Yes, I agree with both points. What I think your second point highlights, using metrics, features, and releases to empower deeper discovery and deeper understanding, is really about contextualized measurement and curiosity-led product practice, not just numerical targets. Metrics should help us learn about how people actually experience our work, not just celebrate the numbers themselves. When the data stops being an end and starts being part of an ongoing conversation with users, that’s where you can begin to see signals that matter.
I think lots of companies aspire to this but in practice they accomplish it to varying degrees. One company that does it well, or at least used to, was Snagajob. A few others that come to mind include Stripe, Spotify, and Netflix but someone with more recent or accurate information might argue differently.
I haven’t heard this distinction before. “Metrics shouldn’t just be celebrated.” And the added pointer that they can be used to help us understand how people actually experience our work.
So they aren’t to be optimized in and of themselves either, per se. They are to be guided towards more and more accurately listening to the users. This is a very useful framing. Thanks so much, Mike.
Ths framing around reformulation backfire is really sharp. The observation that depriving users of pharmaceutical opioids essentially channeled them toward an unregulated black market captures what I've seen in harm reduction spaces too: the intervention people assumed would reduce risk instead created pathways toward fentanyl. It's wild how often product fixes ignore the system dynamics that actually drive behavior.
Two takeaways:
1. Optimizing for metrics, even activation and retention, IS NOT the same as being useful. YouTube story hits home on this.
2. Use metrics, features, and releases to empower deeper discovery. Deeper understandings. Those are doorways to the truth, not the end of the job.
Who do you know who actually does #2?
Yes, I agree with both points. What I think your second point highlights, using metrics, features, and releases to empower deeper discovery and deeper understanding, is really about contextualized measurement and curiosity-led product practice, not just numerical targets. Metrics should help us learn about how people actually experience our work, not just celebrate the numbers themselves. When the data stops being an end and starts being part of an ongoing conversation with users, that’s where you can begin to see signals that matter.
I think lots of companies aspire to this but in practice they accomplish it to varying degrees. One company that does it well, or at least used to, was Snagajob. A few others that come to mind include Stripe, Spotify, and Netflix but someone with more recent or accurate information might argue differently.
I haven’t heard this distinction before. “Metrics shouldn’t just be celebrated.” And the added pointer that they can be used to help us understand how people actually experience our work.
So they aren’t to be optimized in and of themselves either, per se. They are to be guided towards more and more accurately listening to the users. This is a very useful framing. Thanks so much, Mike.
Ths framing around reformulation backfire is really sharp. The observation that depriving users of pharmaceutical opioids essentially channeled them toward an unregulated black market captures what I've seen in harm reduction spaces too: the intervention people assumed would reduce risk instead created pathways toward fentanyl. It's wild how often product fixes ignore the system dynamics that actually drive behavior.
I love the comparison from OxyContin to undesired effects in human behaviours
“human messiness” we’re chaotic, unpredictable beings that create creative and beautiful moments. Thanks for the content. Great read