When was the last time you did user research and learned something that shocked you? I’m talking about something that you would never have been able to intuit on your own. I'm referring to the type of insight that only makes sense in retrospect but, in a million years, you wouldn’t have been able to dream up.
Alternatively, when was the last time you did research and the interviewee was shocked by what they learned about themselves?
When you summarized your learnings for the interviewee, did they pause in a combination of emotions from embarrassment to excitement and relief and say “Wow, it just took you two minutes to describe what really happened and it took me fumbling in circles for over an hour.”
If that isn’t happening consistently, there’s probably some opportunity left in how you are doing your research. That is what real insight feels like and it’s the type of insight that dramatically increases the likelihood of product market fit. Why? Because you’ll know what problem you’re actually solving.
One of the biggest reasons for startup failure is that people are building something no one actually wants.
But that is not new. Y-Combinator’s motto is “make something people want.” Yet, founders are still failing too often because no one wants what is built. That's understandable. It’s actually extremely difficult to build things that people want because our customers have no idea what they want. Even worse, we all vastly underestimate how hard it is to determine what they want.
Nicholas Epley is a Professor of Behavior Science at the University of Chicago Booth School of Business who ran a simple experiment demonstrating this issue. Epley separated a couple and quizzed them. One is asked a series of questions about themselves like “How would you characterize your sense of self-worth?” The other partner then predicts their significant other's answers and also provides an estimate of their confidence that their predictions would be correct. The predictions were barely better than guessing. But, most pertinent to us, the predicting partner often estimated that their own accuracy rate was significantly higher than their realized rate. If we have such a troubling gap with our own partner, what might our gap be when we are building things for others? It is no surprise we spend many billions building things nobody wants.
Founders try to solve this issue by talking to hundreds of current or potential customers.
These might be some typical questions:
What do you like about our product?
What do you dislike about our product?
Is there anything you like more about our competitors’ products?
What annoys you most about current products in the market?
Would you like a product that does a, b, and c for you?
How much would you pay for this product?
What features are missing in our product?
How would you see yourself using our product?
We think these questions are a waste of time. We call this searching in the dark. You may find the direction you are looking for but you will spend ten times the needed money and effort. I know, I did this for years.
My partner, Bob Moesta, is a mechanical engineer who built a product market fit framework with Harvard Business School professor Clay Christensen. He taught me a better way to think about building. We start from a much different place. We don’t aim to understand what people want: we accept and respect that we can’t learn that from them. Rather, we focus our energy on understanding why they want something in the first place. We can learn that.
Today it’s known as Jobs to be Done and it has gained tremendous popularity. But we believe the framework is often substantially diluted in how it’s being described and used, often muffling its potential efficacy.
Jobs to be Done delivers the most value as a highly nuanced way to describe demand. It describes the causal mechanisms for people's decisions to switch products. It describes the tradeoffs they are willing to make to progress toward an outcome. It describes the friction they encounter when attempting to make progress. It describes the holes in the market that are underserved, or unserved. It also describes the satisfaction criteria of the customers and/or consumers of the product within a context.
By describing demand this way, you can substantially focus the market. This is different than choosing a smaller market to start with. This is about understanding the subtleties of the market itself so that you know what is not worth trying in your iterations. This includes deciding to NOT build things that your customers are specifically asking for.
When you are searching for PMF through a lens that doesn’t define demand well, the possible set of solutions that will satisfy the demand will be very wide - the black area. You won’t know when you are searching in the completely wrong place. But if you set your intention to understand the "why" behind the demand, you can dramatically shrink the solution set to the much smaller green area.
You’ll still have to prototype and iterate like crazy and show a ton of grit, but your starting point will be closer to what your customers actually want. Of course, you might get lucky and start closer to the target, but we don’t like relying on luck.
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