Finding product market fit is the foundation for growth and critical milestone for venture backed businesses when raising money, as well as for the venture capitalists themselves when investing.
Founders rightly focus on achieving revenue targets or growth outcomes as a key deliverable or a measure of their startup success. Whilst this is important, alongside this is the journey of discovery, to turn an idea into a product, to find and build business that endures. To achieve this, they need to find product-market fit, and would need to demonstrate the process by which that was achieved.
There is no map for this journey, every company is different as well as the path they will follow. Nevertheless, what we have found useful is to think of the progression of revenue growth and product market fit as a simple mental model, with revenue on the vertical axis and product-market fit on the horizontal, both improving as the company grows.
We apply this framework to our portfolio as a whole when undertaking our internal benchmarking and considering our capital allocation decisions and many of our portfolio companies have found it useful.
Rocket science it is not.
We simply encourage our companies to consider their progress on these two axes, considering progress on each equally important.
This is a wickedly complex problem to solve, with a poorly defined process, masses of signals and no rigid rules. Despite what follows – a set of different models in logical order – it is far from linear or straightforward. VC Investor Brad Feld defines this well:
Every time you work on something new… recognize that you are searching for incremental product/market fit. The search is a continuous and never ending quest.
Everyone’s journey is different and great founders understand everything is also an experiment. Chris Tottman, Founder, Investor and Notion Partner puts this far better than me:
People talk a lot about conviction-led founders, who believe the world should work differently and are crazy enough to enter the fray and take that idea to market, building a proposition, and never giving up.
But the greatest founders are also self-aware enough to realise their original idea is limited – it’s an alpha, an hypothesis. It’s under-informed, it needs to be market tested.
Starting from the beginning, which seems like a good place, there are five steps to follow:
- Solving a problem worth solving
- Building an MVP
- Finding product-market fit: user driven, buyer driven, company driven.
- Establishing underlying capital efficiency
- Establishing the market size
1. Are you solving a problem worth solving?
This is a story that starts with pain.
In B2B tech, start ups are born of pain. They centre themselves around an industry problem that simply won’t go away and they pivot around that pain. If that pain is sufficiently acute, it will inevitably drive adoption at scale as the industry moves from an old way of doing business to a new way.
For Jos White, Notion Partner, this is a fundamental part of his investment philosophy.
I look for founders who combine an insider’s knowledge of an industry with an outsider’s perspective – they see something that is broken, inefficient, or just plain wrong and have a burning desire for the world to conform to their way of thinking.” Jos White.
There is a simple narrative that drives the very earliest of stages in a business; three questions constantly nagging at the back of a founders mind:
- Problem: What problem do we solve?
- Customers: Who will we solve it for?
- Impact: How will it change their world?
And they return to these questions over and over:
“Is this the most important problem? Are these the best customers? Is this most value?” Narrowing in on the answer.
Founders must seek to satisfy themselves they have indeed identified a problem worth solving, they know the very best customers and are confident they can deliver enormous value. But more importantly they can look themselves in the mirror and say “Yes, this is worth putting my life on the line for – over the next ten years – to build a massive company”.
“The best startups generally begin by trying to address a really important problem worth solving. If they can nail the solution to this important problem, they have a great chance of building a successful startup”. Growth Hacking Specialist, Sean Ellis
Research only corroborates the need for stat-ups to address a problem worth solving. CB Insights analysed 101 start-up post mortems and explored the top reasons startups fail – not addressing a big enough problem ranked 1st for 42% of startups.
2. Creating the minimal viable product (MVP)
With the burning problem in mind, our attention turns to establishing the MVP (minimum viable product). The process of Customer Discovery, as described in Steve Blank’s excellent Four Steps to the Epiphany, has guided many through this stage using structured customer interviews.
Undertake customer discovery
To paraphrase this approach, we recommend founders to:
- Turn their problem hypothesis into a series of problem statements, three to five different interpretations of the problem they are looking to solve;
- Turn their value hypothesis into a series of three to five impact statements, highlighting the impact they hope to deliver; and
- Establish a target list of customers, 100+ individuals within target segments, covering a number of different personas and customer types.
The next step is to substantiate these assumptions/impressions through customer discovery interviews. You may ask interviewees to rank the problem and impact statements 1-5, or preferably ask them to pick the most important and least important (the max-diff approach) and then use their answers/feedback to adjust your MVP and your initial customer targets.
At this stage you should also be exploring willingness to pay. Four simple questions will be very revealing:
- At what price is this so cheap, that you’d rip my arm off?
- At what price is this so high, that you’d laugh me out of the door?
- At what price is this a little too expensive?
- At what price is this a little too cheap?
This may be an on-off exercise, but more likely will be a process you will return to frequently. You can learn more here, or of course just read the book. This is a simple exercise in putting problems and customers at the heart and start of your startup journey. It will help you to narrow your focus, and if done well serves as an excellent resource for initial pipeline development.
A Case Study
Hazy, a Notion-backed company, went through a similar process following investment in mid 2018.
“Nailing product market fit is critical and it’s something I had to learn from scratch. The Notion team were instrumental in guiding us through the process and helped measurably accelerate our development.” Co-founder & CEO of Hazy, Harry Keen.
|Customer Validation Case Study featuring Hazy
Hazy, a London based AI startup, conducted a customer validation project to understand three simple things:
- What was their customer’s burning problem?
- What solution should they offer to best solve that problem?
- Who was the solution ideally suited to?
Through some surface-level conversations and personal intuition, they hypothesized that there were three main problems in the data science space they were ideally placed to address:
- It’s difficult to share private or sensitive data confidentially
- It’s difficult to generate good quality test data
- It’s difficult to unlock trapped data
To test the severity of these problems, Hazy interviewed 100+ potential buyers and users, ranging from c-level, down to individual contributors, from a range of pre-defined organisations and sectors.
They reached senior executives through warm intros from investors, cold calling, LinkedIn messaging and networking
- Hazy placed an emphasis on making it clear to the companies that it was an inquisitive outreach and not a sales pitch
- They navigated interviews by understanding companies’ pain points and allowing conversations to flow from there, whilst honing in on certain topics when necessary
The entire customer validation process was 3 months
The responses in these interviews can be summed up simply: Unlocking the value of customer data is a burning problem, especially for mature and technologically advanced companies. The other problems? Not so much.
During the questioning process, Hazy also discussed their idea of three possible solutions:
- A secure data sharing platform
- A “dumb” test data generation tool and/or
- A synthetic data generator tool
The results indicated that the possible capabilities of a synthetic data tool were by far the most sought after solution to solve the problem of unlocking data safely for advanced data science applications.
Prospective customers are more mature, technically advanced companies with sensitive, illiquid data who want to innovate with their data as a competitive advantage.
3.Finding product-market fit: user driver, buyer driven, company driven.
As your startup acquires more customers, the next step is to move beyond the MVP and start the never ending quest for product-market fit (PMF).
Serial Entrepreneur, Founder, Partner & Investor at Adreessen Horowitz,.Marc Andreesen first coined this phrase:
“Product/market fit means being in a good market with a product that can satisfy that market.”
Finding product market fit is a creative and iterative process that requires entrepreneurs to be nimble with their value propositions, agile with their products and receptive to feedback that validates or refutes their assumptions. A quote often attributed to Mark Twain puts it well:
It ain’t what you don’t know that gets you into trouble, it’s what you know for sure that just ain’t so.
Our firmly held beliefs about what is and isn’t so, can get us into trouble and stop us from seeing what is right in front of us. At times our hypothesis simply doesn’t stand up, our explanation of the value is incomplete, the value we create is insufficient and our customers’ choices are just plain wrong. We need to have open minds and treat success and failure with equal importance.
There are many ways to find product-market fit, but below we have outlined three different yet complementary ways to think about this challenge, combining data driven, objective and subjective approaches. One, two or all three may be relevant, however, there are many other signals and sources of data you might consider that we won’t cover here such as product engagement data, market data, competitive analysis and so on.
However, one thing is clear. We learn by doing, which means customers must be acquired in order to gain feedback, placing small bets on target customers. Jim Collins calls this “firing bullets”, low cost small experiments and see what happens.
User-Generated Product-Market Fit: empirical and data driven.
A good starting point to establish user generated PMF is gathering empirical evidence from users, as described in the Sean Ellis Test
In order for this test to work, the company must be executing a customer acquisition strategy of sufficient scale to generate the insights required.
In B2B and enterprise tech, finding product market fit requires getting “uncomfortably narrow” – it may feel counterintuitive to some founders, but at an early stage the paradox of customer choice is that more is less. Chris Tottman puts this well:
At Notion, we are a big believer in an uncomfortably narrow definition of pain, use case and form factor which enables our companies focus at an early stage. Its extraordinary how fast this mental model can accelerate success.
But before we can get narrow, we have to go reasonably wide and “shoot some bullets”.
The customer number may vary from 10-20 customers with large average contract values (for example $50,000 plus) to 100 or even 1,000 customers for smaller average contract values, but the user numbers need to ideally be 100+. Most statisticians agree that the minimum sample size to get any kind of meaningful result is 100. If your population is less than 100 then you need to survey all of them.
To conduct this user generated product-market fit test, Ellis recommends asking users the following question:
How would you feel if you could no longer use the product?
Then measure the percentage of participants who answered very disappointed, somewhat disappointed and, quite happy thank you!
After benchmarking nearly 100 startups, Ellis posited that the threshold for product market fit purposes was 40% i.e. 40+% of users respond with “very disappointed”.
One of the best examples of the application of this process is described by Rahul Vohra, Founder & CEO of Superhuman in his excellent article, “How Superhuman Built an Engine to Find Product/Market Fit”. Below we have summarised – and plagiarised – few pointers from Rahul’s. If you want the real deal, please do read the article it is – again – excellent.
Rahul built on top of the Sean Ellis test with four simple questions to help Superhuman achieve product-market fit:-
- How would you feel if you could no longer use our product/service?
- Very disappointed
- Somewhat disappointed
- Not disappointed
- What is the main benefit you receive and why is this so important to you?
- Who do you think would most benefit from our product and why?
- How can we improve our product for you?
Once you have completed the survey and have an aggregate score of PMF.
The first step Rahul describes is to then segment your customers to understand your supporters and detractors and to enable you to narrow your focus to your “High Expectation Customers”.
Use the data to understand who your product resonates with and why, by first developing personas to describe the respondents and then grouping the responses into the three categories of very, somewhat and not disappointed. This allows you to rapidly narrow your segmentation.
By identifying his “High Expectation Customers”, Rahul was able to identify his most discerning customers.
We have often discussed the importance of becoming “uncomfortably narrow” in your go to market strategy. Some companies may worry about limiting the size of their opportunity but 1) we all have finite resources – product or sales – and want those pointed at our best customers and 2) the problem of a ‘local maximum’ rarely occurs. Rather we recommend founders, go narrow and deep to build a big market.
It’s a commonly held view that tailoring the product too narrowly to a smaller target market means that growth will hit a ceiling — but I don’t think that’s the case. Rahul Vohra
- Obsess about the feedback and focus on turning your best customers into fanatics.
Some customers love the product, so how can you help them love it more and find more just like them. Some you need to ignore, but many will be on the fence and you need to understand if you can turn the fence sitters into fanatics.
CMO at SurveyMonkey, Leela Srinivasan summed this up perfectly at her Saastr 2019 talk:
Using feedback to create a virtuous customer acquisition cycle… is really about figuring out how to identify folks that can become your customer champions and create the right relationships with them such that they not only submit feedback… but they become your champions.
Understanding which users to double down on and which to ignore will be key to hitting that magic 40% number.
- Build a roadmap that doubles down on what users love and address what holds others back.
Superhuman used a very simple cost-impact analysis, labelling each potential project as low/medium/high cost, and similarly low/medium/high impact.
For the first half of the roadmap – doubling down on what people loved – they intuited the impact. For the second half of the roadmap – addressing what held people back – the impact was clear from the number of requests any given improvement had.
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.
And I would add, aligning a customer acquisition strategy to target new “High Expectation Customers”.
- Repeat, repeat and make listening to your customers central to your business.
Repeat the process and make the product/market fit score the most important metric.
Within just three quarters, Superhuman took their PMF score from 22% to 58%.
You can learn more about this approach from Rahul’s excellent article and more in Sean’s book, Growth Hacking.
B) Buyer-Generated PMF – objective data gathered from primary research or via the sales process
In B2B tech, the buyer is rarely the user and vice versa, so you ignore buyer behaviours at your peril. Buyer-generated PMF is shaped around learning the buyer’s needs and journey with the aim of understanding how to trigger those needs with your marketing efforts. As buyers become more self sufficient by gathering their own data and doing their own research, your sales and marketing efforts need to focus increasingly on ‘helping them to buy’.
This process involves a lot of inquisitive questioning with buyers, followed by some extensive internal assessment as to whether or not your product/service is meeting those needs.
Before questioning your buyers, do some research on who they are:
- Who is the organisation and what market are they in?
- Is the market mature? What’s the condition of the market? Etc.
- What are the characteristics of those buyers – their type, their size? Etc.
The first step is to get feedback from them around their buying process and overall experience with your product/service:
- Why did you buy?
- When did you know you had a need and how did you validate that?
- What was the trigger to initiate this process?
- Why did you choose us?
- Who or what else did you consider?
- How did you buy?
- Describe the process: how did you discover us, who or what influenced your decision, what content did you consume?
- What research did you do, what stages did you go through?
- Who else was involved?
- Would you recommend?
- If yes / no what would you say?
- Do you have any recommendations or introductions you would like to make?
At a later stage you can come back to explore some follow up questions such as: How did the solution deliver on the promise? What benefits did you receive? Etc.
Your intention here is to generate a behaviour model of prospective customers as well as useful insights on your buyers’ experiences with your product/service. This enables you to reshape your product/service accordingly whilst learning what their triggers are – ie. what brought them to you in the first place.
General Partner at Matrix Partners David Skok, wrote a great article on understanding buying triggers for B2B startups’ customers of which we’ve summarised below:
Firstly, David defines a trigger as the following:
A trigger is an event that causes a buyer to have a clear need, which usually converts into a sense of purpose and urgency in their buying process.
It goes without saying that buyer’s triggers will vary depending on the nature of your startup, your target market(s), as well as who you are targeting within these markets. However, having a general understanding of what your buyer’s triggers are is very useful, as it enables you to do the following:
- Recognise and hone in on your target prospects
- Improve messaging/marketing efforts to those target prospects
- Better qualify which prospects are ready to buy
As stated, buyer triggers will vary from customer to customer, therefore the key to determining these triggers is to:
- Split up your buyers into different personas
- Identify the trigger(s) that generally get buyers of that persona to buy
- Create targeted messaging and content for each persona
- Understand if you can artificially trigger the event or help them recognize if one has already occurred
Understanding buyer triggers itself is a repetitively inquisitive process. You are effectively shaping the way you promote your service/product in the most ideal way that attracts your target customers. We will dedicate a separate piece on modelling buyer intent.
Ryan Sorley, Founder and CEO of DoubleCheck Research, specialists in win/loss analysis shared this framework with us, which while more appropriate with later stage companies is a useful framework for guiding discussion. Ryan recommends win/loss analysis is completed within 30 days of signing a contract and preferably before implementation starts to get good unfiltered feedback.
Ryan also recommends this research can be completed and captured as a part of the sales process.
c) Company-generated PMF – subjective, perhaps intuitive, but most definitely informed by experience
Companies can bring their insights from users and buyers together with their perspective and knowledge to develop an evolving score, encompassing four key aspects of PMF, that directly inform your growth strategy.
- We know who our best customers and users are.
- We have a well defined ICP “ideal customer profile”
- More than 50% of customers are in this segment.
- We know why and how they buy
- We have a repeatable value proposition (that can be sold without the founders participation).
- We have a repeatable pricing model
- It is applied consistently across our ICP
- We have clear evidence and an upward trend that our solution delivers value that will cause our customers to renew and expand revenues
- This could be measured in many ways – customer satisfaction, usage, ROI, impact, retention, upsell, referrals, etc.
By assessing progress on each criteria, every quarter creates a simple picture of PMF progress .
We use a simple heuristic approach by scoring companies against these criteria on a scale of 0 to 5, with 5 being the best, in line with the descriptions above for example.
You could visualise this PMF Model as in the first section. Think of this as a mental model, not as a hard and fast rule.
Over 1-2 years we recommend start ups assess their PMF progression (from 0-100% complete) and contrast that with revenue growth.
There is a divergence of opinions as to what the optimal indicators of PMF are. Co-Founder & Partner at NextView Ventures Lee Hower:
“Arguably revenue is the best signal of product market fit for B2B startups… If a business is willing to pay something for your early product, even nominal or beta pricing, that’s a pretty healthy indicator the product has value in terms of features and functionality.”
At Notion, we believe revenue alone is not enough. We encourage our founders to consider the systematic mitigation of the risks associated with PMF alongside, and of equal importance as revenue performance.
“At the start up phase it’s all about identifying the pain, assembling the team and building a minimum viable product to address that pain. And remaining really focused on those to achieve product market fit, alongside your revenue goals. Without those it is difficult to establish the unit economics which are critical to the next fund raise.” Stephen Chandler, Managing Partner, Notion Capital
Which brings us neatly on to the next step.
4. Demonstrating the Capacity for Capital Efficient Growth
With more than $1-2m in recurring revenue and a solid PMF scores informed by user, buyer and company generated insights, the company is in good shape to invest for growth.
However, forcing your business to scale before achieving PMF can be catastrophic for your business. Founding Partner at NFX Ventures Gigi Levy-Weis quoted the following in his article on PMF:
If you try to scale before you hit product-market fit, you will experience the leaky bucket phenomenon. All that work you’ve done to bring people to your product will go to waste as they’ll just end up churning right out. So make sure you have it before you turn to scaling.
But in order to invest for growth you also need to be able to demonstrate capital efficient growth, or at the very least a credible path to that nirvana, backed up by some strong unit economics within the customer group for which you have product-market fit.
In Season 3, Episode 1 of the Notion Podcast, Jonathan Gale, Exec in Residence at Notion Capital and Former CEO at NewVoiceMedia, detailed the importance of capital efficiency as an outcome of PMF. A company may be growing fast, perhaps 10% MOM, Jonathan recommends founders strip away growth fueled purely by external investment and explore whether their business could grow at 30-50%+ YOY funded purely by the cash the company generates.
“This last point is critical because it talks to how capital efficient a business can be as it scales.
If a company can sustain 30-100% YOY growth in bookings, purely on the cash it generates from customers, then an injection of venture capital will greatly speed growth thereafter.” Jonathan Gale.
What Jonathan is describing is a business that can demonstrate:
- Payback on the Cost of Acquisition of less than 12 months (taking into account gross margin);
- Low customer churn, within the target group, of less than 5%; and
- Positive revenue expansion within the target customers, so they are not only, not churning, but actually growing their expenditure.
SaaS businesses are machines, they invest to acquire customers who stay with them year after year, spending more as they receive more value.
You need to be able to demonstrate that – even if you don’t have all the metrics today or perhaps they don’t quite stack up – you know how your machine works and how you plan to improve the underlying unit economic picture..
5. Validating the Target Addressable Market
Lastly, to be ready to invest for growth you also have to demonstrate that, while you have proven PMF in a small niche, that niche is adjacent to a large market that you can address over time.
Jonathan Gale again:
Another aspect of qualification is that the market in which the company has achieved fit in is sufficiently large that, ideally, you can demonstrate that you can build a business with revenues of $100m or $200m, but still with less than 1% of the market.
At this early stage, it is important that a business is targeting a small market segment or niche, but has a total addressable market this is sufficiently large to build a really big, enduring business.
Joe Floyd, General Partner at Emergence Capital explains,
Unicorns need ample room to run and that means startups have to target large enough market opportunities. For Emergence, we look for startups that have a near term $1+ billion revenue opportunity within the US.
Our intention is not to provide a playbook for product-market fit, to do so would obscure the fact that every company is unique and, as such, each journey will be different.
History does not allow us to predict the future, but it does provide lessons of past successes and failures we can learn from and provides context and analogies to solve complex problems and make better decisions.
Our experiences as SaaS entrepreneurs and operators first, and investors second; the experiences of our founders; and the experiences of others from around the world allow us to understand, discard, adopt and adapt the techniques and models others have used. I’m sure we will return to this report in a few years time to add more stories and ideas.
Thank you to all the people who have contributed knowingly or otherwise.
We have endeavoured to list all the sources we have drawn on below.
Sean Ellis on Start up Problems
CB Insights Article
Brad Feld Blog:
Sean Ellis Test
Sean Ellis, Hacking Growth
Steve Blank, Four Steps to the Epiphany
Steve Blank on Customer Development
Rahul Vohra on Superhuman
Lee Hower on PMF & Revenue
Alan Gleeson on Validating PMF in Early Stage Saas Startups
Julie Span Article on GTM
Leela Srinivasan on Using Customer Feedback
David Skok on Understanding Buyer Triggers
Hubspot on buyer journeys
Townsend Wardlaw – also on the buyer journey
Gigi Levy-Weiss on Finding PMF
Notion Podcast with Jonathan Gales
How Emergence Capital evaluates series A pitches: