One trend that I have seen in the last few years is the interest of my customers in getting the raw data out of the Adobe Marketing Cloud. More and more corporations are hiring data analysts and these people want all the data they can get. Using various tools (R, Hadoop, Data Workbench…), it is possible to dig deeper into the data to uncover hidden gems or create more sophisticated reports. Today I will explain the raw data from Adobe Analytics, the clickstream data feed.
The Marketing Cloud ID (MCID) Service enables most Adobe Experience Cloud solutions to uniquely identify a visitor. It is the basis of the people identification, as I explained a few weeks ago. But it does not stop here; it provides the foundations for the People core service (aka Profiles and Audiences), which, in turn, provides customer attributes and shared audiences.
Processing rules are basic if-then-else statements to perform minor manipulations of the data. They were added mainly to map context data variables into Analytics variables. However, you can also use them in simple cases instead of a VISTA rule. With processing rules, you can concatenate, copy or set values in Analytics variables. They must not be confused with Marketing Channels processing rules, which are specific for Marketing Channels.
When I was following the Adobe Audience Manager training, I remember that one of the topics I found most difficult to understand was ID syncing. The enablers spent a lot of time using these words and I could see that it was a key part of any DMP. Once I finally understood what it meant, I felt relieved. Today I will explain this concept, in case you are also stuck.
One of the main challenge, if not the most important, of digital marketing is to be able to identify real people. This is the key to marketing objectives like “360-degree view of the customers” or “single view of consumers”. The problem is that web analytics tools track only visitors, so we need to find a way to be able to perform this people identification. Let me explain what options do we have.
I must admit it: I love cookies. I can eat one cookie pack in a couple of days. Therefore, I try to keep my kitchen free of cookies. However, this is not what I am going to explain here. Today I am going to take a step back and, instead of advanced topics, I want to review a basic concept: cookies. I know most of you know fairly well what cookies are. However, if you are still trying to get your head around cookies, I recommend you keep on reading. You might also find useful ideas to explain cookies to other people.
If you have followed my previous two posts, you should understand by now the basics of Analytics segments and its containers. I could write more about the creation of the segments, but today I want to explain one of the features that make the Adobe Marketing Cloud a multi-solution offering: share segments. With this feature, you can create a segment in Adobe Analytics and use it in other solutions, like Audience Manager or Target.
In my last post about the basics of Analytics segments, I briefly touched upon the segment containers: hit, visit and visitor. However, I remember how long it took me to understand them initially. And not only me; some of my clients did not find it easy to learn exactly how the different segment containers work. So, I have decided to explain it in so you can learn once and for all, if you still struggle with them.
Those of you who have been long enough in the Web analytics market, will remember that in old version of SiteCatalyst, there was no concept of segmentation. As an alternative solution, you could use ASI slots, DataWarehouse segments or VISTA rules. However, these solutions were clunky, rigid and, sometimes expensive. The Adobe Analytics segments as we now them today come from the release of SiteCatalyst 15. Initially, the tool was still immature, but over time, it has become more sophisticated and it is still evolving. In this post, I will be covering the very basics of segment creation in Adobe Analytics.
In an Adobe Audience Manager implementation, the first and most important data source is the data you already own. Then, when no more juice can be squeezed from first party data, we switch to purchasing third party data. Finally, in some cases, we go beyond and look for second party data. Today, I will focus on this last resort, which can be more interesting than what it initially looks like.