Data Wallowing

It’s been snowing in the Seattle area and I now live on a very steep hill, so today I worked from home and have been wallowing in website analytics between a couple of sledding breaks.

My data wallows look at everything the analytics reports can serve me: visitors, page views, countries, browser versions, page paths, etc. The more esoteric the data, the more I like it, actually. I tend to find the signals in the extremes: the most popular and least popular stuff. They tell you what to focus on and what to chuck overboard.

I look at the last month, quarter, half-year, and year to get a feel for the trends over time and see how major site updates impacted traffic. I look at the top stats for each bucket and also look deep in the long tail to see what’s hiding. I sanity-check the data against my expectations, like looking at the percentage of non-U.S. visitors to the U.S. site, (it’s always higher than I expect,) and referring pages, (the top entry is really bookmarks instead of search???)

I look at clickmaps of the most and least trafficked pages to get a sense of how the page layout may be influencing clickthroughs.

Then if I have access to it, (at Microsoft I do,) I look at the data of the referring sites themselves to see where the outbound rank is for the site I’m analyzing. I look for customer satisfaction data, customer feedback, planning and marketing data, as well as industry trends for the segment the site’s in.

I search social media and look for positive and negative things about the site in question. I also see what they’re saying about the competition.

Then I spent time thinking about instrumentation gaps and how I can triangulate across or re-query the data sets I do have access to in order to guesstimate the gaps. Examples of gaps that I’ve run into in the past are not instrumenting by content types or site sections.

When I have all this data loaded into my head and spreadsheets, I can finally begin analysis by creating an empirical top task list based on what the data says and compare that to the expected or desired top task list. Further analysis is a topic for another day.

What do you think?

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