Raving fans. Photo by anna-m. w.: https://www.pexels.com/photo/people-enjoying-the-concert-1047442/
How to use product/market fit to learn from and grow your product’s user base from a few die-hard customers to a viable business
Regardless whether you manage product for a startup, B2B, or a Legacy Enterprise, you’ll ultimately come up against the same two challenges:
- Who really are your users, and why do they love you?
- For those who don’t yet love your product, what can you do to win them over?
Rahul Vohra, in the course of building his Superhuman email application, found the key to both questions in the idea of product/market fit.
Product/Market Fit — A fuzzy, lagging success concept
The concept of product/market fit (“PMF”) has been around for years, but previous definitions were all some form of squishy “you’ll know it when you see it.”
Case in point: Marc Andreesen defined product/market fit back in 2007 like this:
“And you can always feel product/market fit when it’s 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…”
Marc Andreesen, The only thing that matters
While many founders have tried to crack the code of achieving product/market fit, Andreesen’s orginal definition, while inspiring, seemed more a series of signs it was happening than a way to achieve it.
Superhuman refining their ideal end-user
Rahul Vohra and his team had worked for two years to build their Superhuman email application, yet still didn’t feel ready to launch.
Vohra had a small pool of beta users, but couldn’t bring himself to launch it more broadly, wanting to get things “right” first.
He knew he needed a way to reduce the risk of launching his application, fine-tuning his “Where to Play” and “How to Win” choices to provide the radically differentiated email experience his target customer was seeking.
While he knew he was on the right track with product/market fit, Vohra struggled with the concept because he needed a way to better define and measure PMF.
He found the missing key in the pioneering work of Sean Ellis.
Measuring Product/Market Fit
Ellis, who had run growth for Dropbox, LogMeIn, and Eventbrite, had become obsessed with an idea that had intrigued him:
“What if you could measure Product-Market Fit?”
After much trial and error, Ellis came up with this flash of insight:
“Ellis had found a leading indicator: just ask users “how would you feel if you could no longer use the product?” and measure the percent who answer “very disappointed.”
Rahul Vohra, How Superhuman Built an Engine to Find Product Market Fit
The Product/Market Fit Benchmark
And what was the “magic” benchmark to insure Product-Market Fit viability?
In Sean Ellis’ own words:
“In my experience, achieving product/market fit requires at least 40% of users saying they would be “very disappointed” without your product. Admittedly this threshold is a bit arbitrary, but I defined it after comparing results across nearly 100 startups. Those that struggle for traction are always under 40%, while most that gain strong traction exceed 40%.”
Sean Ellis, “The Startup Pyramid”
So now Vohra finally had both a way to measure PMF, and a benchmark to hit — 40%.
Making a “Superhuman” email application
Vohra now surveyed his small group of beta users, and saw that only 22% would be “very disappointed” without his fledgling “Superhuman” app.
“With only 22% opting for the “very disappointed” answer, it was clear that Superhuman had not reached product/market fit. And while this result may seem disheartening, I was instead energized. I had a tool to explain our situation to the team and — most excitingly — a plan to boost our product/market fit.”
Rahul Vohra, How Superhuman Built an Engine to Find Product Market Fit
With the knowledge he’d gained, Vohra created a 4-step plan:
- Segment to find your supporters and paint a picture of your high-expectation customers
- Analyze feedback to convert on-the-fence users into fanatics.
- Build your roadmap by doubling down on what users love and addressing what holds others back.
- Repeat the process and make the product/market fit score the most important metric.
And started down the path towards product/market fit.
1. Segment to find your supporters and paint a picture of your high-expectation customers.
Vohra and his team assigned four different personas to the 22% of people who would be “very disappointed” without his email app.
Eliminating all but those four personas, they now accounted for 32% of people in the “very disappointed” group.
Not yet at 40%, but closer, and he had a better idea of who he was trying to reach.
The High-Expectation Customer Framework Sharpens Superhuman’s “Where to Play” Choice
Vohra now turned to Julie Supan’s high-expectation (“HXC”) customer framework to identify the persona who could both benefit the most from the product, and be vocal in spreading the word.
“In my view, 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.”
Rahul Vohra, How Superhuman Built an Engine to Find Product Market Fit
Through analyzing Superhuman’s happiest users’ answer to who they felt would most benefit from the product, they created a clear picture of their high-expectation customer:
A hard- and long-working professional who spends most of their day in their email app and likes to be seen as responsive to the many people with whom they communicate.
The power of a clear “Where to Play”
Vohra understood and continued to narrow his strategic choices to niche down his product’s focus.
Now that he knew for whom he was building Superhuman, (essentially, his “Where to Play”), he and his team need to continue to optimize their product (refine their “How to Win” choices) to only front-load adding functionality Superhuman’s small, passionate group of users cared most about.
2. Analyze feedback to convert on-the-fence users into fanatics.
For the next phase, Vohra wanted to understand the answers to two key questions:
- Why do people love the product?
- What holds people back from loving the product?
Vohra went back and reviewed answers to the question “What is the main benefit you receive from Superhuman?” based on which group they were in:
- Not disappointed at all
- Somewhat disappointed
- Very disappointed
Understanding what your die-hard users value
In digging into the data, Vohra and his team discovered that users who loved Superhuman focused on its speed, focus, and keyboard shortcuts.
And ignoring those who don’t
Importantly, Vohra specifically decided to ignore feedback from users who wouldn’t be disappointed to 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. As surprising or painful as it may seem, don’t act on their feedback — it will lead you astray on your quest for product/market fit.”
Rahul Vohra, How Superhuman Built an Engine to Find Product Market Fit
The exact opposite of most product roadmaps
Many product leaders are driven to focus on broad, immediate growth at all costs, trying to win over as wide a user base as possible by stuffing a wide array of “me-too” features in their products.
While Vohra’s choice to seems radical and counterintuitive, there’s solid data to back up his instincts here.
The ROI of focusing on users who are close to loving your product
We can draw a direct connection to my earlier piece linking Ben Foster’s Product Strategy mental model to Dan and Chip Heath’s insight from Forrester.
The goal isn’t to try to get “0’s” — people who don’t like your product– to “4’s.” There’s hard data behind the insight that you’ll get a 9X return when you focus on getting your “4’s” — people already close to loving your product–to “7’s” — die-hard fans.
The need for speed
Vohra and his team next focused on those who would be somewhat disappointed without the product, but only for whom speed was their highest priority.
In this way, Vohra was matching his product’s primary “How to Win” differentiator — Speed — with “on the fence” users who most valued that feature.
Now they paid special care to this group’s answer to the question
“How can we improve Superhuman for you?”
Recasting the roadmap
Vohra had originally made the decision to focus on the desktop app first.
But the feedback from these somewhat disappointed users made it clear the lack of a mobile app was a major barrier to getting them to fully embrace Superhuman.
This led Vohra and his team to completely revisit their roadmap from a new perspective, given how important these “somewhat disappointed” users valued not just mobile, but other missing functionality like integrations, calendaring and search, among other features.
Vohra hypothesized that shifting his roadmap with this feedback would allow them to turn their “somewhat disappointed” users into devoted fans.
3. Build your roadmap by doubling down on what users love and addressing what holds others back.
With the knowledge he’d gained, Vohra’s main challenge was now figuring out how to balance improving what users loved about the product and adding what was holding others back.
Vohra’s realization:
“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.”
Rahul Vohra, How Superhuman Built an Engine to Find Product Market Fit
To address his devoted user fanbase, Vohra and his team specifically added the following features to the roadmap:
- More speed
- More shortcuts
- More automation
- More small interface “delighters”
To win over the ambivalent, “somewhat disappointed” users, Vohra added these features to their roadmap:
- Developing a mobile app.
- Adding integrations.
- Improving attachment handling.
- Introducing calendaring features.
- etc…
Vohra and his team stack-ranked, and started building out features in order of highest-impact and lowest effort first.
Seeing these features become available, Vohra believed, would begin leading to a lift in their product/market fit score among their chosen personas.
4. Repeat the process and make the product/market fit score the most important metric.
Vohra and his team doubled-down and repeated their survey process.
They even created an OKR with only a single Key Result: the PMF percentage of users who would be “very disappointed” to not have their app.
And they measured it continuously–weekly, monthly, and quarterly.
The power of focus
What’s amazing is just how quickly this process paid off for Superhuman:
“Within just three quarters of our work to improve the product, the score nearly doubled to 58%.”
Rahul Vohra, How Superhuman Built an Engine to Find Product Market Fit
(Note that Superhuman’s 58% PMF bested even Slack, which had previously hit an industry-leading 51% PMF score, and led directly to their IPO and broad success.)
I’ve coached teams that have iterated on the same set of features for over two years, and continued to report lackluster client satisfaction.
The fact that Vohra and his team managed to accomplish this over just 9 months, after being in limbo for two years, is nothing short of astonishing.
Product/Market Fit first. Growth second. Always.
Product/Market Fit is the key to the elusive user growth that can build and sustain a business over the long term.
But many organizations make the mistake of driving for growth before adequately addressing their users’ needs.
Pushing for growth too early, before achieving a solid benchmark of user satisfaction will only create a “leaky bucket.” Users may sign up, but they’ll quickly drop out when it becomes clear their needs haven’t been addressed, not to return anytime soon.
Working with and optimizing for the product/market fit score can be a great way to make sure your product is ready to scale for sustainable growth.
The size of your organization doesn’t matter
This isn’t just important for startups — many large, legacy enterprises have been traditionally more internal-stakeholder or sales-oriented in their focus.
Vohra’s product/market fit engine can help enterprise product managers better understand their client personas and their unique needs, building their feedback into their roadmaps, and lead to better client experiences and user growth.
This ties closely to the other consideration noted above that many roadmaps are littered with features requested by users who will never become die-hard fans.
First and foremost, focus on prioritizing the feature decisions of your users who are close to loving your product.
Implications for investors — internal & external
VCs investing in startups, as well as executives overseeing products and Value Streams within their organizations, shouldn’t push too quickly for growth, and encourage their teams closest to their users to adopt the product/market fit engine.
And remember– without constant vigilance and great client-centric product management decisions, if you’re not taking care of your users who are close to loving your product, someone else will be, and will take both them, as well as your die-hard-fans, over time.
One note
The one observation I have of the Superhuman team’s process is they seemed to rely heavily on survey (Quantitative) data.
It might have been interesting to see how much of an impact adding continuous user interviewing, along the lines of Teresa Torres’ Continuous Discovery Habits process to provide some Qualitative data to their mix.
In any case, you can’t argue with Superhuman’s current success and results.
TL;dr
Increase the product/market fit of any service by:
- Surveying Users
- Segmenting supporters, identifying both your current biggest fans, as well as those who could be supporters
- Making Strategic Choices around whose needs you’ll address and when over your roadmap you’ll tackle them between improving features they already love and adding missing features they’ll need to love you more
to create great client experiences and continuously grow your user base.
Try the Product-Market Fit Engine yourself
Rahul Vohra has generously provided his “PMF Engine” as a really helpful Coda.io doc with sample data product managers can duplicate and use freely for their own products here.