Mixpanel (YC S09) Raises $65M to Build Predictive Data Tech
wsj.com
wsj.com
I noticed they mentioned Heap Analytics (https://heapanalytics.com/) as one of their competitors. We've been using Heap for over a year and it seems like the logical and magical next step in analytics. Mixpanel gave you smarter analytics on things you had the foresight to track, but Heap automatically tracks everything from the day you integrate it. That means you can get smart analytics even on things you didn't have the clairvoyance to start tracking 6 months ago, or didn't have the resources to insert tracking code in.
For startups, Heap's automatic and retroactive tracking is huge. It means we can iterate on product features and marketing/outreach schemes way more quickly while still getting insight into what's successful and what's not. It's not perfect--a couple times we've added special class names to our HTML elements so Heap can distinguish them, but that's still easier than adding manual tracking code--but it's a huge improvement over the old way.
I noticed Heap has a page comparing themselves with Mixpanel (https://heapanalytics.com/compare/heap-vs-mixpanel) but I don't see anything similar from Mixpanel's POV. I'd be curious to hear what Mixpanel's plans are in this area (automatic/retroactive tracking).
Unfortunately, Heap's approach only captures the events automatically but can't capture the business-specific attributes that need to go on those events. Ultimately that will always require some human being to think about their business-specific problems.
This is an excellent point. Two things:
1. Empirically, we've found that our customers rarely fall back on custom attributes. The vast majority of queries run in Heap (>75%) operate on automatically-captured events. To me, this suggests we've either: 1) cut out a significant portion of implementation work, or 2) enabled analysis that was previously blocked by implementation work. If either (or both) are true, it's a win, and suggests that automatic event-tracking produces salient data out-of-the-box.
2. That said, some metrics are important and do require manual instrumentation. Coincidentally enough, we're about to launch a feature that solves the problem you mention and requires no extra implementation work. We're excited about it. Want to try it out on newrelic.com?
These are questions for the business, but I feel like Mixpanel could add so much more context. "We noticed that 'time to first interaction' has gone down with 'watched home page video'." That would at least be a clue.
MP has the data, but all of that analysis is manual (or was, last time I used it).
They have these flows that chart the user's path through your site, so you can see where, when and why they dropped off where and when they did.
Before Mixpanel can even attempt to solve that though, they first need to tackle multi-channel attribution. Right now GA and Adobe are the big players who tackle it, and GA only offers dynamic attribution (ie. the holy grail of attribution) in GA Premium (which costs $150k/yr).
If you want a standalone attribution platform you're left with options like VisualIQ, Convertro, Adometry, etc., all of which have recently been acquired by big players in the space.
So yes, I'd love to see Mixpanel answer the "why." However the first step is to truly answer the "where" question and until they add those tools, their model is still fully last touch, and therefore dated.
Of course even GA doesn't use its attribution modeling capabilities outside of the multi-channel/attribution reports, so they still have a ways to go too. The big difference is, those tools are available today for free.
That said, congrats to Mixpanel. They made huge strides in the event tracking approach that GA has since gone on to borrow, and that is what any modern web analytics platform looks at these days because it simply makes more sense.
They've got an elegant and, as far as I know, unique modeling approach that avoids the first-touch/last-touch/path-analysis pitfalls.
Also, would I need an ad server in place to properly attribute display or can they handle that on their own?
It's a unique approach in that they don't need a lot of granular attribution data, but instead use higher level aggregate data. As a result it's easier to integrate with all kinds of media campaigns.
You need to be able to provide impressions over time for your early funnel ads and conversions over time for your late funnel touchpoints. They use some econometric time series techniques to analyze and estimate the impact so you can focus on whats working.
GA's attribution tools are fun to play with, but at the end of the day they are still static models that don't evolve over time as they collect data.