![]() We could also use Amplitude for attribution but it isn’t as good as Google Analytics. They also form the foundation for a marketing automation stack. I typically get clients to use GA to analyze everything that happens before a user signs up and Amplitude for analyzing anything that happens after the signup. In reality, Google Analytics and Amplitude are more complementary than you might imagine. ![]() Amplitude also requires a significant shifting of your culture (data-driven or not). The event model makes these reports quite powerful as well. Flexible funnels and cohort analyses were there from the start. Events let you track anything you want and you could understand almost any kind of product using them.įinally, Amplitude started with several reports better suited for digital products. They also expanded events to make it extremely flexible. This user model can be quite powerful but it only works for situations where you’re mostly tracking actual customers or users. It’s not just about aggregate numbers but looking at what John Smith did in detail. The importance of concepts like the North Star metric has made Amplitude even more relevant.Īmplitude is built on a user model and they assume that you will be tracking users by their name, email, or something else that is unique. It was born at a time when apps (web or mobile) were already quite popular and there was a need for deeper analysis. Firebase is actually more similar to Amplitude in functionality but it still feels like a GA clone made for mobile marketing.Īmplitude was designed for analyzing digital products like software apps, ecommerce, and more. They kept the same principles but added mobile-specific metrics. Events in GA are also limited to 3-4 event properties which is not enough for digital products.Įventually, GA added Firebase which is their attempt to port this work for mobile apps. They have added things like userID which lets you track individual users but again, it’s an addition not an original design. Most of the reports in GA are suited around looking at users in aggregate. GA also designed their data around the idea of anonymous users which is what most marketing traffic is. ![]() All the kind of things a marketer would need to understand their website. You can also see other performance like landing page conversion rate, time on site, etc. You can easily see last & first touch and even run multi-touch attribution reports. Google Analytics is responsible for the creation of UTM parameters and most tools have copied how GA captures and stores them.īased on this, you can imagine that anything does with marketing attribution is quite strong in GA. It evolved into being a great tool for understanding WHERE users are coming. Google Analytics (GA) was originally designed for content websites in the early internet days (the late 90s). I could try and hack my bike to work on water but I would be better off with a boat. Yes, you might find interesting ways to hack a tool but that may not be efficient. I believe the original design of a tool can help us understand how to use it. Let’s look at the original intent for each tool and how that affects how we use it today. ![]() Sidenote, this is the concept behind one of my favorite podcasts ( Throughline by NPR). ![]() To begin with, we need to go back in time to understand the present. If you have seen my Mixpanel vs Google Analytics comparison, then you know what to expect. The other tool is relatively newer but has quickly made a name for itself. One tool has been around for a long time and has defined fundamental concepts for web analytics. In this article, we’ll do a showdown of Google Analytics vs Amplitude. Apple vs Google, Coke vs Pepsi, and even things like summer vs winter. There’s something about a showdown that is exciting. ![]()
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