Just last week, I was celebrating Customer Journey Analytics’ new “Next or Previous” and Math features in Derived Fields. While I originally intended to update that post once the new Summarize function is released, I found this feature so useful and versatile that I decided to write an entire post about it. If you want a longer introduction, feel free to check out last week’s post. If not, just enjoy this one! Summarize Derived Fields function The Summarize function does pretty much what the name says: It reduces a larger set of values, like a user’s entire website journey, into a (for now) single value. For example, a user may view a bunch of pages during their session but you might only be interested in the very first page. The Summarize function can return that for you with ease! Now, you may think that this example sounds somewhat familiar. And […]
Tag: Adobe Customer Journey Analytics
Adobe Customer Journey Analytics keeps getting better with Derived Fields
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 […]
2023 (offsite) Content Roundup
Happy new year! 2023 has finally come to an end and with that, it’s time for another yearly content roundup. In case you missed any of my content on other platforms, this should help to get you back on track. Enjoy! Content on my own blog Unsurprisingly, I couldn’t stop myself from writing content for my own blog, despite the many, many other things going on in 2023. Here’s the list of posts: Content on my company’s blog As you will have heard way too many times, I work an amazing company called Accutics, which lets me create all kinds of content on their own platforms.In terms of blog posts, there are three more posts to read: Company video content 2023 was a very interesting year for me personally, since I got the chance to lean way more into video content, webinars, and in-person events. The one-and-only reason why I’m […]
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: […]
Google Universal Analytics is gone. Where should you go now?
Well, it finally happened. In a mild surprise to the industry, Google actually stuck to the announced sunset date for Universal Analytics. While there are some reports of GA still collecting data (I would love to link to the Tweet here and throughout the post, if linking to Twitter still worked) it seems clear that it is actually in the process of being turned off. Some folk desperately hoped for a last-minute deadline extension to give GA4 some more time to mature, further demonstrating how much Google overestimates the maturity of their own tool. Luckily, Google isn’t the only player on the market. My new job at Accutics gives me the chance to speak to many tool vendors at quite a bunch of conferences and conventions. In addition to my own continuous market monitoring, talking to the teams and developers of those tools gave me some deeper insight into how […]
It’s finally time to migrate to Adobe Customer Journey Analytics
The market for digital analytics solutions is going through some big changes. Google continues to annoy customers by removing features from the universally hated GA4, which helps companies like Amplitude, Piano, or Piwik Pro to gain traction in a diversifying market. On the receiving end, vendors are eagerly trying to differentiate themselves by claiming that “product analytics” or “marketing analytics” could only really be done with their tools. Adobe has been quite busy defending their market leadership with their own new tool, Customer Journey Analytics. While I’ve been one of the very first customers of this next-gen Adobe Analytics, my general recommendation has been to stay with (or buy) Adobe Analytics instead, as CJA was still missing some important features for anyone wanting to replace AA. However, this recommendation has now finally changed. As you can see in my comparison post, my general recommendation is now to buy Customer Journey […]
2022 Offsite Content Roundup
Welcome to the first of potentially many posts in a newly-found yearly tradition. At some point during the year, I noticed that I don’t have a continuously updated list of the things I’ve been up to outside of this blog. And even besides that, it is sometimes hard to keep up with all the content that eventually makes it onto the blog. To help with both, I’m planning to release a post like this every year, potentially in the last week of the year. I’m going to try my best to remember all the conferences, events, webinars, and foreign posts (or even update a draft post throughout the year) and put them in some sort of order. Thank you for another great year on this blog and I hope you enjoy all the different pieces of content! I have a YouTube channel now! Writing blog posts definitely is my go-to […]
Should you buy Adobe Analytics or Customer Journey Analytics for Web Analytics use cases today?
The market for web analytics tools is going through some big changes right now. On one hand, Google has officially announced to sunset Universal Analytics (also known as “the ‘good’ Google Analytics”) next year in favor of the universally hated GA 4. On the other hand, Adobe is heavily promoting their new tool Customer Journey Analytics, both to new and existing Adobe customers. There is no doubt that, at some unannounced point in the future, Customer Journey Analytics will become Adobe’s only analytics tool. However, there is one important detail about Customer Journey Analytics that we need to keep in mind: It is not a dedicated web analytics tool like good old Adobe Analytics. Customer Journey Analytics is built to handle data from all sources you can think of, not just websites and apps. Because of that, Adobe Analytics still has some unique features, like the Visitor Profile, that are […]
Cookie-less Server Side Tracking with Adobe Customer Journey Analytics
If there is one big hot topic in digital analytics right now (besides the unfortunate sunset of Google Analytics 3 and GDPR news) it quite possibly is the recent trend of what many call server side tracking. Currently, server side tracking is an obligatory agenda item at every analytics conference and virtually every vendor of analytics or tag management systems is working on a way to serve the rising demand. However, while there is a lot of talk around the topic, there is no shared definition in our industry of what server side tracking actually is. Jim Gordon has assembled a nice overview of what people might mean when they talk about any of the underlying concepts. In my personal experience, people usually refer to a form of server side tag management, often using Google’s server side tag manager, that still uses some logic in the client’s browser. Adobe has […]
Import Google Analytics data into Adobe Analytics using Data Sources
On one hand, Adobe Analytics remains my favorite web analytics tool on the market. The longer I use it, the more I appreciate all the well thought-out features, from data collection to processing, storage, and analysis. Those features are even more impressive when compared with what Google Analytics has to offer. And yet, on the other hand, even I can’t avoid having to work with Google Analytics in some way or another. In a large, global company, it is basically unavoidable to find Google Analytics on some small, long forgotten marketing landing page in some market. It gets even worse: Up until last year, I personally had to maintain an inherited Google Analytics instance on a legacy website and app. What a cruel world! Besides those cases, where someone in your company actually wants to use Google Analytics, there are also more forgivable cases. For example, a company may be […]
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 […]
Web Analytics with Adobe’s Customer Journey Analytics, Part 8: A new home
This post is the eight and last post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we were creating the connection from Experience Platform to Customer Journey Analytics. In this post, we are going to take a look at our web analytics data and explore some use cases. Believe it or not, but this series of posts is almost finished! Starting with nothing, we have created a sophisticated schema for our data in Experience Platform, created a tracking implementation using the new Web SDK, enriched our data in Query Service, and pulled all that data into Customer Journey Analytics. If you have been following since the start of the series, I want to say: Thank you, hope you enjoyed the ride! Now it is time for the finale, where […]
Web Analytics with Adobe’s Customer Journey Analytics, Part 7: Customer Journey Analytics Backend Configuration
This post is the seventh post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we were enriching our basic web analytics data with some advanced fields in Query Service. In this post, we are creating the connection from Customer Journey Analytics to Experience Platform. At this point in this series, we have a world-class dataset of web analytics data in Experience Platform, ready to be analyzed. I’m personally very proud of the things we were able to achieve in Query Service, especially with the pathing dimensions. With all of that, we have even more than what normal Adobe Analytics would give us! With all the data enriched, we now have only one step left before we can start analyzing our digital user’s behavior. First, we need to pull data […]
Web Analytics with Adobe’s Customer Journey Analytics, Part 6: Advanced Data Processing in Query Service
This post is the sixth post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we took a look at processing some basic data we need for our web analytics use case utilizing Query Service in Experience Platform. In this post, we are creating some advanced fields to our data in Query Service. I think it’s fair to say that even with just the information from the previous part, we could have a very useful web analytics tool already. But if you know me, you know that I like to take things to the next level wherever I can, especially if it involves writing code. And is SQL not some sort of code too? Entry and exit page were a nice start last time, but we have some fields still […]
Web Analytics with Adobe’s Customer Journey Analytics, Part 5: Basic Data Processing in Query Service
This post is the fifth post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we took a look at doing the implementation using Adobe Launch, the Adobe Web SDK, and Client Data Layer. In this post, we are going to processing some basic data we need for our web analytics use case utilizing Query Service in Experience Platform. This series of posts is coming along quite nicely. If you followed all the previous posts until now, you will now have a functioning Web SDK implementation that tracks your data into Experience Platform following the Experience Data Schema we have tailor-made for our use case. Nice! Now we are ready to feed our data into Customer Journey Analytics, right? Well, we could. If we are just interested in the plain […]
Web Analytics with Adobe’s Customer Journey Analytics, Part 4: Capturing Data with Web SDK (Alloy)
This post is the fourth post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we took a look at our business questions and how we can structure our data most effectively. In this post, we are doing the actual implementation using Adobe Launch, the Adobe Web SDK, and Client Data Layer. On our way to creating a full-scope, front-to-back implementation of Customer Journey Analytics to track a web site, we are now ready to think about our actual implementation. Since we have the data structure in place and already have an awesome Experience Event Schema, we just need some actual data. The logical choice to feed data to the Adobe stack is, of course, by utilizing their client-side tools as well. Specifically, we are going to use Adobe Launch […]
Web Analytics with Adobe’s Customer Journey Analytics, Part 3: Data Structure in Experience Platform
This post is the third post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we took a look at the different possible solution architectures we can use to bring data into Customer Journey Analytics and decided on the best one. In this post, we will take a look at our actual business questions and how we can structure our data most effectively. From the last post we already know that we want to track data using only the new Adobe Web SDK going forward. To make that work, we need to create a schema in Experience Platform first, which defines the structure of the data that we want to capture. While some people (sometimes me included) see schema management as one of the more tedious tasks in Platform, I […]
Processing Adobe Analytics Data Feeds with Apache NiFi for Adobe Experience Platform
In the series of posts that is currently being released on this blog I’m showing how companies can move from Adobe Analytics to the brand new Customer Journey Analytics to utilize the many advantages of the new tool. However, I feel like the current Adobe-provided solution for bringing data from that old to the new world lacks some essential information. I did an extensive comparison in the most recent post of the series, but will give some of the reasons here again. When we use the Adobe Analytics Data Connector to bring data from an Adobe Analytics Report Suite into Experience Platform, we are dealing with some limitations: The data is based on what Adobe calls mid-values. Those sit between raw, unprocessed data, and fully processed data in the processing chain. Because of this, we don’t have access to dimensions like persisted Evars, Visit Number, and other data points we […]
Web Analytics with Adobe’s Customer Journey Analytics, Part 2: System Architecture in Experience Platform
This post is the second post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In the previous post, we discussed the motivation and scope of this project and why, eventually, existing Adobe Analytics customers will start moving to Adobe’s Customer Journey Analytics. In this post, we will take a look at the different possible solution designs we can use to bring data into Customer Journey Analytics and decide on the best one. Adobe’s Customer Journey Analytics is built on Adobe’s brand new Experience Platform. With that, it is very flexible in terms of how data can be brought into the tool. Depending on the setup it may seem very easy to bring data in quickly. However, all that flexibility also means we have many ways to deviate from the ideal path, so we […]
Web Analytics with Adobe’s Customer Journey Analytics, Part 1: Goodbye Adobe Analytics, my Old Friend
This post is the first post of the eight-part-series Web Analytics with Adobe’s Customer Journey Analytics, showing how web sites can be analyzed better using Adobe’s next evolution of Adobe Analytics. In this part, we discuss the motivation and scope of this project and why, eventually, existing Adobe Analytics and new customers will start moving to Adobe’s Customer Journey Analytics. If you found this article, chances are high you work in or adjacent to the field of digital analytics or web analytics. It doesn’t really matter if you are an existing Adobe Analytics user, on the Google stack, or just looking for your very first web analytics tool. If you have been following the trends and discussions in our industry in the recent time, you will likely already have caught on the massive changes that both our industry and Adobe’s products go through. With changes to privacy requirements and cookie […]
Tracking Apps with Adobe’s new Experience Platform SDKs and the Edge Network
Tracking mobile apps has always been fun for me. Compared to measuring websites, apps are a more controlled environment, which is great for data consistency. Sure, there are some less-fun cases (like those pesky hybrid apps) but the general experience on major platforms like Android and iOS has been quite great! Changes even happen a bit slower compared to browsers and there are way less moving parts to keep track of. Just like when tracking websites, Adobe has been most helpful in providing us the tools we need to collect data in the most effective and consistent way. If you have been tracking mobile apps with Adobe for a while, you will know about the similarities between websites and apps (like having a trackState function that increments Page Views and trackAction for Custom Links) and nice comfort features (like automatically tracking App ID, Launches, Upgrades, etc.) that make it so […]
Calculated Metrics in Segments are finally here… Sort of, in Adobe’s Customer Journey Analytics
If you have been following this blog for a while (thank you!), it shouldn’t surprise you if I claim: Adobe Analytics is the best web analytics solution available today. But if we’re honest, it has been around for a long time, which has been leading to a situation very familiar to anyone working in the tech industry: The things that we build today might limit us in the future when new technology becomes available. This is also true for Adobe Analytics. When Adobe Analytics was created, it was necessary to build features like the Visitor Profile or Props in a certain way with what was available at that time. Back then, it was necessary to store Visitor Profile information in a database and add it to the data as it was processed (something I also used in a previous series of posts). The database engine on top of that data […]
The Visitor Profile: Adobe Analytics’ Big Advantage
We live in some very exciting times for our industry. There is a lot going on in the analytics space with Adobe’s brand new Experience Platform, Customer Journey Analytics, Web SDK, and Launch Server Side. All of those new innovations will fundamentally change how we track data and process data once it has been collected. But since I got the opportunity to try out most of those exciting things myself, people often ask me why I still love Adobe Analytics as much as I do. My answer to that usually covers multiple areas. For example, I like how the App Measurement Library in Launch helps me to collect data efficiently. Analytics’ Processing Rules and Marketing Channels are another great tool to enrich our events after the collection. In a previous post, I already explained why I love prop-type dimensions quite a lot, since they can provide us with metadata on […]
Building the ultimate auto tracking implementation with Adobe Experience Platform and Web SDK
I think it’s no secret that a lot of companies, agencies, and analyst dread the amount of effort it takes to implement a sophisticated analytics tool like Adobe Analytics. That may come in part from the correlation between company size (and thereby business complexity) and choice of analytics tool, but it is quite clear that implementing Adobe Analytics in a way that fully utilizes both all of its countless features and what can be collected from a page is a challenge to even the most experienced specialists. This is where other tools like Google Analytics or smaller solutions like Matomo have their place. If your use case and business situation are right, they may be a quicker solution for you. The simplicity is quite tempting but would not be enough for larger businesses. That leads to a funny situation when people from agencies or small companies join a large corporate […]
Using Flow and Fallout Visualizations like a Rockstar in Adobe Analytics
It’s no secret: I love Analysis Workspace. In fact, I think it is the main advantage Adobe Analytics has over Google Analytics. That is because Workspace allows for seamless collaboration between analysts, marketeers, product owners, and other business stakeholders. With enough enablement, there is no difference in which tools different groups of analytics users would use: It’s always the best one! Workspace is the perfect combination of sophisticated functionality and an appealing user interface. But because of this user-friendly interface, not every advanced function or use case is immediately apparent to every user. This can lead to funny situations, where experienced analysts never really use certain parts of Workspace that could save them a lot of work. In today’s post we will take a close look at two of the most undervalued features: The Flow and Fallout visualizations. While they seem quite similar in functionality and trivial to understand on […]
(Time-)Normalize Performance over time in Adobe Analytics’s Analysis Workspace
In Digital Analytics, one of the most common requests from business stakeholders is to compare the performance of two or more items on our websites, like marketing campaigns or content pages. While it is immediately obvious why this comparison is important to the business, it quite often leads to graphs like this, where the analyst tries to visualize performance over time: This solution is technically correct but makes it hard to really compare how both pages perform in direct comparison with each other. They went public on different dates and while Page A is rather stable in regards to traffic, Page B got a boost at around the middle of its time online. So, how do we make this simpler? When enjoying my free time between jobs, I caught up on some older videos from the Superweek Analytics Summit’s Youtube Channel. In 2019, Tim Wilson demonstrated how to align dates […]
Cool Approximate Count Distinct Use Cases – Adobe Analytics Tips
One of the things that really sets Adobe Analytics apart from other solutions is the ability to create sophisticated Calculated Metrics and Segments on the fly. You don’t need to be a highly trained Analyst or Data Scientist to create your very own set of Measures and Dimensions unique to your business question. The best thing for me personally is that we can create those metrics from the same interface where we do our day-to-day analysis and reporting. It doesn’t matter if we want to quickly create an average or build advanced time series analysis dashboards, it’s all right there at our fingertips. Today I want to tell you about one of my personal-favorite functions called Approximate Count Distinct. This functionality allows us to count how many different values from a dimension we tracked and use that number in both Calculated Metrics and Segments (making this function the closest we […]