The Biggest Issue with Product-Market Fit

What's up, everyone? Welcome back to another episode of Founders Journal. I'm your host, Alex Lieberman, co-founder and executive chairman of Morning Brew. Before we hop into the show, I have a 10-second favor to ask of you. We have tons of new listeners to the podcast, and my goal is to get to know as many of you as humanly possible. Now, what I'm about to say is either the smartest thing I've ever done or the absolute dumbest. Either before you start this episode or right after you finish it, shoot me an email to my personal email, alex@morningbrew.com. If you want the easiest option, the two-second option, just say hi in the subject line, literally H.I., and I will respond to you getting the conversation going. If you're a little bit more ambitious and maybe you have thirty seconds instead of two seconds, shoot me an email to alex@morningbrew.com and tell me a little bit about yourself and why it is that you listen to Founders Journal. I cannot wait to get to know you over the coming days, and you know, for me, it's the best part. Of this podcast is getting to know the community and the listeners who give me their time. Now, for today's episode, I'm going to talk about the entrepreneur's ever elusive North Star that is product market fit. Let's hop into it. I've been thinking about product market fit a fair bit recently, partly because it's the number one focus at Storyyard, my executive ghostwriting agency, because I don't think we. Have product-market fit yet, but I think we can get there in the next few months if we stay relentlessly focused on checking in with our customers and iterating on our service and our process. I also have been thinking about it partly because I feel like a lot of founders are focused on the wrong things today, focused on growth and focused on acceleration of revenue. And I think it's largely driven by social media's pressure. To build and grow things fast. Now, Raul Vora from Superhuman put it perfectly in 2018, and I think it's as relevant what he said today. Raul said investors advising early-stage teams should avoid pushing for growth ahead of product-market fit. As an industry, we all know that this ends in disaster. Yet the pressure for premature growth is still all too common. Startups need time and space to find their fit and launch the right way. So my hope with this episode is to help reiterate the importance of finding product-market fit, however long it may take you before focusing on other things like growth. And I want to give you a simple single metric for any entrepreneur, irrespective of the market you're in or the product that you've built, a metric that you can focus on that can be a really good proxy for knowing if you do or don't have product-market fit. Let me start by talking about the issue with product-market fit. There are dozens of definitions for it given by really smart people, people way smarter than me. But historically, there hasn't been a super measurable way that is broadly applicable to lots of different companies to know whether you have achieved product market fit or not. And because it's been largely subjective and based on feeling, I believe it prohibits entrepreneurs from obsessing about hitting product market fit as much as they should. Because at the end of the day, that is the number one job of an entrepreneur, or their number one first job before they find product market fit. Once they do, then it's about building a company. Here, I wanna share a few of the most well-accepted definitions of product market fit before I talk about the definition that I have found to be most satisfying. Marc Andreessen's definition is product market fit means being in a good market with a product that can satisfy that market. You can always feel when product market fit isn't happening. The customers aren't quite getting value out of the product. Word of mouth isn't spreading. Usage isn't growing that fast. Press reviews are kind of blah. The sales cycle takes too long and lots of deals never close. And you can always feel product market fit when it is happening. The customers are buying the product just as fast as you can make it, or usage is growing just as fast as you can add more servers. Money from customers is piling up in your company checking account. You're hiring sales and customer support staff as fast as you can. Reporters are calling because they've heard about your hot new thing and they want to talk to you about it. You start getting Entrepreneur of the Year awards from Harvard Business School. Investment bankers are staking out your house. You could eat free for a year at Box. That's Marc Andreessen's definition. I also don't know what Box is, so maybe someone can inform me. Now let me share 2 more definitions. Elad Gil, who's one of, you know, arguably the greatest early-stage venture capitalists of all time. He defines product-market fit as you have very strong customer feedback, even from a small group of people. For example, at Color, early on, we were getting literal love letters from customers. And then the final one I want to share is from Sam Altman. Sam Altman defines product-market fit as, I think the right initial metric is, do any users love our product so much they spontaneously tell other people to use it? Now, while I agree with the sentiment of all of these definitions, I think they are riddled with the same issue— measurability or lack thereof. If you tell a founder to measure for Andreessen's definition of, quote, customers are buying the product as fast as you can make it, or Elad Gil's definition of, quote, getting literal love letters from customers, they won't be able to know exactly if they've hit product-market fit like If an entrepreneur doesn't get love letters, does that mean that they should worry they don't have product market fit yet? If an entrepreneur didn't get an Entrepreneur of the Year award or didn't get their door knocked on by every reporter, does that mean that they haven't hit product market fit? Not necessarily. So these are the definitions that, again, really smart people have shared, but I find to be unsatisfactory from a measurability perspective. Now, I want to share 2 more definitions that are more specific, but they have their own trade-offs. Brian Balfour, who is, you know, one of the most highly regarded Growth minds in the startup space. He says plot the percentage active users over time for various cohorts to create a retention curve. If it flattens off at some point, you have probably found product-market fit for some market or audience. And then David Sacks, who is co-host of All In, he's a successful entrepreneur, successful B-SaaS investor. His definition is, quote, burn multiple equals net burn over net new ARR. The higher the burn multiple, the more the startup is burning to achieve each unit of growth. The lower the burn multiple, the more efficient the growth is. This is a measure of product-market fit. The startup that generates $1 million in ARR by burning $2 million is more impressive than the one that does it by burning $5 million. In the former case, it appears that the market is pulling product out of the startup, whereas in the latter case, the startup is pushing its product onto the market. VCs will make inferences about product-market fit accordingly. End quote. Now, I love that these definitions are more objective because it allows an early-stage business to orient its priorities and its roadmap around an actual tangible metric. But the issue with these 2 definitions is applicability. In both examples, these definitions of product-market fit are limited to a certain subset of companies. The first definition around retention, I do think, is a great metric to follow, but I am left with more questions than answers. For example, what is considered a retention number that equates to product-market fit? How does that number differ across industries? And what should my retention number be given the industry that I'm in? Right. A lot of questions that I need answers to in order to make that my North Star metric. Now, the second definition by David Sacks is great if you're in B2B SaaS, but outside of that space, it's probably not the best proxy to follow either. We're going to take a quick break, but more from Founders Journal. When we get back. So all of this to say that there are a lot of fine definitions for product-market fit out there, but none that are both measurable and applicable to a wide array of businesses. This hunt for a better metric led me to a 2018 article by Rahul Arvora, who's the founder of Superhuman, which is basically a better version of Gmail, where he too was in search of a better metric for product-market fit. And what Rahul says is, The descriptions of product-market fit all seemed so post hoc, so unactionable. I had a clear understanding of where we stood, but I had no way of conveying that to others and no plan for the part that should come next. So I racked my brain for an answer on how to travel the distance between where Superhuman was and the high bar that we needed to hit. And I eventually started to wonder, what if you could measure product-market fit? Because if you could measure product-market fit, then maybe you could optimize it. And then maybe you could systematically increase product market fit until you achieved it. Rahul searched for this answer to how could you successfully measure product market fit, and he found his answer hidden in the depths of the web in an article that was written by Sean Ellis, the former head of growth at Dropbox, Eventbrite, and Andela. And what Sean Ellis said is very simple. To get a proactive measure of product market fit for your business, you should survey your customers and ask them a very simple question. How would you feel if you could no longer use the product? So that's the question you would ask to your users and you would give them 3 options: very disappointed, somewhat disappointed, and not disappointed. What Sean Ellis found is that achieving product-market fit requires at least 40% of your users responding that they would be very disappointed if they did not have access to your product anymore. And Ellis got to this what seems like an arbitrary percentage, 40%, by comparing results across 100 startups and finding that the companies that struggle for traction were always under 40% of their customers being very disappointed if they could no longer use the product. So that's the metric. It's measurable, which means you can optimize towards it, and it is applicable across any type of business. Now, Rahul from Superhuman took this definition of product-market fit and he took it a step further, basically breaking down a system for what you do once you've surveyed your customers and you know what percentage of them would be very disappointed if they never use your product again. And so his process started with a 4-question survey, and he sent these 4 questions to all of his users. The first is the product-market fit question that I said, which is how would you feel if you could no longer use Superhuman? Second is what type of people do you think would benefit most from Superhuman? Third is what is the main benefit you receive from Superhuman? And fourth is, how can we improve Superhuman for you? All of these questions, these 4 questions were very intentional by Raul. From this survey, he wanted to be armed with information to accomplish 3 things. He wanted to know if he has product-market fit or not. He wanted to know what is the customer segment that gets the most value from Superhuman. So said differently, what is the customer segment that he and his team should be most focused on? And third, what are the things that he and his team can do to get the right customer segment over the 40% threshold. So now I want to summarize what Rahul found and what he did based off of his findings. When he first ran the survey, he saw that 22% of users would be very disappointed if they could no longer use Superhuman. Obviously, that is well lower than the magic 40% number. But then what he did was he focused on the segment of customers that had answered very disappointed and thus would be Superhuman's most passionate customer base. Raul found that founders, managers, executives, and business development people were the 4 customer segments that responded very disappointed to that first question, whereas segments like sales, data scientist, engineer, and customer success were not. And so he eliminated those last 4 segments. He no longer put focus on them. And once Raul just focused on those first 4 segments, the percentage of users in these segments that chose very disappointed jumped from 22% to 32%. So by focusing on the right segments, the right customers, he and his team were getting closer to the 40% number, but they weren't there yet. So the thing he started doing to try to close this 8% gap from 32% to 40% was to analyze the feedback from the right people. He looked at feedback gathered on question 3, which is, what is the main benefit you receive from Superhuman? And he looked at feedback from question 4, which is, how can we improve Superhuman for you? And his goal was to start finding patterns that could lead to product improvements that could convert people who responded somewhat disappointed to ultimately responding very disappointed to get to that 40% number. One other thing that Raul's team did that is really important for any founder is they ignored feedback from customers who said they would not be disappointed if they could no longer use the product because these were folks in customer segments that the company would no longer be focused on. On top of that, they also ignored people that were somewhat disappointed but did not state the main benefit that power users of Superhuman most frequently stated, which in the context of their business was speed. Basically, in saying it a different way, Raul focused on people who were very disappointed to improve their experience even more, and he focused on people who were somewhat disappointed and came to Superhuman for the right main benefit, because that told him and his team that they were in the right customer segment, but just required some product improvement. To move them from somewhat disappointed to very disappointed. And the final step, after knowing how far from product-market fit Superhuman was and focusing on the right segments of customers, was to build a product roadmap that was informed by all of the answers to these questions, specifically by the right customers' answers to these questions. And they focused their roadmap on 2 things. First, double down on the main benefit that customers love Superhuman for, which in their case was speed. And second, address what is holding Superhuman back from having more customers in the very disappointed category of the product-market fit question. This translated to Superhuman dedicating half of its product roadmap to the things that their very disappointed users loved and dedicating half of their product roadmap to the things that the right somewhat disappointed users wanted more of. And so this is by far and away my favorite approach to thinking about product-market fit. It allows you to measure it objectively. It can be measured and used and applied across companies, industries, and products. And you can use that measure to dictate how exactly you run your business. There is a lot there. So let me know if you have any questions about this topic. And on top of that, I've linked in the show notes to, of course, Rahul's article on how he measures product-market fit, as well as some of my other favorite resources on this topic. As always, thank you so much for listening, and I'll Catch you next episode.