Again We Found a Reputation of the Initial

This article is past Rahul Vohra , the founder and CEO of Superhuman — a startup edifice the fastest electronic mail experience in the world.

Nosotros've all heard that production/market fit drives startup success — and that the lack thereof is what'southward lurking behind almost every failure.

For founders, achieving product/market fit is an obsession from day 1. Information technology'southward both the hefty hurdle we're racing to clear and the festering fearfulness keeping us upwardly at nighttime, worried that nosotros'll never make information technology. But when it comes to agreement what product/market fit actually is and how to get there, most of us quickly realize that there isn't a battle-tested approach.

In the summertime of 2017, I was waist-deep in my search for a mode to observe product/market fit for my startup, Superhuman. Turning to the archetype web log posts and seminal thought pieces, a few observations stuck out to me. Y Combinator founder Paul Graham described product/market fit as when yous've made something that people want, while Sam Altman characterized it as when users spontaneously tell other people to use your product. But of course, the most cited description comes from this passage in Marc Andreessen'south 2007 blog mail service:

"You can always feel when product/market fit is not happening. The customers aren't quite getting value out of the production, 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 yous can ever feel production/market fit when information technology is happening. The customers are buying the production merely as fast as yous can make it — or usage is growing just equally fast as you can add more servers. Money from customers is piling upwardly in your visitor checking account. You're hiring sales and customer support staff as fast every bit you tin. Reporters are calling because they've heard about your hot new thing and they want to talk to you about information technology. Yous start getting entrepreneur of the year awards from Harvard Business School. Investment bankers are staking out your firm."

For me, this was the about vivid definition — and one that I stared at through tears.

We had fix shop and started coding Superhuman in 2015. A year afterward, our squad had grown to seven and we were all the same furiously coding. By the summer of 2017, nosotros had reached 14 people — and we were even so coding. I felt intense pressure to launch, from the team and likewise from inside myself. My previous startup, Rapportive, had launched, scaled and been acquired by LinkedIn in less time. Yet here nosotros were, two years in, and we had not passed go.

Only no matter how intense the pressure, I wasn't gear up to launch. Common practise would exist to "throw it out at that place and see what sticks," which may be fine after a few months of effort when the sunk toll is low. Merely the "launch and see what happens" method seemed irresponsible and reckless to me — particularly given the years that that we had invested.

Superhuman founder and CEO Rahul Vohra

Further compounding the pressure level, as a founder, I couldn't just tell the squad how I felt. These super-ambitious engineers had poured their hearts and souls into the product. I had no fashion of telling the squad we weren't set, and worse yet, no strategy for getting out of the state of affairs — which is not something they would want to hear. I wanted to find the correct language or framework to articulate our current position and convey the side by side steps that would get united states of america to product/market place fit, but was struggling to do so.

That's because the descriptions of product/market fit I plant were immensely helpful for companies post-launch. If, afterward launch, revenue isn't growing, raising money is tough, the press doesn't want to talk to you and user growth is anemic, then you can safely conclude you don't take product/market fit. Merely in practise, because of my previous success equally a founder, we didn't have problems raising money. We could have gotten press, just we were actively avoiding it. And user growth wasn't happening because we deliberately choosing not to onboard more users. We were pre-launch — and nosotros didn't have any indicators to clearly illustrate our state of affairs.

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 encephalon for an answer on how to travel the distance between where Superhuman was and the high bar that we needed to striking. And I eventually started to wonder: what if you lot could measure product/marketplace fit? Considering if you could mensurate product/market fit, and so maybe you lot could optimize it. And then maybe yous could systematically increase product/market fit until you achieved information technology.

Reoriented around this purpose and reinvigorated past the new direction, I set out to reverse engineer a process for getting to product/market fit. Below, I outline the findings that followed, specifically unpacking the clarifying metric that made everything fall into place and the four-step procedure we used to build an engine that propelled Superhuman forwards on the path to finding our fit.

ANCHORING AROUND A METRIC: A LEADING INDICATOR FOR Production/Market FIT

On my quest to sympathise product/market fit, I read all I could and spoke with every expert I could find. Everything inverse when I found Sean Ellis, who ran early early on growth in the early on days of Dropbox, LogMeIn, and Eventbrite and later coined the term "growth hacker."

The product/market place fit definitions I had establish were bright and compelling, but they were lagging indicators — by the time investment bankers are staking out your house, you already take product/market fit. Instead, Ellis had found a leading indicator: only ask users "how would you feel if yous could no longer use the product?" and mensurate the percent who answer "very disappointed."

Later on benchmarking virtually a hundred startups with his customer development survey, Ellis plant that the magic number was 40%. Companies that struggled to discover growth about e'er had less than 40% of users respond "very disappointed," whereas companies with strong traction almost always exceeded that threshold.

Ask your users how they'd feel if they could no longer employ your product. The group that answers 'very disappointed' will unlock production/market fit.

A helpful example comes from Hiten Shah, who posed Ellis' question to 731 Slack users in a 2022 open enquiry project. 51% of these users responded that they would be very disappointed without Slack, revealing that the product had indeed reached product/marketplace fit when it had effectually half a meg paying users. Today, this isn't too surprising, given Slack'due south legendary success story. Truly, this example shows simply how hard it is to shell the forty% benchmark.

Inspired by this arroyo, we set out to measure out what the responses would exist for Superhuman. We identified users who recently experienced the core of our product, following Ellis' recommendation to focus on those who used the production at least twice in the last two weeks. (At the time we had betwixt 100 and 200 users to poll, but smaller, earlier-phase startups shouldn't shy abroad from this tactic — yous start to get directionally correct results around 40 respondents, which is much less than nearly people recollect.)

We and so emailed these users a link to a Typeform survey request the following four questions:

ane. How would you lot experience if yous could no longer apply Superhuman? A) Very disappointed B) Somewhat disappointed C) Not disappointed

2. What blazon of people do you retrieve would most benefit from Superhuman?

3. What is the primary benefit yous receive from Superhuman?

4. How tin can we better Superhuman for you?

With the responses collected, we analyzed the first question:

With but 22% opting for the "very disappointed" respond, it was clear that Superhuman had not reached product/market fit. And while this upshot may seem disheartening, I was instead energized. I had a tool to explain our situation to the team and — most excitingly — a programme to boost our product/market place fit

FROM BENCHMARK TO ENGINE: THE 4-Pace MANUAL FOR OPTIMIZING PRODUCT/MARKET FIT

Determined to move the needle, I became singularly focused on means to meliorate our product/market fit score. The responses to each survey question would be key ingredients in what became the framework for fulfilling our goal.

Here are the four components that comprised our product/market place fit engine:

1) Segment to find your supporters and paint a pic of your loftier-expectation customers.

With your early marketing, you lot may have attracted all kinds of users — especially if y'all've had press and your production is free in some fashion. Simply many of those people won't be well-qualified; they don't have a real demand for your production and its main benefit or employ case might not be a great fit. You wouldn't have wanted these folks as users anyway.

As an early-stage team, you could just narrow the market with preconceived notions of who you call up the product is for, just that won't teach you lot anything new. If yous instead use the "very disappointed" group of survey respondents as a lens to narrow the market place, the information can speak for itself — and you may even uncover unlike markets where your production resonates very strongly.

For me, the goal of segmenting was to find pockets in which Superhuman might take amend product/market fit, those areas I may have disregarded or didn't remember to scope down to.

To outset, we grouped the survey responses by their answer to the first question ("How would you feel if you could no longer use Superhuman?"):

We and then assigned a persona to each person who filled out a survey.

Next, nosotros looked at the personas that appeared in the very disappointed group — the 22% that were our biggest supporters — and used those to narrow the market. In this simplified example, yous can see we focused on founders, managers, executives and business evolution  — temporarily ignoring all other personas.

With this more than segmented view of our data, the numbers shifted. By segmenting down to the very disappointed grouping that loved our product well-nigh, our product/market fit score jumped by 10%. We weren't quite at that coveted twoscore% yet, just nosotros were a lot closer with minimal endeavour.

To go even deeper, I wanted to better understand these users who really loved our product. I hoped to paint every bit vivid a picture of them every bit possible, then I could galvanize the whole team to serve them better.

I turned to Julie Supan's loftier-expectation customer framework as a tool to practise just that. Supan notes that the loftier-expectation customer (HXC) isn't an all encompassing persona, but rather the near discerning person within your target demographic. Nearly importantly, they volition savor your product for its greatest do good 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'south work safe.

With this in mind, I sought to pinpoint Superhuman's HXC. Nosotros took only users who would be very disappointed without our product and analyzed their responses to the second question in our survey: "What type of people practice you call back would virtually do good from Superhuman?"

This is a very powerful question, equally happy users volition near e'er describe themselves, not other people, using the words that matter about to them. This lets you know who the production is working for and the language that resonates with them (providing valuable kernels of insight for your marketing copy as well).

Using our customers' words and Supan's tips for edifice a profile, we crafted a rich and detailed vision of the Superhuman HXC:

Nicole is a difficult-working professional who deals with many people. For example, she may be an executive, founder, manager, or in concern evolution. Nicole works long hours, and often into the weekend. She considers herself very busy, and wishes she had more time. Nicole feels every bit though she'south productive, only she's self-aware enough to realize she could be meliorate and will occasionally investigate ways to ameliorate. She spends much of her piece of work solar day in her inbox, reading 100–200 emails and sending fifteen–forty on a typically 24-hour interval (and equally many every bit 80 on a very busy one).

Nicole considers it part of her job to be responsive, and she prides herself on beingness so. She knows that being unresponsive could block her team, damage her reputation, or cause missed opportunities. She aims to go to Inbox Zero, merely gets there at virtually 2 or three times a week. Very occasionally  —  perhaps once a yr  —  she'll declare email bankruptcy. She generally has a growth mindset. While she'south open up-minded about new products and keeps up to date with technology, she may have a fixed mindset about email. Whilst open to new clients, she'due south skeptical that one could make her faster.

With our HXC in mind, we had a tool to focus the entire company on serving that narrow segment meliorate than everyone else. Some may find this approach also limiting, arguing that you shouldn't narrow in on such a specific customer base of operations early on.

It's a normally held view that tailoring the production likewise narrowly to a smaller target market place means that growth volition hit a ceiling — but I don't think that's the case.

These words of wisdom from Paul Graham explicate why:

"When a startup launches, there have to be at least some users who really need what they're making — non only people who could see themselves using information technology one twenty-four hour period, simply who want it urgently. Usually this initial group of users is small, for the simple reason that if there were something that large numbers of people urgently needed and that could exist congenital with the corporeality of effort a startup usually puts into a version i, it would probably already exist. Which means yous accept to compromise on 1 dimension: you can either build something a large number of people want a small corporeality, or something a small number of people want a large amount. Choose the latter. Not all ideas of that type are adept startup ideas, only nigh all skilful startup ideas are of that type."

In a separate post, he drives this signal dwelling house fifty-fifty further:

"In theory this sort of hill-climbing could get a startup into problem. They could end up on a local maximum. But in practice that never happens. … The maxima in the space of startup ideas are not spiky and isolated. Most fairly good ideas are adjacent to even ameliorate ones."

In essence, information technology's better to make something that a small number of people desire a large amount, rather than a product that a large number of people desire a small amount. In my view, the product/marketplace fit engine process of narrowing the market place massively optimizes for a production that a pocket-sized number of people want a big corporeality.

2) Analyze feedback to convert on-the-argue users into fanatics.

Still, just winnowing downward to HXCs is not plenty. We had gone narrow, simply now needed to dig deeper. Since nosotros were below the forty% threshold, we needed to effigy out why this smaller subset actually loved Superhuman — and how we could bump upward more than users into this segment.

To go to the root of how we were going to improve the production and aggrandize the depth of its appeal, I found it helpful to focus my efforts on these central questions:

Why do people honey the product?

What holds people dorsum from loving the product?

To understand why users loved Superhuman, we one time over again turned to the segment of those who would be very disappointed without our product. This time, nosotros looked at their answers to the third question on our survey: "What is the chief benefit you receive from Superhuman?"

Hither's a sample of some answers that stood out:

"Processing email is much faster with Superhuman for two reasons: show one email at a time and overall speed is much better than gmail. I go through my inbox in one-half the time."

"Speed! The app is crazy fast, and the UX + keyboard shortcuts make me an actual superhuman."

"Using Superhuman is so much faster than using Gmail. Non even close. And it mirrors my favorite Gmail shortcuts, and then there is zero learning curve for a ability Gmailer."

"I can work through incoming email more speedily, sorting messages accordingly and streamlining my work process."

"Speed. Aesthetics. I tin do everything from the keyboard."

"Speed and the corking set of keyboard shortcuts. I rarely, if ever, accept to utilize the trackpad."

After throwing the responses into a word cloud, some common themes emerged: the users who loved our production most appreciated Superhuman for its speed, focus and keyboard shortcuts.

With this deeper understanding of the product's appeal, we turned our attention to figuring out how we could assistance more than people love Superhuman.

Our next pace was somewhat counterintuitive: we decided to politely pass over the feedback from users who would not be disappointed if they could no longer utilise the product.

This batch of not disappointed users should not impact your production strategy in any fashion. They'll asking 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 deed on their feedback — it volition lead you astray on your quest for product/market fit.

Politely condone those who would non be disappointed without your product. They are then far from loving you that they are substantially a lost cause.

That leaves the users who would be somewhat disappointed without your production. On the 1 hand, the 'somewhat' indicates an opening. The seed of attraction is there; mayhap with some tweaks you can convince them to fall in dear with your production. But on the other hand, it's entirely probable that some of these folks will never be very disappointed without your product no matter what you do.

To fine-melody who nosotros took our cues from, we segmented once again. From analyzing our tertiary survey question, we knew that happy Superhuman users enjoyed speed as their main benefit, and so we used this as a filter for the somewhat disappointed group:

Later on splitting the somewhat disappointed group into two new segments around speed, hither's how we decided to act on their feedback:

Somewhat disappointed users for whom speed was non the chief benefit: we opted to politely disregard them, as our principal do good did not resonate. Even if nosotros congenital everything they wanted, they would be unlikely to fall in beloved with the product.

Somewhat disappointed users for whom speed was the main do good: nosotros paid very close attending to this group, because our master benefit did resonate. Something  —  probably something small  —  held them back.

Focusing on this concluding grouping, we looked more closely at their answers to the 4th question on our survey: "How can we improve Superhuman for yous?"

This is what we saw:

After some assay, nosotros found that the main affair property back our users was simple: our lack of a mobile app. In 2015, nosotros had taken the contrarian approach of starting with the desktop. Most emails are sent from desktop, so that'southward where we thought we could add most value. We were always planning on edifice a mobile app, just at the beginning of our journeying — like every startup — we had the fries for just one bet. In 2017, it was clear that we could no longer delay this, and that mobile had become critical for product/marketplace fit.

Probing further, we found some less obvious and more interesting requests: integrations, attachment treatment, calendaring, unified inbox, better search, read receipts and then on into the long tail. For example, as an early-stage company, internally nosotros weren't making heavy use of our calendar and we wouldn't have prioritized calendaring much at all based on our own intuitions almost email. Hence, this procedure of earthworks through feedback massively moved calendaring up on the product priorities list.

With a clear understanding of our main do good and the missing features, all we had to exercise was funnel these insights back into how we were edifice Superhuman. Implementing this segmented feedback would help the somewhat disappointed users get off the fence and movement into the territory of enthusiastic advocates.

3) Build your roadmap by doubling downwardly on what users dear and addressing what holds others back.

Fifty-fifty though we understood why users loved our product, and what held others back, information technology wasn't initially clear how nosotros were going to navigate the tension between the two when it came to committing to a production roadmap.

I eventually came to this realization: If you only double down on what users love, your product/market fit score won't increase. If yous only address what holds users back, your contest will likely overtake you. This insight guided our product planning process, effectively writing our roadmap for u.s.a..

To double downward on what our very disappointed users loved, half of our roadmap was devoted to the following themes:

More than speed. Superhuman was already extremely fast, but we worked to make it even faster. For case, the UI would respond within 100 ms, and search was faster than in Gmail. We pushed even further to response times of less than 50 ms, and worked to make search feel instantaneous.

More shortcuts. Users loved that they could do everything from the keyboard. So we made our shortcuts even more robust and comprehensive. We built shortcuts that no other email experience had and nosotros started pipelining keystrokes, ensuring that everything still worked even if you typed faster than your machine could handle.

More automation. Users really valued the power to be more efficient with their time. But we all hit the same limit: the sheer time it takes to type. So we congenital Snippets, a feature that lets users automatically type phrases, paragraphs, or whole emails. To save even more time, we made Snippets more robust, adding the ability to include attachments, automatically add together people to CC, and even integrate with a CRM and ATS.

More than design flourishes. In our feedback, we saw that users loved the blueprint and its many small details, and then we invested in hundreds of minor touches to show that we care. For example, typing "-->" now automatically turns into a right arrow: →.

To gain ground with our speed-loving-yet-somewhat-disappointed users, the other one-half of our roadmap was focused hither:

Developing a mobile app.

Adding integrations.

Improving attachment handling.

Introducing calendaring features.

Creating a unified inbox option.

Making search ameliorate.

Rolling out read receipts.

To stack-rank amongst these initiatives, we used a very simple cost-impact analysis: we labelled each potential projection as low/medium/high cost, and similarly low/medium/high impact. For the 2d half of the roadmap, addressing what held people dorsum, the affect was articulate from the number of requests any given comeback had. For the beginning half of the roadmap, doubling downwardly on what people love, we had to intuit the bear on. This is where "production instinct" comes in, and that'southward a function of experience and deeply empathizing with users. (The HXC profile practice from earlier helps a great deal with developing this muscle.)

With this programme of attack outlined, we got to work, starting with the lowest hanging fruit of low cost, high bear on work and so we could deliver improvements immediately.

To increase your product/market place fit score, spend half your time doubling downwards on what users already love and the other half on addressing what'due south holding others dorsum.

four) Repeat the process and make the product/market place fit score the nearly important metric.

As time went on, we constantly surveyed new users to track how our product/market fit score was changing. (We were conscientious to ensure that we didn't survey users more than once, and then as to not throw off the 40% benchmark.)

The percent of users who answered "very disappointed" speedily became our most important number. It was our most highly visible metric, and we tracked it on a weekly, monthly and quarterly basis. To make this easier to measure over time, nosotros built some custom tooling to constantly survey new users and update our aggregate numbers for each timeframe. We also refocused the product team, creating an OKR where the simply key result was the very disappointed percentage and then we could ensure that we continually increased our production/market fit.

Reorienting Superhuman around this unmarried metric paid off. When we started this journeying in the summertime of 2017, our product/market fit score was 22%. After segmenting to focus on the very disappointed set of users, we were at 33%. Within just three quarters of our piece of work to improve the product, the score near doubled to 58%.

And nosotros're not washed — the product/market fit score is something that we're going to continue to rails. I think it'due south ever useful for startups to look at this metric, because as you grow you'll encounter different kinds of users. Early adopters are more forgiving, and will enjoy your product's primary benefit despite its inevitable shortcomings. But as yous push beyond this group, users become much more demanding, requiring feature parity with their current products. Your product/market fit score may well drop as a result.

However, this shouldn't cause too much feet, as at that place are some ways around it. If your business has potent network effects (think Uber or Airbnb), then the core benefit volition continue getting meliorate as you abound. If you lot're a SaaS company like Superhuman, you simply have to go on on improving the production as the pool of users expands. To do that, nosotros rebuild our roadmap every quarter using this process, ensuring that nosotros're improving our production/market fit score fast enough.

BRACING FOR IMPACT

In the twists and turns of post-obit this process, I found a manner to define product/market fit and a metric to mensurate it. Our squad had a single number to rally around instead of an abstruse goal that left united states feeling hopeless. Past surveying our users, segmenting our supporters, learning what users loved and what held them back, and then dividing a roadmap betwixt the two, we found a methodology to increment product/market fit.

It is hard to enlarge the impact of this product/market fit engine on our company. Everything nosotros practice  at Superhuman —  from hiring to selling and marketing to raising capital  —  has become significantly easier. Our team has grown to 22 people and our NPS has increased right alongside our production/market fit score. Users became noticeably more vocal nearly how much they loved the production, both in our surveys and on social media. Current investors started request if they could put in more coin ahead of upcoming rounds while exterior investors continually inquire me if they tin invest.

Taking a step dorsum to reflect on what I've learned from building this product/market fit engine for Superhuman, I'yard left with two concluding takeaways:

Investors advising early-phase teams should avoid pushing for growth alee of production/market place fit. As an manufacture, we all know that this ends in disaster, yet the pressure for premature growth is still all besides common. Startups need time and infinite to discover their fit and launch the correct way.

For whatever founder looking to get out of the wilderness and on the path to the ever elusive product/market fit, I've been in your shoes — and I hope you'll consider retooling this engine in those proverbial startup garages to make it your ain. And when you lot finally hit the production/marketplace fit score you're targeting, my advice is to button the pedal all the way down and grow as fast as you can. It will feel uncomfortable, but y'all'll have the testify you demand to know that you'll succeed.

If you would like to attempt this engine for yourself, checkout this interactive tool, with a sample of actual Superhuman results. You can see the give-and-take clouds change as you play effectually with it — and you tin can also put in your ain information and use it to build your ain production.

Image by DNY59 / Getty Images. Photograph and charts courtesy of Rahul Vohra.

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Source: https://review.firstround.com/how-superhuman-built-an-engine-to-find-product-market-fit

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