A Quantitative Approach to Product Market Fit

This seems more like a companion article to David Skok’s SaaS Metrics 2.0:<p><a href="https:&#x2F;&#x2F;www.forentrepreneurs.com&#x2F;saas-metrics-2&#x2F;" rel="nofollow">https:&#x2F;&#x2F;www.forentrepreneurs.com&#x2F;saas-metrics-2&#x2F;</a><p>I found it to be more about SaaS metrics and less about product&#x2F;market fit.<p>For example, you could have great product&#x2F;market fit with poor pricing, in which case you might have awful SaaS metrics and sluggish revenue growth while having great usage metrics and rapid organic&#x2F;viral user growth.<p>For example, imagine if PagerDuty or Slack were free for enterprises: they’d have terrible SaaS metrics but wonderful product&#x2F;market fit, IMO.

Interesting, but seems pretty complex. I prefer the model employed by Superhuman: <a href="https:&#x2F;&#x2F;firstround.com&#x2F;review&#x2F;how-superhuman-built-an-engine-to-find-product-market-fit&#x2F;" rel="nofollow">https:&#x2F;&#x2F;firstround.com&#x2F;review&#x2F;how-superhuman-built-an-engine...</a><p>Yeah I know, they&#x27;re the joke of last week, but that methodology is pretty simple (just ask four questions) and (importantly) is trackable over time, while working for businesses of all kinds.<p>Is anybody else using that at the moment? How has it worked out?

Interesting, but this seems more suited for subscription-type software businesses, not anything related to products with longer periods between repeat purchases. You&#x27;d have to wait for a couple of years or more to build out churn&#x2F;resurrection&#x2F;expansion, etc. and cohort data for a hardware or durable goods business. No wonder VCs don&#x27;t really like to fund hardware&#x2F;infrastructure businesses

metrics are helpful, but creation is art