The Product/Market fit (PMF) Score
Can Product/Market fit be measured?
I came across this article by Rahul Vohra that completely changed my approach of how Product teams must prioritize in a startup ecosystem. In this blog post, I’m going to share my learnings & takeaways from the Product/Market fit engine built by Superhuman 🦸♀️
Hello beautiful fellas,
Welcome to the Daily product management show! 📺 I’m your host, Bhavya, and I’ll be bringing you fresh insights on product management every day! 👋
So let’s dive in!
What is Product/Market Fit?
Product/market fit has always been a fairly abstract concept making it difficult to know when you have actually achieved it. Yet many entrepreneurs have highlighted the importance of creating a product that resonates with the target market
The Lagging indicator definitions of PMF:
1.The Y Combinator founder Paul Graham described product/market fit as when you’ve made something that people want!
2.Sam Altman characterized it as when users spontaneously tell other people to use your product.
3. Marc Andreessen’s blog post:
You can always feel when product/market fit is not 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.”
The Leading indicator definition of PMF:
Sean Ellis came up with the following proactive approach to measuring PMF- Just ask users “how would you feel if you could no longer use the product?” and measure the percent who answer “very disappointed.”
After benchmarking nearly a hundred startups with his customer development survey, Ellis found that the magic number was 40%. Companies that struggled to find growth almost always had less than 40% of users respond “very disappointed,” whereas companies with strong traction almost always exceeded that threshold.
PMFsurvey is a free tool that helps you run the Sean Ellis test and measure your company’s product/market fit. 👆
Superhuman nailed their product/market fit, & this is exactly how they did it 🔨
The PMF survey:
SuperHuman identified users who recently experienced the core of our product, following Ellis’ recommendation to focus on those who used the product at least twice in the last two weeks. They floated the following survey to their user-base at that point-
1. How would you feel if you could no longer use Superhuman? A) Very disappointed B) Somewhat disappointed C) Not disappointed
2. What type of people do you think would most benefit from Superhuman?
3. What is the main benefit you receive from Superhuman?
4. How can we improve Superhuman for you?
The raw results from the survey were far from perfect (22% opting for the “very disappointed” answer) as opposed to the 40% threshold recommendation.
THE FOUR-STEP MANUAL FOR OPTIMIZING PRODUCT/MARKET FIT
Step 1: Segment to find your supporters and paint a picture of your high-expectation customers (HXC)
Superhuman was determined to improve their product/market fit score, so they started by segmenting their users. They wanted to identify those who were truly passionate about their product.
- Biggest supporters = The “very disappointed” group
- High-Expectation Customers (HXC) = Further analysis of the second question’s responses specifically from the “Biggest supporters” group.
Analysis to figure: Who product is working for & the language that resonates with them.
Julie Supan’s high-expectation customer framework as a tool to do just that. Supan notes that
The high-expectation customer (HXC) isn’t an all encompassing persona, but rather the most discerning person within your target demographic. Most importantly, they will enjoy your product for its greatest benefit and help spread the word. For example, Airbnb’s HXC doesn’t simply want to visit new places, but wants to belong. For Dropbox, the HXC wants to stay organized, simplify their life, and keep their life’s work safe.
SuperHuman then zeroed their focus on their HXC, a tool to focus the entire company on serving that narrow segment better than anybody else.
It’s better to make something that a small number of people want a large amount, rather than a product that a large number of people want a small amount. The product/market fit engine process of narrowing the market massively optimizes for a product that a small number of people want a large amount.
Step 2: Converting On-The-Fence Users into Fanatics
- To bump up their PMF score, Superhuman then analyzed the next 2 questions from their survey specifically for the HXC — why users loved it and what held others back.
- They paid close attention to 3rd question — the main benefit users received from their product, and it turned out that speed, focus, and keyboard shortcuts were big hits.
- In their next step; they decided to politely pass over the feedback from users who would not be disappointed if they could no longer use the product.
This batch of not disappointed users should not impact your product strategy in any way. They’ll request distracting features, present ill-fitting use cases and probably be very vocal, all before they churn out and leave you with a mangled, muddled roadmap.
- The only use group left was- the users who would be somewhat disappointed without your product. This group was segmented again as seen below.
- This allowed them to pinpoint the missing features that would turn them into happy users.
Step 3: Building the Roadmap Smartly
With a clear understanding of what users loved and what held them back, Superhuman crafted their product roadmap strategically.
Rahul says: If you only double down on what users love, your product/market fit score won’t increase. If you only address what holds users back, your competition will likely overtake you.
- To double down on what their very disappointed users loved, half of the roadmap was devoted to the themes: More Speed | More shortcuts | More automation | More design flourishes
- To gain ground with their speed-loving-yet-somewhat-disappointed users, the other half of the roadmap was focused here: Mobile app | Adding integrations | Enhancing attachment handling etc.
To increase your product/market fit score, spend half your time doubling down on what users already love and the other half on addressing what’s holding others back.
Step 4: Measuring and Improving Continuously
Superhuman didn’t stop there. They continuously surveyed new users, tracking their product/market fit score closely. They made it their most important metric, setting OKRs around it to ensure constant improvement. Their efforts paid off, and within a short time, their product/market fit score almost doubled (From 33% -> 58% in 3 quarters).
Infact, SuperHuman has also open-sourced the Template for measuring PMF and designing the product roadmap to optimize this all-important metric.
And exposed a Build your own PMF engine as well!
Alright, folks, here’s the deal; these visionary founders have put in some serious hustle to create these fundamental frameworks. And you know what? Just by taking those frameworks, applying them, and giving them your personal touch, you can set yourself up for success!
Do check out the PMF YouTube video by the man himself!
I’m a product manager myself, and I know how hard it can be to find good resources on Product. That’s why I started writing this blog.
I hope you found this article helpful. If you are as energised as I’m after discovering this gem of a framework, do apply it and share your experience in the comments. And if you’d like to stay up-to-date on my latest articles, please follow me.
See you in the next one 👀
Happy PM-ing! 🚀
