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Library Analytics with Char Booth and Paul Signorelli, Session 1 Part 2

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You must have gathered by now that we ’re as interested in results as descriptions. As we’ve overtly said several times today, collecting data is the first step; using it effectively—key word there, everybody: “effectively”—is the difference between a wasted tool and an opportunity grabbed and mined to the benefit of everyone involved. It’s not unusual to hear those who are at the head of the pack saying that if you’re spending money on a web analytics tool, that expenditure should be ten percent of your budget; the other ninety percent is to pay people—your staff, outside experts, anyone who could help—to analyze that data and help you effectively use what you’ve learned. Once you’ve understood what you have, the next step is to effectively communicate the information to others who can change data to positive action.
Let ’s backtrack for a moment. A growing field of interest is “data visualization’—using graphic representations to help others understand what we are trying to convey. The New Media Consortium’s 2010 Horizon Report saw this as an important and growing element of technology in learning, and the 2011 report, which will be released online in February 2011 (http://www.nmc.org/horizon), provides updates on that theme. It takes us to an idea explored at an entertainingly effective level in Chip and Dan Heath’s book “Switch.” The book opens with a story about how someone trying to draw attention to a problem within a company—they were buying 400 different types of gloves to accomplish their work—hit a brick wall until he found the perfect way to draw attention to the situation: collecting samples of every one of those 400 gloves and placing them on a conference-room table so that everyone could see what a purchasing nightmare they had created. So, do we bury people under numbers, or augment them with images? And if we do use numbers, can we do so creatively?
Those familiar with Edward Tufte ’s work (http://www.edwardtufte.com/tufte/index) on effective visual representations are on familiar ground here. We’re far from bar charts and overwhelming amounts of text. With this Gapminder chart, it all comes together with a combination of text, color, decent design elements—those circles that draw our attention right away--and an easy-to-decipher legend. It shouldn’t take more than about thirty seconds for us to see that in 2010, China and India had the largest GDPs in the world. Makes us wonder how we might use similar tools to quickly show those approving our budgets how many people we serve with relatively small amounts of an overall city or county budget, doesn’t it? Web analytics gives us the data, our own creativity combined with visual analytics tools makes that information meaningful. There are other wonderful examples of what Gapminder does at http://www.gapminder.org/downloads/.
Another tool that isn ’t necessarily high on the list of topics to cover in a basic web analytics session, but gives us food for thought, is a tool called the keyword density checker, from webconfs.com. It’s very easy to use and gives us additional insight into what is or is not drawing people to online presence.
Taking a URL—in this case, the URL for the Library of Congress (http://www.loc.gov), we simply paste it into the keyword density checker box and it produces a basic readout of the words—and their frequency—appearing on that page.
If we are trying to draw people to our online photo collections and realize that the words “photo” or “photographs” don’t even appear on the page, we have a great hint as to what we might do to draw more readers onto the site. The next step, if we ’re trying to convince others to take action, is to turn to a tool like Wordle to capture their attention.
Wordle is another tool that moves us from the realm of words as an overwhelming jumble of hard-to-decipher information into words as graphic elements. You can create word clouds similar to the increasingly familiar tag clouds we see on blogs and other websites, play with colors and appearance, and create another of those pictures worth a thousand words—with the words themselves. There ’s no mistaking what is important here…
… or here…
… or, quite playfully, here. More samples are available in Wordle ’s online gallery. The point, we hope, is obvious here. Web analytics, by itself, is information. Web analytics combined with our imagination and our willingness to translate that information into eye-catching displays that can inspire positive action means better results for all of us.
As we move toward our final q&a for this session, let ’s talk about a few resources to keep you going after you leave us today. Avinash Kaushik, in “Web Analytics: An Hour a Day,” offers an entire page of recommended blogs for those interested in learning more about the topic. A great starting point is the Google Analytics blog.
Among the others are Kaushik ’s own “Occam’s Razor.”
A third, Clint Ivy ’s “Instant Cognition,” focuses on visual representations of data to make information more understandable—and compelling—to those receiving it. We hope it will serve as a great complement to a topic we’ve explored with you today.
Those interested in looking at web analytics from a business point of view will find plenty of material in Avanish Kaushik ’s “Web Analytics: An Hour a Day.” The WebAnalyticsLand website, which lists a wide selection of books on the topic, is also a great resource. And the Web Analytics Association is clearly an organization for those who want to completely dive into the topic through a professional membership group. We ’ll leave these up for you while we answer any remaining questions you have, and we hope you’ll join us next week for the second of our two sessions on web analytics.

Library Analytics with Char Booth and Paul Signorelli, Session 1 Part 2 Presentation Transcript

http://www.google.com/analytics/index.html
http://www.google.com/analytics/index.html http://www.kaushik.net/avinash/
http://www.google.com/analytics/index.html http://www.kaushik.net/avinash/ http://blog.instantcognition.com/
http://webanalyticsland.com/web-analytics-books/ http://www.webanalyticsassociation.org/
Char Booth [email_address] blog: info-mational - infomational.com @charbooth Paul Signorelli & Associates San Francisco, CA 415.681.5224 [email_address] paulsignorelli.com
Title slide: From Mollycake ’s photostream at http://www.flickr.com/photos/mollycakes/226843996/sizes/z/in/photostream/ Smartphones: From Csaila ’s photostream at http://www.flickr.com/photos/csaila/3648816968/ Fire Hydrant: From Will Lion ’s photostream at http://www.flickr.com/photos/will-lion/2595497078/sizes/z/in/photostream/ Bow & Arrow: From Melilab ’s photostream at http://www.flickr.com/photos/melilab/2436615256/sizes/z/in/photostream/ Question Mark & Exclamation Point: From Horia Varlan ’s photostream at http://www.flickr.com/photos/horiavarlan/4290549806/sizes/z/in/photostream/ Man at Desk: From Brian Auer ’s photostream at http://www.flickr.com/photos/brianauer/2104054031/ Sleeping at Desk: From Bewarenerd ’s photostream at http://www.flickr.com/photos/bewarenerd/238306029/sizes/z/in/photostream/ Mountains: From Christianisthedj ’s photostream at http://www.flickr.com/photos/hcmedkamera/2291925430/ Molehills: From Stiphy ’s photostream at http://www.flickr.com/photos/somebodysavedme/277634286/ Target: From Ntang ’s photostream at http://www.flickr.com/photos/ntang/21736757 Question Mark: From 姒儿喵喵 ‘ s photostream at http://www.flickr.com/photos/crystaljingsr/3914729343/sizes/z/in/photostream/ Finish Line: From Jerekey ’s photostream at http://www.flickr.com/photos/tyreseus/507244847/sizes/z/in/photostream/ Fireworks: From Express Monorail ’s photostream at http://www.flickr.com/photos/expressmonorail/3096574067/sizes/z/in/photostream/ Math Symbols: From Mykl Roventine ’s photostream at http://www.flickr.com/photos/myklroventine/2332789392/sizes/m/in/photostream/ Gloves: From ARTS ’s photostream at http://www.flickr.com/photos/arts/93481862/ Images taken from flickr.com unless otherwise noted