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The Shape of Traction

We do a fair bit of investing in companies pre-product and spend a lot of time speaking with entrepreneurs before they have found strong product/market fit.

The tricky thing about the period before strong PMF is that it’s rare that things are obviously not working.  If you are a smart, competent team building quality products, usually you can squint to see some evidence that things are “sort of working” and believe that with a few more iterations or more scale, things will really start working. Essentially, there is the sense that strong PMF is just around the corner.

It’s been helpful for me to think of this period in terms of a graph, and to contemplate the shape of these curves. Imagine a graph with the X-axis being “product quality” and the Y axis being “traction”.  There is some level of traction that suggests that it’s highly likely that you have strong product/market fit.

Screen Shot 2016-09-02 at 11.17.10 AM

The simplest visualization of this would be a straight line.  The better the product, the better the traction, and the relationship would be linear.  This is simple to visualize, but everyone knows it is not the reality.

Screen Shot 2016-09-02 at 11.18.08 AM

The more accurate visualization is probably an S curve.  Initially, the improvements in a product yield positive results, but the return on product quality start to increase exponentially as you approach PMF.  At some point, you get diminishing returns and the relationship starts to flatten.  For the purposes of this post, let’s just contemplate the first half of this curve before we really start seeing diminishing returns.  It looks more like this:

Screen Shot 2016-09-02 at 11.19.28 AM

The challenge for entrepreneurs is interpreting the flattish part of the curve.  That’s the “kind of working” phase.  Where is the kink in the curve for your product?  Is it pretty close, which would mean that it’s right around the corner?  Is it actually pretty far?  Or, even worse, is there not really a kink to be found and the curve you are on is actually different.

Example 1: You think you are close to the kink, but are pretty far

Screen Shot 2016-09-02 at 11.21.09 AM

Example 2: You think you are heading for an inflection point, but you are not

Screen Shot 2016-09-02 at 11.24.35 AM

It’s hard to have a crystal ball and really know where you are, and there isn’t a one-size-fits-all approach for all businesses.  But I’ve found that it’s helpful for founders think about this framework and the assumptions they are making about where they are in the curve.  From my experience, I’ve noticed a few things that tend to be true.

First, founders tend to over-estimate how good a product needs to be before you start to see meaningful traction.  Put differently, it’s amazing how crappy or bare bones products or services are when they start to show meaningful adoption and wildly happy customers.  Now, in competitive segments, there may be minimal level of quality required around look/feel, speed, and polish.  But when you think about the actual features and functionality, bare bones products that are doing unique things can get adoption very quickly.

Second, founders tend of underestimate how well things work when they do start working.  This is why it’s easy to think that PMF is right around the corner, when it is in fact far away. Don’t fool yourself into thinking that you have PMF when you don’t.  That’s one advantage one might have if they have been at a company that has had very strong PMF, because you know what it looks like when it happens.  The best discussion of this is in an old post from Marc Adreessen almost 10 years ago. The article is republished here (on LI of all places) https://www.linkedin.com/pulse/marc-andreessen-product-market-fit-startups-marc-andreessen

The money line:

“You can always feel when product/market fit isn’t 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’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.”

So, I find that the journey for find PMF often looks different than you think.  Lesser products can create greater traction, and that traction is faster.  Instead of this picture:

Screen Shot 2016-09-02 at 11.19.28 AM

It actually looks more like this:

Screen Shot 2016-09-02 at 11.26.23 AM

And because of that, the search for PMF may be challenging, but it’s not usually constrained to one curve.  It’s more a series of bigger pivots or restarts that occur on different curves, until you find yourself on the right one.  This is hard to illustrate unless you change the X axis a little, so instead of X being product quality, it is time.  Each curve is a different attempt at PMF with a different product.

Screen Shot 2016-09-02 at 11.27.08 AM

So, for a pre PMF company, what I usually encourage founders to do is shrink the time required to figure out whether an experiment is working or not.  Also, I encourage them to keep their teams small and their burn low during this period.  Having a big team is great after PMF, but often lengthens this process before PMF.  This influences both how much money they look to raise at this point, and how aggressively they should build their teams even if they have a lot of money in the bank.  And if things aren’t working, it’s important to consider much more radical shifts of thinking and direction rather than incremental improvements.

This post is already too long, but one final word.  In this post, I’m speaking specifically about companies that are searching for initial product/market fit.  The path towards building a great company after initial PMF can look very different, and this is not about that.  Anyhow, I’d be curious how this jives with the experience and observations of other founders and investors.  This is just one view of the shape of traction. In my next post, I’ll revisit this idea, but from the perspective of a question I often get: “How much traction do I need to raise a round?”

Rob Go

Thanks for reading! Here’s a quick background on who I am:
1. My name is Rob, I live in Lexington, MA
2. I’m married and have two young daughters. My wife and I met in college at Duke University – Go Blue Devils!
3. We really love our church in Arlington, MA. It’s called Highrock and it’s a wonderful and vibrant community.  Email me if you want to visit!
4. I grew up in the Philippines (ages 0-9) and Hong Kong (ages 9-17).
5. I am a cofounder of NextView Ventures, a seed stage investment firm focused on internet enabled innovation. I try to spend as much time as possible working with entrepreneurs and investing in businesses that are trying to solve important problems for everyday people.  
6. The best way to reach me is by email: rob at nextviewventures dot com


    • Fletcher Richman

      Great post! Really enjoyed that Marc Andreessen (you have a typo in his name) post too.

      I definitely agree with your sentiment that founders should keep teams lean and do big product iterations or even entire changes of direction until it’s clear they’ve reached product market fit. However, I’ve seen a lot of companies raise seed rounds and build their teams up to 10+ because they feel like it will make them move faster. What ends up happening is they burn money faster, can’t iterate as quickly, and have to start fundraising less than a year later.

      How do you communicate to the founders that it’s better to keep a team of 2-4 and survive 10 iterations over 3 years instead of a team of 10 that can only do 1 or 2 iterations over 12 months?

    • Ashley A

      Interesting post…is this considering hardware or IOT companies?

    • The visuals are a great way of putting the journey to PMF in context. As a first time founder, the “is this working?” question is a daily consideration. Although maybe a bit dramatic, the “trough of sorrows” concept is also helpful context. I’m looking forward to the “How much traction do I need to raise a round?” post. At least for me, I often feel “early stage” investors judge our traction against a true product market fit criteria.

    • Wendy Lin

      This is really excellent — I see both mental fallacies (and have experienced them myself) all the time. One of the personally illuminating moments was reading Jessica Livingston’s Founders at Work, after which it became clear that there wasn’t a single example where 1) the product was great when it achieved PMF and 2) the founders were uncertain about whether or not PMF was achieved. I assume these are the truest versions of the stories, given they’re interview transcripts with founders…I guess it does make me wonder about the true stories behind the more recent generation of post PMF startups and whether or not the patterns that were so clear in the last generation still hold as strongly today.

    • AngelSpan

      Our service incorporates the overlooked BellMason Diagnostic, which is the most rigorous playbook on the startup life cycle. It provides the framework to track startups at each stage of their startup life cycle, allowing them to more thoroughly, and professionally, communicate where they are on their ‘product/market’ curve without fooling themselves or their investors/stakeholders.

      The shame is that is has not been applied as much as it should have since its inception in the late 1980’s, leading to the need/invention of the Lean Startup Model.

      Wheels get re-invented, investors’ $’s get wasted, and entrepreneurs (or their investors/mentors/advisors) need to be the source of invention/solutions, rather than executing on what has already been back tested and proven to be successful.

      No wonder entrepreneurs aren’t as transparent as they should be, and vcs are not as transparent on their investment decisions/portfolio companies as they should be.

    • José Andrés Chávez

      Great post, we’ve seen this kill, kill, kill graph first hand, hopefully we’re closer than we think to PMF. Good advice.

    • Hernan Giraldo

      Enjoyed the post. How do you know when is time to start a new radical iteration? Do you have some objective metrics that help make that inference? To me just making it time based, seems a bit single-threated. I agree that there will be a lot of false positives before you find the right PMF. But, how can you try to assess that you are not -prematurely- moving away from a false negative? Perhaps large sale cycle deviations for customer cohort? Low customer engagement or net promoter scores? Any insight on this? Thanks.