Quo vadis, W4D?

Those of you who have been to the Adobe Summit, or any other big event like it, may have been a victim of post-Summit blues – the feeling when you’re back from a couple of ridiculously intense days of listening, meeting, talking, discussing, and fully committing to one single subject. It is part exhaustion, part buzz, part sadness, part being full of new ideas and plans.

I love it!

Summit is getting bigger each year, partly because new stuff keeps getting added, new pieces of the huge puzzle that is digital or online marketing.

This year, I had a bunch of really interesting discussions about how the growing breadth and depth of it changes the way some of us are working. This directly affects this blogger, and this blog. As a result, I have a question I want to ask you: where do you think this should go?

Historical Documents

When I started with Omniture in 2008, web analytics was still a stand-alone profession. Omniture had just aquired Touch Clarity and Offermatica in 2007, and people like Adam Greco started looking at synergies, aka how could we make those testing and targeting tools work with SiteCatalyst (web analytics).

When Adobe bought Omniture, then Day Software, Efficient Frontiers, Neolane, Demdex, and others, we ex-Omniture people found ourselves in the middle of a huge, ever-growing offering now called the Experience Cloud.

For those of us working in the field, it meant going through a lot of trainings and/or experimentation in order to understand at least the basics of the other parts.

There is a model that describes the skill set of a Consultant: know a little about a lot of things, and a lot about one part of it. The model is represented by the letter “T”.

Obviously, not all people are alike. Some have a broad knowledge, a thick horizontal bar on the T, but not much depth. Others concentrate on a single aspect, a long vertical bar on the T. Some go for some depth on two or more solutions, for a wide, stumpy vertical bar.

Now you understand why I have been banging on about simplicity, standards, and data quality so much over the past years.

Data quality is crucial if you want to use Analytics data in other Solutions. “Garbage in, garbage out” applies here.

And simplicity and standards help those people who want to be operational without having to learn everything about all the solutions they touch. I think that with a decent set of standards, you can get away with stumpy vertical bars as long as you understand the bigger picture.

On, Teb, on!

With DTM and then Launch, the focus of this blog changed somewhat. Where I used to explain a lot about how to deploy Analytics, and why some things were as they were, DTM and Launch allowed me to take a wider look at all things related to deployment.

For a glorious couple of months, I dissected DTM. Launch was simpler (good!), but also opened up the ecosystem via Extensions, so I started to explore those (and there are some articles in the pipeline that explain how the Extensions that I made so far work).

But in terms of deploying Analytics, DTM and Launch made things a lot easier. There is a lot to say, of course, but maybe not enough for 20+ articles per year. The how is simply too simple these days.

There is also an argument that Analytics is a lot better with friends.

When you A/B test, and data from Analytics allows you to a) find the best place to do so, and b) judge the results by a plethora of metrics, you tend to get better results and more value.

The same goes for search and display ads.

Example: if you are a retailer selling shoes, you might be thrilled that showing me an ad led to a purchase, but I have very big feet, and I will probably send them back. Out of 12 pairs of shoes I bought recently, only a single pair was ok.

Using Analytics data to decide whether to bid for an ad for me, or not, you would likely have decided not to. I am pretty sure that you won’t make money selling to me.

People working with AdCloud, Campaign, or even Target, like being able to use Analytics data that way. They also like being able to create a segment in Audience Manager (“returners”), so they can exclude me from most of their marketing.

So, your friendly marketer is likely to talk to you about integrations, or about what you can do to make Analytics work with all the other parts.

Some of that is our (Adobe’s) responsibility, yes, but some sits with you.

To be able to work with other solutions, there are things you must know about Analytics, and things you should know about the other solutions themselves.

Quo vadis?

In the context of this blog, the question is: how far do I stray into other territory? Or do I stick with web analytics and do I go deeper?

I like the overall premise of “web analytics for developers”. This is a) a niche, and b) something that comes fairly easy to me.

In the 90s and 2000s, I was a developer, after all, albeit not a good one. Palm OS has since gone away, and although I haven’t touched a line of C since 2001, working with Javascript feels related. Whether I work with very restricted memory and a simple app model in C, or with Javascript in a browser, constantly c&p’ing from SO, there is a directness to what I’m doing, a quick feedback.

I was able to build a tool on Solaris in 1998 using pthreads just as I was able to build an Extension for Launch using Javascript promises.

I feel at home on this blog. I don’t want to change the “for developers” paradigm.

Should I change the focus on Analytics? Or should I stick with it, and go deeper down that rabbit hole?

Leave me a comment, let me know what you think!