You won’t be too surprised when I tell you: I’m a big fan of Adobe’s Customer Journey Analytics. Ever since I got the pleasure of using it for the first time four years ago, I am excited for every new release and its many new features. Sure, there are some things that Adobe Analytics is still better at, but the way CJA innovates on familiar concepts clearly shows how it will one day surpass AA’s features. The most recent release is no exception to that trend. As you know, Customer Journey Analytics works fundamentally different from Adobe Analytics. Where Adobe Analytics relies on the Visitor Profile to keep data about a Unique Visitor’s history and provide information like Entry Pages, Exit Pages, etc., Customer Journey Analytics does those things in real-time when we query the data. While this brings challenges for a couple of use cases (like deriving the Visit […]
Tag: Data
The 4+1 Types of Digital Analytics Solutions
If you’ve been following this blog for a while (in which case: thank you!) you already know how much I love Adobe’s analytics solutions, like Adobe Analytics and Customer Journey Analytics. And while I can’t shut up about my excitement over every new feature, I rarely talk about the strategic and positioning aspects. The most I’ve written about that is when I was comparing Adobe Analytics and Google Analytics and gave my take on where people should go after the UA sunset. In some of my recent conference talks and my Adobe Analytics Masterclass, that strategic component got a lot more attention. For the Masterclass, I even dedicate a whole half-day (25% of the training!) to strategic decisions and incrementality considerations. So today, I want to share some of my takes on how I think about different solutions and what makes them special. To do that, I’ll first cover how […]
Exploring Forms Tracking with Custom Data Types in Adobe Customer Journey Analytics
I can’t think of any analytics tool that got me quite as excited this year as Adobe’s Customer Journey Analytics, especially with the recent addition of Derived Fields. While there are some features still missing from Adobe Analytics, it should become more and more clear that CJA is already superior to the vast majority of the market. While I’ve already done an extensive series of posts on how to get started with CJA for a website and exploring the mobile AEP SDK, the new tool brings up many, many questions around setup, admin, and implementation. While the interface for business users is the familiar Analysis Workspace-democratization-paradise, all of the new and shiny capabilities invite us to re-think how we provide analytics capabilities to our companies. In this post, I want to take a look at an evergreen of digital analytics: Form tracking! Unperturbed by any recent trends, websites like to […]
Marketing Channels just got so much better in Adobe Customer Journey Analytics
Like it or not, but analyzing marketing performance is a key requirement for any digital analytics solution. Even solutions that try to find a niche by self-branding themselves as “product analytics” tools have some more-or-less developed feature to analyze marketing performance. In Adobe Analytics, we can use the Marketing Channels feature to analyze where the traffic on our website is coming from. So far, so neat! However, Marketing Channels in Adobe Analytics have one big drawback: They rely on comparatively simple Processing Rules. In those Processing Rules, we have to find a way to identify traffic for a given channel only by using what is available during data collection. Many customers use the Tracking Code dimension to achieve that, forcing them to use campaign codes like “searchads-123” to identify traffic from paid search ads. In the Processing Rules, they would then configure a rule like this to identify SEA traffic: […]
Keep track of goals using the Linearity Indicator in Adobe’s Analysis Workspace
There is an universal truth in life: Inspiration always strikes when and where you least expect it. The same happened to me the other day, when I was reading High Output Management by former Intel CEO Andrew Grove. While the book is definitely worth reading for anyone interested in management, analysts can benefit just as much from reading it to get inspiration for valuable performance indicators and visualizations. Quite early in the book Grove presents one of his favorite visualizations to track progress towards specific goals: The linearity indicator. This chart shows the current progress towards a set target and where the performance might be heading. Here is his example for a hiring target from the book: My initial reaction was “wow, this is super cool and simple to understand”. If the current progress is above the linear progress, we’re in good shape to reach our goals. If it is […]