IA conference 2009 – Web Analytics and User Experience / WA + IA

I do not know whether you know it, but ...
we had a fantastic and informational weekend in Hamburg

During the whole weekend we had a great spirit - Motivated and inspired speakers and in the majority great talks have increased a general and competent and expert atmosphere.

One of the key speakers was Louis Rosenfeld ...
Lou made an outstanding speech..
He requested for web analysts and user experience people to work more closely together. The consequence would be solid basis for identifying the right design questions, and the power of surprise and vision brought to data.
On the one hand there are the web analysis people. Analysts are often considered to be left-brained and data-driven, unconcerned with the 'big picture', or with the possible benefits of the unexpected. And on the other hand there are “we” – I often here that UX people are just right-brained and unconcerned with anything outside the scope of our plans, wireframes and designs.
Lou Rosenfeld argues that this ought to change, and he's someone who is in a good position to know.

What vs Why
Analytics data gives us plenty of What — how many people visited a site, how many white papers got downloaded, how many service requests got sent in. User experience data gives us the Why — why people failed to buy a product at the order step, why service requests spike on Tuesdays, why some white papers are downloaded so much more than the others.

Obviously, What is useless without Why, and vice versa. To put it another way, looking carefully at data should suggest the in-depth questions that need to be solved so that any organization can meet its goals.

Working Together
Combining What with Why is not easy, and it's not often done. But players like Amazon, eBay and other organizations that live or die by the Web have established that it works. For the rest of us, how can we work more closely together? Lou offered a few suggestions:
  • UX people should get a little more comfortable with numbers. You don't need to know what a chi-square test is.. Leave that to people who really love doing them. But understanding basic numbers like conversion rates, unique visitors versus traffic and purchase funnels is easier than it looks and is really, really helpful.
  • Analytics people should get a little more comfortable with creativity. It's not just that research shows accidents, mistakes and playfulness often lead to breakthroughs. It's that creative techniques such as storytelling are really persuasive. If there's a compelling point in the data, turn it into a story and tell it — that Sally seems to love shopping Thursdays at lunch, for instance. That will make non-experts and creative types understand the significance of the numbers and work to find out why.



To find out more about Lou, visit his web site: louisrosenfeld.com

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