Many potentially great companies fail each year because, while they have an incredible product, they don’t figure out how to get it to market fast enough. Figuring out how to reach customers and break through to Product-Market-Fit remains one of the hardest parts of building a successful startup.
This post introduces a four stage framework and checklist for founders to use when searching for Product-Market-Fit (P-M-F) and exploring the early phases of finding a repeatable sales process. It will help you 1) initiate understanding of the market landscape and the pain point you’re solving, 2) learn how to gain access to initial customers and start to understand your machine, 3) prove out the market and underlying components of the machine, and ultimately 4) scale to gain market share. It also provides a measuring system to determine whether you have reached Product-Market-Fit.
For this post I interview Guy Cohen, the CRO at a New York startup called Wonder, to talk about their search for Product-Market-Fit (P-M-F) and the checklist he built along the way.
Like many companies, Wonder had a product that could be used by many verticals. But to find P-M-F, Guy knew that they would have to go vertical by vertical, as the buyer persona, business benefits delivered, positioning, messaging, pricing, etc. would need to be different for each vertical. In itself, this is one important lesson to be learned in the journey for P-M-F, and it follows the highly regarded recommendations of Geoffrey Moore’s book “Crossing the Chasm”. (If you are not familiar with Crossing the Chasm, I recommend that you read this short summary.) To cross the chasm, Moore recommends that you focus on a single market, a beachhead, to win domination over a small specific market and use it as a springboard to expand into neighboring markets.
As Guy searched for P-M-F he developed a framework to make the process for all future verticals more scientific and repeatable, so as to not repeat the same mistakes twice. This framework can be applied to many different companies, across verticals, so that you can more systematically approach and define what P-M-F looks like for your company.
David: Tell us about Wonder and how you approached getting to P-M-F?
Guy: Wonder is an on-demand research service that gives you instant access to the intellect and fact-finding skills of a distributed network of thousands of analysts, at the push of a button. Throw any project at us, large or small, and we’ll turn around answers in 24 hours or less (example: “How are Millennials incorporating technology into their healthcare decisions?”). We help you collect the dots so you can spend more time connecting them.
In our search for P-M-F, we’ve always adhered to this mantra: “you want to be a painkiller, not a vitamin – vitamins are nice-to-haves, but people can’t live without painkillers.” We had a product we believed solved a real pain point, we just didn’t know who felt the pain most, and how best to reach them. Wonder is ubiquitous both vertically and horizontally — it’s used by everyone from teachers to consultants to lawyers to recruiters. This presented us with the difficult challenge in that we had endless verticals and roles to explore, and lack of focus generally leads to failure when there are so many shiny toys to chase. We had to be laser focused on 1-2 verticals to gain initial traction.
David: How did you go about selecting the first verticals, and what factors did you score, to help decide the finalist?
Guy: The first thing we did was build a list of 15 different verticals we thought had this ‘pain’ and then cold called hundreds of firms in each to ask every question they’d be willing to answer. We learned about their day-to-days to see how we might fit into their workflow and after stress testing the various markets, 2 quickly stood out. We then put ourselves in a box and sprinted towards figuring every part of the machine for those verticals. We’re almost 2 years in and the learning never stops.
There were hundreds of factors for us to score each vertical on, but we ultimately boiled the selection process down to 3 primary criteria:
- Frequency & magnitude of pain: those who felt the pain most and most often should have the highest propensity to pay for a solution.
- TSAM (total segmented addressable market): a non-negotiable we answered before exploring any of the verticals was: “Is this market big enough?” We dug deep to find out how many companies there really were and how best to reach them… we tried to avoid looking for a fluffy number that would normally be used to impress VC’s. It didn’t matter if there were five million Biotech firms globally, if we could only find contact info and details for five thousand that was our TSAM until we found more tangible leads we could add to our CRM. This question is crucial because if there are only 300 companies in our TSAM, it wouldn’t matter how much of a pain point we were solving — unless we were selling 8 figure deals the market wouldn’t be meaningful and we’d be lead poor in months.
- Inelastic demand: pricing, as we’ll discuss below, is a fickle art and because we had no idea what the right strategy was we wanted to ensure we had a market that was relatively inelastic. Like most other startups, we were guilty of underpricing in the early days and wanted to avoid getting locked into markets that wouldn’t be able to afford future increases.
Then we used targeted outbound selling to reach these verticals. Some startups begin by selling to inbound leads but we chose not to — inbound is an incredibly effective engine (if perfected) but because we wanted to reach a very particular kind of prospect (targeted, and in a particular vertical), outbound was far more effective.
David: How did that evolve into your spreadsheet framework?
Guy: As it became time for us to start thinking about our next vertical we sat down and wrote out all the things we learned from the first market and that’s how the spreadsheet was born.
Disclaimer: There is no panacea — every company has a different product, with a different vision, and a different strategy to achieve that vision. What we’re about to describe is a generic and repeatable framework for anyone who is trying to find P-M-F in the early days of building a B2B SAAS company. Only fools would try to compress years of learning into a few pages of conclusions. We proceed.
This living and constantly updating formulae is the amalgamation of learning through mistakes, observing, reading, and speaking to people much further along and more intelligent than we are. We initially built it for ourselves as our checklist manifesto for things we had to know before deploying resources into each new vertical (to ensure we didn’t scale prematurely). After speaking with David I realized what we built is actually a standard checklist other B2B startups can use before scaling a sales team or dipping into new markets. We’ve borne witness to so many startups repeating the same mistake: following a round of funding they immediately think the sliver of P-M-F they have is repeatable and has the same funnel metrics and go-to-market strategy as every other vertical they want to tap. So they hire 50 reps only to realize that the HR function at private equity firms is completely different from HR in the Fortune 1000. We’ve tried to dose ourselves daily with Munger’s salient advice: “It is remarkable how much long-term advantage people like us have gotten by trying to be consistently not stupid, instead of trying to be very intelligent”.
Amazing companies fail each year because they have have an incredible product but don’t figure out how to get it to the market fast enough. We hope this checklist helps you expedite your process.
David: Tell us about the framework.
Guy: Our checklist is divided into 4 phases:
- Gain Access
- Dry Run
Below you’ll find the timelines, goals, and key learnings from each phase:
Timeline: Days 1-90
Goal: Understand basic market landscape, what pain point your product solves most, and who your initial targets are.
David: Here are two slides that I like as they show where you are at the start of trying to figure out a predictable and repeatable sales process, and what things look like at the end:
What I like about your Initiate Phase is that coming out of it, you have clarity on the following:
- Who to call on initially
- What is their use case
- What messaging will best work for them
- And some initial thoughts on how to go about reaching them
2. Gain Access
Timeline: 91 – 180 days
Goal: Land initial clients & start to understand the machine.
Key Learnings: Gaining access will bring about some of the hardest days but you finally start to hear the golden word (‘Yes’) and it makes all the ‘No’s’ worth pushing through. The main goal of this phase is to have enough confidence to know that it’s worth pouring more fuel into the machine to see where it will break. At this point you’ve only tested your hypothesis across a small sample size and you should be able to solidify the following before testing with a larger n:
- Funnel metrics that make economic sense (even if you have to extrapolate)
- What’s the average and median CAC, LTV, and ACV across your first cohort of clients
- What kind of quantifiable business benefit they get from using your product
- What kind of price point they are likely to accept
- What cadence structure ensures highest access and close rates
3. Dry Run
Timeline: 181- 365 days
Goal: Prove out the market and the underlying components of the machine.
Key Learnings: We found the Dry Run phase to be the rockiest part of the journey and at times can feel like you’re in a raft barreling down a class 5 rapid ping-ponging from river bank to river bank while you iron out the kinks. This is where the real calibration happens. While the waters are tough pedagogues they provide some of the most valuable lessons along the journey.
By the end of this phase you should gain significant clarity on the early mechanics of your machine:
- How accurate were your hypotheses across all components of the machine?
- Was the sales cycle closer to 7 weeks instead of 3 weeks?
- Do companies with legal teams have extended sales cycles?
- Which funnel metrics have the greatest areas for improvement and what levers can you toggle to move them in the right direction?
- What did you miscalculate and what’s the best workaround?
- What does the post-sale hand off and onboarding process look like?
- What are you hearing (qualitatively) on pricing relative to the value of your offering?
Timeline: 365 days +
Goal: Scale the sales team to execute and gain market share in this vertical.
Key Learnings: looking back from the peak of the Deploy phase will leave you with an entirely new level of learning. At this point you should most importantly be able to determine your ability to scale, and at what rate.
The biggest ticket items you’ll walk away with clarity on:
- Size of the market: after hearing from thousands of prospects and gaining a better understanding of what exact pain you’re solving and who’s willing to pay, how big is the actual segmented market?
- Ideal user / buyer: you’ll also have a better idea of what type of firm (size, specialty, jargon used, etc.) fits the perfect profile as they’ll have the highest close / usage rates.
- Hiring / Training: what do your machines look like for hiring & training and what types of candidates fit your ideal profile? More importantly — what types of candidates should you stop hiring more of?
- How do you shorten the learning curve for new hires to ramp them up faster?
- Pricing: what have you heard? Are you getting pushback 10% of the time, or 90% of the time that you’re too high? (they generally won’t tell you if it’s too cheap)
- Further certainty (or uncertainty) around machine mechanics: are the deviations from your hypothesized funnels getting closer to where you’d like them to be?
*you’ll notice many of the steps / questions are repeated at each stage of scaling as your sample size increases and your job is simply to re-evaluate and prove or disprove your original hypotheses.
Measuring Product Market Fit
David: How did you think about measuring Product-Market-Fit?
Guy: It felt strange to us that there wasn’t some quantifiable way to measure how good (or poor) a job we were doing at figuring out Product-Market-Fit. Out of all the articles we’ve read most don’t address the fact that P-M-F is a 2-part equation: the first side of the equation addresses Pre-Sale, and the second is for Post-Sale. Both are vital and if either is neglected you risk a great deal (we made that mistake). One thing we’ve witnessed is companies hire amazing reps who can sell a ice to an Eskimo so accounts are flying off the shelf, but they don’t find out until much later (weeks /months) that nobody is actually using their product as utilization and churn are lagging metrics. Because of this we’ve struggled with and have tried to create a framework that allows us (the community of bold entrepreneurs) to have the best shot at leading indicators for whether or not we are walking the line for P-M-F on the Post-Sale side (we believe this is in fact more important than the Pre-Sale equation in the long run).
This is still a work-in-progress and will be different for every product and every vertical. To keep things simple, we chose what we believed to be the most important variables in the early days to avoid churn (growth and virality were luxuries for phase 2 — step 1 was making sure we didn’t lose clients we worked so hard to acquire). The thinking here is that if you’re in the right market solving for the right pain point you should have a good close rate, a decent sales cycle, and sticky end usage, and we believed there should be some equation for that.
We then assigned acceptable ranges (and corresponding values) for each variable as a warning system in case we had miscalculated something. Multiplying our coefficients by respective values left us with the sum of their parts: a score greater than 50% meant we are in the right forest but had work to do on clearing the path forward (offering, pricing, messaging, etc). A score below 50% on either equation gave us directional indicators of what we needed to focus on solving, or if we were in the wrong market altogether. We know this is oversimplified but mediocrity often hides in what’s unquantifiable and we believed it’s better to have an imperfect indication than none at all.
You will need to adjust the ranges and variables to suit your product and market. (e.g. your average sales cycle may be 9 months based on your ACV / market while another service might be shooting for a 2 week sales cycle). Take this equation and make it completely your own — that’s the point.
David: What were the key lessons you learned from your first vertical that you wish you’d known beforehand?
Guy: A few immediately come to mind:
- Talk & listen to users / buyers: you can’t find out through email marketing. It’s vital to hear their voice and understand the market challenges and opportunities through real conversations — call as many people as you can and get them to open up.
- Test your Pricing: as we learned in the Lessons of History, “Total perspective is an optical illusion. We must operate with partial knowledge”. We didn’t get it right the first, or 2nd, or 3rd time and it’s one of the most critical components to success. We treated it more like an R&D function that constantly needed to be tested and tweaked until we achieved the results we were satisfied with.
- Find a CEO with a clear long term vision: so much of this P-M-F journey is dependent upon what you’re ultimately trying to achieve as a business. I was blessed to partner with a founder who trusted the process as we wandered through the desert. Make sure you are completely aligned and leave no room for miscommunication on plans and expectations.
- Everything is better in 2’s: we’ve always tried to avoid single points of failure. For example if you hire a single rep and they tell you this market doesn’t work, that’s your only reference point and you can’t be certain if it’s that rep or the market itself. We’ve always tried to do things in 2’s and it’s saved us more than once.
- Books: Winning the Brain Game, The Sales Acceleration Formula, Never Split the Difference (3 must-reads)
David: Any final thoughts for other entrepreneurs starting their journey?
Guy: We’ve heard a handful of entrepreneurs claim they “found” P-M-F as if it’s the last horcrux that leads to a happy ending, but Alan Watts famously said “you cannot walk off with a river in a bucket. If you try to capture running water in a bucket, it is clear you do not understand it and that you will always be disappointed, for in the bucket the water does not run.”
We prefer to think of P-M-F as a perpetual river that evolves over time and takes turns you could have never imagined, and only the paranoid survive this trying journey.
Here’s to surviving!
For those interested in learning more about Guy, I asked him to tell us a bit about himself
Guy: Everything I learned about work ethic and tenacity can be traced back to my parents.
Having a love affair with numbers growing up naturally led me into accounting and then finance before I caught the startup bug. I joined the team at Seeking Alpha and as we grew the company I had the fortunate privilege to work directly for the founder and CEO; it was the greatest 2 years of learning I could have ever hoped for.
Along the same timeline my close friend Justin was building Wonder and he eventually hooked me — I was sold on the product and his vision and couldn’t imagine not working on this massive challenge, and so our journey began.