I really love Mixpanel, it is the "best in breed" when it comes to event analytics. I don't think many people would argue with that, it's awesome. In fact, we u

I really love Mixpanel, it is the "best in breed" when it comes to event analytics. I don't think many people would argue with that, it's awesome. In fact, we use it at Zapier for pretty much everything (basic funnels, A/B testing, retention, engagement, etc...) and we haven't even reached our full potential with it yet. But I still have some pretty fundamental beefs with the state of analytics software in general. About the article, the problem stems from the fact that proper analytics is hard and is (arguably) getting harder with more advanced packages.Shouldn't it be going in the opposite direction? It is a lot easier to track discrete downloads or pageviews than some other, more insightful metric, so people will naturally gravitate to the cheaper metrics. Until this is reversed, bullshit metrics will reign. Anyways, my beefs: First: how do you decide what data to send into the package? The more data you send, the better (sure), but at a certain point you are just duplicating your internal datastore, so that is too much, right? But not enough and you'll miss a chance to understand a phenomena that you didn't predict seeing (isn't that the point?). After you decide, then you write a crapton of code to send it all (what about backfilling data when you want to track something new?). Second: once you are collecting the data, how do you know what metrics to actively track? This is definitely existential, but it's back to the core problem: doing analytics properly is hard. Why couldn't the software let me define some properties about the type of app I am running and suggest some strategies (you have a subscription SaaS app? Try tracking paid plan retention, signup funnels, etc...). Maybe it could go even further with reverse funnels, as in: what events are the most important and work backwards. I could see some automation and discovery possibilities there. Third: do I really have to dig around trying to find something useful? All the data is there, the software should tell me what is useful or interesting. It's definitely a hard problem, but I would throw money at software that could send me this email: "Looks like users who experienced event "ABC" also performed your highest priority event "Signup" at a 13% higher rate. This observation is 99% confident." Of course, you'd need to investigate a littler deeper to see if that isn't just a fluke or something stupidly obvious (like: people who view a page signup at a higher rate than those who don't), but at least I might learn something. I know this is certainly a pipe dream as of today, but I vow to shower someone with money if they can do this. In my opinion, the next generation of analytics software won't just have more bells and whistles, it will fundamentally shorten the time to some sort of real "AHA!" insight.