Superhuman built an engine to find product market fit (2018)
review.firstround.com
review.firstround.com
But if you have users you can simply test product market fit to see engagement. If people are engaged, that's a good sign. If you have people that are signed up and aren't engaged, that's a bad sign.
The author uses Slack as an example of a company that has product market fit and over 50% of users surveyed would say they'd be "very disappointed" without Slack (the magic number to beat is 40%). I wonder how that poll would fare for Microsoft Teams, that has 320 million MAU compared to around 40 million for Slack (roughly, few years old but order of magnitude is ~10x). Does Slack have more of a product market fit than Teams because very few people would be disappointed if Teams stopped existing? Or is usage a better metric?
I'm coming from a lay perspective but they just seem like totally different markets. I don't know a single person who has ever used Teams voluntarily. I don't know a single person who likes Teams. But I know tons of people who use it every day, because it was bundled and cheap or convenient for their employer to install it on their machine. Meanwhile I don't currently have any Slack communities that drive me to use it, but if given a choice between Slack and Teams I'll always pick the former.
(Actually Discord is where most of my communities are now, and I'm not happy about that either; it's great for social gaming and pretty bad for text chat - although for different reasons than Teams. I am heavily engaged in Discord, and I would be happier if it ceased to exist, because it would force alternative modes to be chosen)
I'm almost on this bandwagon, I was super annoyed when all my groups from from google chats and such to discord. Now that I have to keep it around for at least one of those groups, I don't really mind, but having to initially install it and get used to it was annoying.
I guess it’s VC product fit. Or VC salesman fit or something.
As the other comment in this thread asks “the proof is in the pudding, does Superhuman have product market fit today?”
It reminds me of Peloton (though they did go mainstream-ish), or the Snoo (smart baby bassinet)... just because a ton of people email/exercise/have babies doesn't mean the bulk of them are in the market for the hyper-optimized and high-price solution.
Finally, some time ago managed to sign up in hopes it could help to manage multiple inboxes with a unified inbox for all of my accounts. Nope doesn't have that. Canceled my subscription immediately yet I kept receiving their spam for a while.
Overall, a very scammy vibe.
They emailed me when features I mentioned were added and then a couple of years ago tried again. Been using it everyday since then as my primary email driver at work.
They know they have a niche product - a paid email client; an expensive one at that! So they filter so word of mouth and reviews and all match expectations and make sure their product is a good fit. It has been the opposite of scammy.
Wait! That means, if the only person using your product is your mom, you have PMF.
Based on what you said and the TFA, this is Superhuman’s PMF approach (i.e., perversely satisfy this metric by filtering users).
I don’t understand where this “engine” is, but perhaps that’s it.
> Wait! That means, if the only person using your product is your mom, you have PMF.
This just seems straightforwardly correct. If you want to find the size of your total addressable market, use a different tool; this one is for product market fit.
That is - you don’t want to build for people that already love your product (it’s already great for them!) and you don’t want to build for people that absolutely don’t like your product (would need a very different product), but instead build for people that you can convert from “somewhat like” to “love”.
It was not worth it for me at that price point, but they clearly put so much craftsmanship into the app, I feel obliged to defend it from be called scammy. It remains on the short list of best “new technology” experiences for me, right up there with some of my first Apple devices.
I also tend to get annoyed with forced 1:1 onboarding, but they seem to have found that the tool is only sticky if they help retrain your habits. It worked for me, and others I know.
It's been a bit quiet since their insane hype-cycle during the time this article was published.
https://www.reforge.com/podcast/unsolicited-feedback
Think of it like you're making a career change and immersing yourself in a new circle. Not strictly studying, rather just hanging out and taking it all in.
It helps my brain more fully switch into the "product leader identity". It's been very helpful and fun.
With a small sample size and large numbers of personas / categories you would expect to see a positive bump, even if there was no statistical relationship between the persona and the preference. Since you are only eliminating categories that don't happen to be represented in the subset you are testing, you can only ever actually go up.
For demonstration I rolled 20 dice randomly for 6 personas and 3 categories of preference:
1, 5, 4, 4, 4, 2, 6, 1, 4, 2, 1, 2, 5, 6, 3, 6, 3, 2, 1, 3
A, A, A, A, B, C, B, A, C, A, C, A, B, C, A, A, B, A, B, B
A = 10, B = 6, C = 4; Which gives me 20% for C
I restrict myself to just the numbers that voted for C (2, 4, 1, 6) removing all 3 and 5s
I now am left with:
1, 4, 4, 4, 2, 6, 1, 4, 2, 1, 2, 6, 6, 2, 1
A, A, A, B, C, B, A, C, A, C, A, C, A, A, B
This now gives me A = 8, B = 3, C = 4
And now I get 27%, a nice 35% boost! Even better than Superhuman's 10% boost. But this is all an illusion, there was absolutely no dependency between the persona and preference here, which you would only see with a large enough sample size.
Peter Reinhardt from Segment has a must-watch talk for anyone interested in this topic https://youtu.be/_6pl5GG8RQ4?si=pogHC45L58U7K6mW