I was lucky enough to attend eMetrics San Francisco last week, and I have to say, it was one of the best eMetrics I’ve been to.
Typically, these events end up somehow converging around a common theme or couple of themes (without any collusion amongst the presenters!) and this year was no different.
Here are the top things I took home:
1. “Big Data”
Surprise, surprise, talk of “big data” was everywhere. However, data alone is worthless – no matter how much of it you have. In the end, what matters is the insight you draw from it, and the action you take. It’s not about big data – it’s about big action.
2. The Art of Analytics
It’s not unusual to hear about the art and science of analytics, or the importance of visual storytelling. What is unusual is having artists on hand to sketch the key themes from a presentation. This unique feature of eMetrics SF 2012 was not only fun and interesting, but showed just how persuasive the “art” of analytics can be.
This message did not end there. Bob Page stressed the importance of combining creativity with data, and Stephen Few applied the key tenents of information architecture and visual presentation of data to dashboards.
“Data needs to be integrated for a 360 degree view of the customer, blah blah blah, buzz word, buzz word, buzz word.” However, I’m not just talking about data integration, but the integration of different channels into the holistic business goals, and leveraging complementary methodology such as user testing and keyword analytics to enhance analytic insights. The focus this year was on so much more than just the integration of data – it was about the cohesion of all elements of the business.
Not only has the Web Analytics Association evolved into the Digital Analytics Association, but our field is clearly evolving to include a more holistic understanding of data from all parts of the business. In addition, client-side stories made it clear that companies are evolving in their own capabilities. This is a long term process with no magic tools, but this evolution is what we need to drive our organisations, our industry, and our own skills and impact forward.
5. Analytics is everywhere
So why are we evolving? Because, in Bob Page’s words, “Data is everything.” Ryan Zander from Sportvision made for a fascinating keynote at the WAA Awards Gala. (And this is coming from someone who could not care less about sports.) Yeah, yeah – Moneyball made analytics all cool and popular. But the data that Sportvision are using (how one inch can affect a baseball pitch!) and the amazing visualisation of that data, showed that analytics isn’t just something that nerds are doing in their dark basements – it is becoming critical to success in almost every industry, and is being put to amazing use.
What were your key takeaways? Did I miss any?
Related post: eMetrics Tweet Activity
First of all, just so there’s no confusion, let me state that I am giving my own opinions here, not as a representative of Adobe.
I really wish I could have been there, but thank you very much for summarizing what you heard. These are a few of my impressions based on your takeaways:
1) Agreed. The bigger data gets, the more it needs to be distilled down to simple representations in order to make any sense of it. But on the other hand, the map is not the territory, so I think the challenge is, you can’t always distill things separately. Big data needs a big picture, and most things don’t exist in a vacuum. Big data often won’t let you draw your conclusions individually from each of hundreds of different channels, then try to pool those conclusions. Because after you’ve boiled it down from huge raw data to insights, the individual insights are missing context clues, which prevents tying one to another. Sometimes I think you literally need to mix together everything from everywhere into one huge database – and then stare it down for information, in whatever ways you can manage to do so.
2) I am a huge subscriber to the idea of analytics as more art than science. What I like is that people are starting to think of it as a pursuit more than a discipline.
5) As far as the ubiquity of analytics – I’m going to wander off topic. I like a good statistic, but as a data geek I find I often want to examine the source rather than take someone’s word for it. I know I have a bad habit of pointing out logical fallacies, and I like claims to be concretely substantiated. Somehow, I’m more keenly interested in a giant spreadsheet of raw data than in a straightforward statistic. I guess because what bothers me most about the conclusions that get drawn is that once the numbers support a specific conclusion, people tend to leave the specifics behind and fixate on the implications of their conclusions – as if what you know about something on the broad scale (with a margin for error) is more poignant than the nitty gritty details of the thing itself. I, for one, find comfort in having unadulterated details on hand while scrutinizing the final interpretation.
Thank you for the comment Jorgen!
Re: your last point. I agree, and I think that’s why we as analysts need to ensure we are credible. Some people are still always going to be “I need to see the math.” (I have worked with CEOs and EVPs that I knew wanted to see the raw, dirty data, and was always prepared with it.) But we aim to prove our credibility so that they trust what we are telling them, and don’t fear we are ignoring data that doesn’t fit our theory.
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Nice blogpost; looking forward to eMetrics Toronto in my case.
I like your point about integration. It reminds me that it’s still the strength of a tool like Omniture if you compare it to Google Analytics (comparision is made with Google Analytics as it’s the most spread tool).
But, I have this feeling (and it fits perfectly with the change from WAA to DAA) that many companies start to build BI solutions that would contribute to this “integration need”.
On the other, I feel we’re still far from properly done integration as most of the time, WA implementation hasn’t evolved from basic implementation (GA base code) to more robust implementation (var, event, commerce,…)
Prior from thinking about “data integration” should we first think “proper implementation” 🙂
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