The article discusses a way to test product market fit prior to launching. After launch its obvious. But then the way it tests product market fit is asking its users if they would be disappointed if the product didn't exist.
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?
Enterprise software is a different beast as the buying cycle and structure is a lot different. Selling into the enterprise requires a different go-to-market strategy. It's why you never see things like 'Superhuman' reach mainstream tech.
> 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 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.
It's fine for friend (small, private) communities. My problem is that Discord is virtually never a good option for public communities, but it's almost always the go-to choice (because "everyone already has it").
Yeah, it's kinda weird when you are going to a conference or something (especially one that isn't inherently tech related) and discord is essentially required to get the information.
You gotta love good survivorship bias stories like this. Especially those written by VC armchair quarterbacks. It's always the same examples reiterated over and over again.
They found PMF in a niche (productivity-obsessed email-superusers), which is decent market in size, but raised money and got press coverage like a mainstream so in the end it feels like they kinda failed.
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.
My experience with Superhuman has been terrible. Back in the day, I tried to sign up. Couldn't. Then they started allowing sign-ups, but there was a mandatory onboarding/sales call to get started...
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.
I had the opposite vibe. Had the same process went through the call and they asked what I needed and wanted from an email client and after telling them they said that it probably wasn’t for me yet. And I didn’t sign up.
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.
The engine part is looking for users that are somewhat, but not totally satisfied and building for them.
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”.
> TFA says finding product market fit is when 40%+ of users would be “very disappointed” if your product disappeared.
> 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.
I had the same exact experience. I was looking for a Sparrow replacement for years after google bought them and shut it down. I think that's all superhuman needed to do, recreate sparrow.
I have to disagree with the scammy part. They were pretty serious/intense about teaching you how to use superhuman, so the daily emails for the first week could be considered spammy, but personally I found them useful when trying to learn to be a power user.
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 had the opposite experience as well. Big fan, can't live without it. It really helps me manage multiple inboxes effectively. As someone with a similar email challenge it strikes me as less than ideal to view all inboxes in one view? The inbox in question is a pretty important piece of context for the email.
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.
They've been shipping features somewhat regularly. One I really like (but was unfortunately gated behind a $10 price bump) was being able to ask AI to find an email "where's that email about blah" or to have it summarize a long email chain "hey what am I supposed to be doing here"
Even though I don’t have real information, I feel that they focused so much on the power user that they must have a high level of stickiness. I don’t even believe they expected to scale beyond the ICP.
Would love a suggestion on books to start conceptualizing of a business in terms like these, instead of how I currently think of it (tech stacks and cost)
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.
because there were some interesting nuggets. Maybe nothing new to you - but not everyone has read everything on the topic.
though this was more about their process rather than an 'engine'. but you know, headlines /shrug
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:
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.
The pudding proof is the percentage of “very disappointed not to have” in the next round of customers, after adapting customer targeting and product from the previous customer batch.
Having followed this exact playbook to validate several products I can confidently say this will give you false positives and the only reliable way to determine when you have PMF is: accidentally get PMF on something so that you know what it feels like (it’s unmistakeable).
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?