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How to Find a True Product-Market Fit

Author ryan.drawdy Category Uncategorized

The fastest email experience ever made — who wouldn’t want that?

Well, actually, when Superhuman was first finding its footing, there weren’t too many people who’d be sad to see it go.

Fortunately, Superhuman’s fearless leader, Rahul Vohra, had a feeling it wasn’t the right time to launch then. They hadn’t quite nailed down the product-market fit.

A year later, Superhuman had nearly tripled its product-market fit.

Here’s what we’re unpacking today:

  • Who is Superhuman and why did it take so long to launch?
  • What’s the definition of true product-market fit?
  • How do you measure and eventually increase product-market fit?

This post is based on a podcast with Rahul Vohra. You can hear the full episode here and below.

Superhuman: the fastest email experience ever made

What does Superhuman do?

Rahul: For those who don’t know, Superhuman is the fastest email experience in the world. 

As you yourself [Sangram] have discovered, our customers get through their inbox twice as fast compared to in Gmail. They reply to their important emails faster and many of them sustainably see inbox zero for the first time in years; which, if you haven’t seen it, as you can imagine, it’s fairly life-changing

 

Defining a true product-market fit

Could you walk us through your journey to finding a true product-market fit?

Rahul: It took a while longer than I think most founding teams would have the patience for. For Superhuman to get to product-market fit it was a journey of years. 

For context, my last company Rapportive, we had started, scaled, and been acquired in less than two years. It was only 20 months. To this day, that product remains sort of a cult classic, well known, and beloved. 

So here we were two years into Superhuman and we still had not yet launched. I knew deep down inside that no matter how intensely I felt this pressure — and I felt it most from within myself as well as from the team — that a launch would go very badly if we did not have product-market fit. 

I had searched around for definitions of product market for example. Paul Graham would say you have it when you’ve made something that people want. Sam Altman would say you have it when users love your products so much that they spontaneously tell other users to use your products. 

Then I found Marc Andreessen’s definition of product-market fit and he has arguably the most compelling or the most vivid definition: You almost always know it when you don’t have product-market fit. You know, customers aren’t quite getting value out of the product. Users aren’t quite growing fast enough. Word of mouth isn’t quite spreading fast enough. 

But he says you can almost always feel it when you do have product-market fit because you’re hiring sales and support as fast as you can. You’re adding servers as fast as you can buy them.

I could tell in a very emotional way, Superhuman did not even serve me properly as an example of our market. But all we had were these post hoc definitions, what we call in the business, lagging indicators of success. 

So, I started my search for this holy grail for a way to define product-market fit for a metric to measure product-market fit. And, ultimately, for a methodology to systematically increase product-market fit. 

I searched high and low, I spoke to all the experts, I read everything I could find and then I found the sky. 

Sean Ellis — he actually ran early growth at Dropbox — had found a leading indicator for product-market fit, one that is a benchmark and one that is predictive. 

You simply ask your users, “How would you feel if you could no longer use the product?” and measure the percentage that answers “very disappointed.” 

What he found, is that if you have 40% or more of your users say they’d be very disappointed without your product, then your company will be very amenable to growth and you should double-down on growth. 

If you have less than 40%, then you would probably struggle to grow.

So with that, I had a plan. I was able to go back to the company, do this survey, and show that we weren’t ready. 

In the summer of 2017, we surveyed our users and we found that we only had 22% of our users who would be very disappointed without Superhuman. That may seem sad, but at least it gave me a way to communicate what was happening to our team. 

And most importantly, I had a cunning plan.

 

Increasing product-market fit

How did you go from 22% to 40%?

Rahul: Well, the survey really only has four questions and they are: 

  • How would you feel if you could no longer use the products?
  • Who do you think this product is best for? 
  • What are the main benefits you get from the product? 
  • How can we improve the product for you? 

What I would recommend is that you create a rolling survey. This isn’t a batch process, this is something that is integrated into the user lifecycle.

Wait for them to experience the core value prop of the product. We waited for two or three weeks and then sent them an email with a link to a survey. We happen to use a type form survey with those four questions. 

Now you’d also asked, when do you start to get meaningful results? And the magical thing about the survey is they become directionally representative because you’re looking for a binary outcome with as few as 40 respondents. 

So, if you survey 60 or 80 people, you might get 40 respondents. That’s actually not that many people. Most companies, even very early startups are able to do this. 

In the summer of 2017 when we first ran our survey, as I said, our product-market fit score was 22%.

The thing that most people don’t realize about product-market fit is it’s a double-sided equation. Most of the time as founders we talk about changing the product, but you can also change the market. That’s actually one of the most efficient things to do because you don’t have to rewrite any code. 

By doing a re-segmentation of Superhuman, we immediately got that 22% school to a 33% school. And then we ran a rolling process. A quarter later, it was 47%, a quarter after that it was 56%, and a quarter after that it was 58%. 

So a year after beginning with this process, 58% of our users would be very disappointed without Superhuman. That is a very high score for the survey. 

This product-market fit engine we came up with really does work. It gives you a way to define products-market fit, it gives you a metric to measure product-market fit, and it gives you a methodology to systematically increase product-market fit.

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