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Re:Show HN: I created an algorithm to help me achieve Produc... by koonsolo on Wednesday October 30, 2019 @08:42AM (#21397031)
For those who think the "40%+ of users would be highly disappointed if your product did not exist" is weird to test PMF, I recently found a better way: Your cohort retention curve should flat out somewhere above 0%.

I find the 40% rule weird because it highly depends on which people you include as "users". The flattening retention is way more acurate (vs survey question) and already gives more insight into what people are actually doing on your platform.

Re:Show HN: I created an algorithm to help me achieve Produc... by glaive123 on Wednesday October 30, 2019 @12:26PM (#21399455)
It's not weird at all. It's also called the "Must Have" Metric which defines if your product is a Must Have vs. Nice-to-Have. Must Have means your users can't live without it. This is the first state of Product/Market Fit. If you have can find a scalable channel then you have the second stage of Product/Market Fit.

Not all products need or have retention. Some amazing businesses are 1-time or products people pay for but don't need to use or actively engage with.

e.g. Universities, Courses = 1-time use Stocks/Investments = buy them and don't touch them until you sell Insurance = buy it and don't touch it until you renew 1 yr later Plenty of other examples

But every product should be a "Must Have" if it's going to grow.

Re:Show HN: I created an algorithm to help me achieve Produc... by koonsolo on Wednesday October 30, 2019 @01:54PM (#21400512)
But you need 40% of your "users" to qualify.

If I take all registerd people on my platform as "users", I might end up at 0,1%. But if I define a user as someone who is currently using my product >1 month, I might end up at 60%.

You are correct that not all products can have retention. But if you do, the cohort is a better metric in my opinion.

Re:Show HN: I created an algorithm to help me achieve Produc... by fstopmick on Wednesday October 30, 2019 @09:21PM (#21404806)
Here's the source of that line of code:

https://www.karma.fm/p/hJibw7y/eric-migicovsky---how-to-talk...

The way I presented it is certainly weird, but Eric's articulation resonated with me. He also describes cohort retention iirc.

Re:Show HN: I created an algorithm to help me achieve Produc... by StavrosK on Wednesday October 30, 2019 @09:54AM (#21397733)
What's a cohort retention curve?
Re:Show HN: I created an algorithm to help me achieve Produc... by mygo on Wednesday October 30, 2019 @10:03AM (#21397818)
define a cohort.

Say, people who signed up during a given month = 12 cohorts per year

Or people who signed up during a given week = 52 cohorts per year

Then, given a set of cohorts, what percentage of people per cohort are retained over time?

Re:Show HN: I created an algorithm to help me achieve Produc... by StavrosK on Wednesday October 30, 2019 @10:06AM (#21397860)
Ah, so basically the GP is saying "your users should be sticking around"?
Re:Show HN: I created an algorithm to help me achieve Produc... by koonsolo on Wednesday October 30, 2019 @11:34AM (#21398863)
At some point, no more users should leave. For example after registration week 1, retain 60%, week 2 30%, week 3 10%, week 4 1%, week 5 0.1%. In that case, you don't have PMF. Unfortunately my numbers look a lot like this :,(

But assume week 4 has 10% and week 5 has 10%, that curve flattened out at 10%, and so you have product market fit.

Re:Show HN: I created an algorithm to help me achieve Produc... by mygo on Wednesday October 30, 2019 @06:09PM (#21403394)
> Unfortunately my numbers look a lot like this :,(

Fortunately you have a mathematical equation at your disposal that helps tell you this so that you can feel confident in trying something different and seeing how that effects PMF