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Start with a Belief

People looking at a data dashboard with an idea lightbulb in the middle

To build successful products using data and experiments, you must start with a hypothesis. Data can inform your decisions, but they cannot decide for you. Simply following the data wherever it leads will create an incoherent product. It will be lifeless and uninspiring.

Successful products begin with an insight. Data isn’t insight. Data by itself can lead you astray. It’s easy to drive a single metric up in a way that is harmful in the long term. Without an insight into how that number should move, chasing the data can lead to a quantitative success that’s a qualitative failure.

Start with the question you want to answer. Start with a belief about the world. Those beliefs can be formed by past research and experiments. Past data can reveal context or trends that become a hypothesis. The beliefs can also come from experience, domain expertise, observation, or even creative sparks.

Experiments and data can validate your hypothesis. You have an idea that if you do something you’ll change the way people behave. They’ll buy more products. They’ll use this feature more. They’ll stick around longer. They’ll invite their friends. The data tells you if you are right. It helps you add detail to your hypothesis. It tells you the idea was correct for some people but wrong for others.

Without a hypothesis to start from, data can’t provide insights. You don’t know what the data is telling you. Be data-informed, not data-driven.

Recently Written

Too Big To Fail (Apr 9)
When a company piles resources on a new product idea, it doesn't have room to fail. That keeps it from succeeding.
Go small (Apr 4)
The strengths of a large organization are the opposite of what makes innovation work. Starting something new requires that you start with a small team.
Start with a Belief (Apr 1)
You can't use data to build products unless you start with a hypothesis.
Mastery doesn’t come from perfect planning (Dec 21)
In a ceramics class, one group focused on a single perfect dish, while another made many with no quality focus. The result? A lesson in the value of practice over perfection.
The Dark Side of Input Metrics (Nov 27)
Using input metrics in the wrong way can cause unexpected behaviors, stifled creativity, and micromanagement.
Reframe How You Think About Users of your Internal Platform (Nov 13)
Changing from "Customers" to "Partners" will give you a better perspective on internal product development.
Measuring Feature success (Oct 17)
You're building features to solve problems. If you don't know what success looks like, how did you decide on that feature at all?
How I use OKRs (Oct 13)
A description of how I use OKRs to guide a team, written so I can send to future teams.

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