What can you learn from Superhuman’s product-market fit playbook?

[Update on Feb 26, 2020] Rahul Vohra has recently published a super cool interactive tool so people can use Superhuman’s PMF framework for themselves. Check it out here.

As I am building-out my startup Workomo (helping knowledge professionals supercharge their professional relationships), have already used so many ideas from this method. My detailed take in this article below.

One of the best articles I have read in recent times is How Superhuman Built an Engine to Find Product/Market Fit by Founder-CEO Rahul Vohra. As I have been building Workomo over last few months, the overarching goal for me as a founder continues to be — how to achieve PMF while minimizing time spent & capital utilized? Having read Marc Andreessen’s legendary essay on defining PMF (“Product/market fit means being in a good market with a product that can satisfy that market”), as well as all YC stuff on the topic, I had developed a playbook for it in my head:

  1. Make something people want
  2. Be lean (product development approach + capital)
  3. Launch simple & quick
  4. Organic demand generation (networks + communities + word-of-mouth)
  5. Identify early adopter persona
  6. Iterate based on their feedback
  7. Eventually “delight” & consequently, “retain” early adopters
  8. Test how much will they pay
  9. Get to 10, then 100, then 1000 “retained & paying” users
  10. Scale-up from there

As a founder dealing with so many unknowns, one is always looking for actionable insights, more than theoretical advice. Reading about the Superhuman experience just gave me so much execution color on this PMF playbook. I think every founder (and even venture investor!) should absorb these valuable insights so sharing my notes & key takeaways from this article.

Summary of Superhuman’s deconstructed product-market fit playbook:

#1 PMF takes time

#2 Quantify PMF via a single, North Star metric

#3 Structure & execute the user survey process well

#4 Create a highly detailed user persona of the High-Expectation Customer

#5 Focus on delighting a small number of users first

#6 To convert users that are “one-the-fence”, focus on what your fanatic users love the most about your product

#7 Two-pronged product planning approach to move towards PMF — focus on core strengths + address core concerns

#8 For feature prioritization, stack-rank to get to “lowest cost, highest impact” features

#9 Rinse, and repeat…

Let’s dive into these elements in detail.

  1. PMF takes time

Superhuman team first started coding in 2015 and it’s only in last few months that they have attained a critical mass of vocal adopters, who are in-turn, making the product viral. A reality check for all of us in terms of how much time it truly takes to make something people want, and therefore, the value of patience in founding teams (& investors).

2. Quantify PMF via a single, North Star metric

A big challenge in working towards PMF is that it appears “fluffy”, especially when as a founder, you are trying to align your engineering & product teams around it and even more so, when you are trying to set an actionable & trackable process roadmap for it.

The best way recommended is to quantify PMF in terms of a North Star “leading” metric.

The Superhuman team used the following leading metric to quantify PMF (originally articulated by Sean Ellis in this article) — just ask users “how would you feel if you could no longer use the product?” and measure the percent who answer “very disappointed”. The threshold for having achieved PMF is 40%.

3. Structure & execute the user survey process well

Perhaps the most refreshing info in this article are the details Rahul shares about the user survey process they ran, to gather data on the PMF North Star metric:

a) Identify users who used the product at least twice in the last two weeks

b) Exact survey that was sent out given below (just the minimum number of critical questions were included, amazingly succinct yet effective!)

PS: I loved the 2nd question, where existing users are prompted in a way, to describe their own persona. Makes it so much easier to clearly identify who your real early adopters are. More on this later.

c) Classified the responses into 3 buckets — 1) Very Disappointed, 2) Somewhat Disappointed, and 3) Not Disappointed.

d) Assigned a persona to each bucket, to identify the “Very Disappointed” user persona (the actual early adopter)

To me, this entire user survey process is the core of the PMF playbook, and something I found exceptionally insightful.

As has been my learning doing Workomo’s customer development process, at this really early stage of the company, the number of respondents matter much less than you think. Some data is better than no data, especially coming from actual, retained users. Superhuman mentions anything more than 40 responses as an adequate sample size (at the time, their universal sample set was only ~100–200 users that could be polled!!)

4. Create a highly detailed user persona of the High-Expectation Customer

I think the most clever trick in the above user survey structure is Q #2 — “what type of people do you think would benefit most from Superhuman?” ‘Cos, people tend to describe their own personas as a response. Analyze responses to this question only for the “Very Disappointed” bucket, and you end up with detailed personas that users themselves have pretty much self-created for you!

Going from this 1st level user persona…

1st Level User Persona

…to the 2nd level user persona.

2nd Level User Persona

PS: have been searching for what an optimally-sized user persona should be like for a really early stage startup. This is a great example — ~200 words, 2 paras; captures both professional & personal behavior, motivations, quantified behavioral characteristics, relevant life goals and desired outcomes/ end-state.

5. Focus on delighting a small number of users first

Paul Graham always says it; Superhuman case study just confirms it — define a narrow market, delight, dominate & then grow out from there.

Reproducing this quote by PG, just to drive home this point:

“When a startup launches, there have to be at least some users who really need what they’re making — not just people who could see themselves using it one day, but 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 be built with the amount of effort a startup usually puts into a version one, it would probably already exist. Which means you have to compromise on one dimension: you can either build something a large number of people want a small amount, or something a small number of people want a large amount. Choose the latter. Not all ideas of that type are good startup ideas, but nearly all good startup ideas are of that type.”

6. To convert users that are “one-the-fence”, focus on what your fanatic users love the most about your product

Key to converting more on-the-fence users into fanatic users is first identifying the core 1–2 strengths of your product. The reason being, non-fanatic users that fundamentally care about these strengths, are the ones most likely to convert into fanatics. However, this requires addressing their top 1–2 product concerns.

In Superhuman’s case:

Core strengths (as told by fanatic users)— speed, focus, keyboard shortcuts

% of “Somewhat Disappointed” bucket users, who care about “Speed” as the main benefit — 30%

For these 30% of “Somewhat Disappointed” users, what are their primary concerns (as told by them in the survey)— lack of mobile app (MAIN) + integrations, calendaring, better search etc.

7. Two-pronged product planning approach to move towards PMF — focus on core strengths + address core concerns

Boom! Post the above 6 steps, now you have a clear roadmap of features needed to convert on-the-fence users to fanatic users, and inch closer towards that elusive 40% PMF benchmark.

Your PMF product plan needs just the following 2 strategies — 1) doubling-down on core strengths that are loved by fanatic users+ 2) working to allay concerns & feature requests from on-the-fence users.

8. For feature prioritization, stack-rank to get to “lowest cost, highest impact” features

Use a combination of survey data and your qualitative product instinct to arrive at the low-hanging features (low cost + high impact) that can start delivering immediate value to users.

9. Rinse, and repeat…

…until you get to PMF!

Hope you find this deconstruction useful for your own journey towards PMF. Would love to hear any specific strategies that have worked for you.

Side Note: am currently building Workomo, a smart & simple professional relationships management hub for the new-age knowledge professional. If you would like to transform yourself from just a “networker”, to a deep “relationship builder”, do sign-up to receive private beta access. Also, check out this post on Workomo’s long-term Mission & product thesis.

Author: Soumitra Sharma

Operator-Angel I Product Leader I US-India corridor I Believer in Power Laws I Love building & learning

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