis. Assumption criticality: Essentially, the more central the hypothesis is for your overall business model to be successful, the higher the risk is to your business it its proven to be false. Lack or evidence: If there is little or no underlying evidence to back up your hypothesis the risk will be higher because it has not yet been validated. New and innovative ideas: Despite entrepreneurship being the realm of innovation, a new never before seen idea carries inherent risk. Imagine pitching the idea of launching a chain of gyms versus providing personal trainers for dolphins online. A VC will likely have more issues with the latter due to it highly novel nature.

One of the key factors to truly validate a hypothesis is racking up the numbers. More it more in this case. For example, if you ask two people the same question and they both provide the same answer, then 100% of your subjects will either agree or disagree with your hypothesis. It might look good when presenting the numbers. But very few people will be impressed by the method. However, if you ask 10,000 people and 85% agree with your hypothesis, the percentage is lower. But the credibility of the hypothesis being correct will be significantly higher than in the first example.

If at all you come to a stage where the customer has expressed their desire to use your product/service to ease their pain the most important thing is to understand if they are willing to pay for it. You might think that you are figured out a solution to their problem but if they are willing to pay zilch for it then maybe your business model might not make much sense. On the other hand, if they are willing to pay something for it, there is a good chance they will pay more than what they are willing to right now.

As in most VC analysis processes I've done, money is king. If you can get people to actually part with money even before you have you product, and do that reliably, you're on to something. In falling order, reliable evidence can be as follows: - Actual payment - Pre-order - Signed contracts - Pilot programs - Beta testing - Waitlists - Engagement metrics - Prototype or MVP usage - Interest expressions (likes, shares, comments, up-votes etc) - Click-through rates There are of course additional pieces of evidence that can be gathered as you are building your case and the above just provides a brief overview of how evidence can be weighted.

There is a limit to this however. Henry Ford once famously said "If I had asked people what they wanted, they would have said faster horses" There is a certain magic to being an entrepreneur. Almost like having an intuitive sense of what the market wants and how to provide it. The issue is that there's often a tenancy among entrepreneurs towards overrating their ability to understand their market or their customers. And by doing that, they often ignore the scientific approach that is most often required to properly validate a hypothesis.

One should definitely iterate and pivot but just keep in mind that you don't do it too soon. By design, new ideas take time for validation so one shouldn't start with the idea of pivoting. Think hard, talk to customers, provide the best possible product/service and only when it has failed after persistent efforts, think about pivoting.

Having been part of many ventures and mentoring a lot of entrepreneurs, I can't overstate the importance of risk mitigation. There are so many pitfalls in building a venture into a thriving company that it's close to impossible to make it all the way without applying a certain methodology. There's a reason why some people fail while other succeed over and over again. That reason is called method. The best way of learning that method is to talk to people who have been where you are and made it. And the best way to make that happen is to simple reach out. You will be surprised over how many successful entrepreneurs are willing to share their knowledge.

Burn the bridges before you start. If you have a fallback option when you start your journey, chances are you will use that option. Trying to build a venture takes a lot of time and persistence. The key is to keep on moving ahead. Try to talk to a couple of senior entrepreneurs from the field and you will get some good advice.