In my last post on data visualization, I had a couple tools recommended to me to try out. One had a limited trial period that I didn’t take advantage of in time, and the other, a tool by VisualizeFree, was too buggy to work. I uploaded my data easily enough (still had to clean it up first like some other ones), then I can’t view the actual visualization. Lame.  I could email support, but I’m too lazy to do that again.

I think I got more out of reading this article on what is (or should be) the point of data visualization.  Its based on a talk given by Manuel Lima of VisualComplexity.com, who curates that collection of data visualization examples and resources.  The main point from Lima was this:

“We need to make a transition from tools of curiosity to tools of functionality.”

Which is true, there are many tools that provide interactivity but not much substance. On the other hand tools for fun or aesthetics only can also drive innovation. I’m torn. It seemed like a lot of people were disagreeing over separating “information art” from data visualization, but this article states it more eloquently than I can. Manuel Lima also listed some key principles for data visualization that I did not know and should probably keep in mind:

form follows function

start with a question

interactivity is key

cite your source

the power of narrative

I’ve become much more judgmental toward charts and graphs thanks to blogs like Junk Charts, Flowing Data, and Simple Complexity.  So when I tried out one of the many Twitter measurement tools, Graph Edge, and received my first report, I was confused by the charts.

Followers and "Legitimate" Followers

This graph shows my Twitter followers and “legitimate” followers (they have a definition for it). Because the lower limit of my y-axis is the number of legitimate followers, it gives a false impression of having a very low number of legitimate followers. Why not start with 0?

Net Twitter follower change

This line graph shows the follows, unfollows, and net follower change over time for my Twitter account. But I thought it was strange to include negative numbers, because it looked like I had negative 1 unfollows. Anyway, there’s room for improvement here.

Misc.

Today I created a Twitter list for #measure and web analytics people (like @ABTests did) on TLists. I think the value is that its curated so you can see recommended people who actually tweet about web analytics on a regular basis, and you can follow many people at once/discover new people. It may not be worthwhile once Twitter implements lists though. And I successfully integrated my GWO data with GA thanks to this post from the GWO Tricks blog!

Lately I’ve been seeing a ton of new data visualization tools/experiments that I thought were worth sharing. One is not really applicable to web analytics or reporting, but others are.

Trendly

I saw a post about Trendly on the Google Analytics Blog, its an application that leverages GA data to display it in a way that is supposed to help you understand the data better. From what I can tell, they use statistically significant numbers (between the upper and lower control) to show a trend-line that is less jagged and crazy. I think that is helpful for noting the big picture of change over a longer time span, but less so if you want to do a deep dive. Which might be besides the point. And then their other graph shows time vertically (I’ve always had issues with that metaphor), and the percentage of traffic from that source correlates to thickness. Its easier to show than tell so here it is:

Trendly time graph

Darwin’s Origin of Species

This is the English major in me geeking out, but I think this changing textual visualization by Ben Fry (go to the site to see it in action) is a great way to show how different editions of an important book like this can change. I’d like to see it for Lyrical Ballads. This is from the information aesthetics blog again, but I think its cool.

Darwin visualization

California Stimulus Map

I should probably find some more data visualization blogs, but I like the information aesthetics finds so much. This interactive map by Stamen Design shows where stimulus money is being spent in California, and what kinds of projects it goes to. The subject matter is worthwhile, but mainly I liked the vertical graph on the right side, I find that visualization easier to duplicate (in Excel!) and translate to different data sets than the one in Trendly. I will try to sneak it into a report at some point, and I’m sure I will get a WTF reaction, but it would be more interesting than the standard Excel graphs for me and the reader.

CA stimulus map

Otherwise I am having fun with my new G1 phone, new running shoes, and I’m going to Arizona this weekend–good times! Hoping to get some hiking in if it is not over 100° outside.

Thanks to those who participated in the poll! I took a 2-week hiatus from writing in the blog because I kind of just got lazy. So there is a tie between writing a post about optimization and data visualization. When my sister found out that her puppy was on the ballot, the puppy faction mysteriously got a lot of votes within 1 hour. She pretty much openly admitted that she voted a few times for Bentley, but on the off chance that someone else voted for Bentley, I’ll dedicate a picture or 2 to him. First, is a comparison of 2 data visualization tools: Tableau and Swivel.

Data Visualization Tools: Swivel and Tableau

I decided to try Swivel mainly because I could access it without having to download anything, it’s free, and seemed like it had an easy-to-use UI.  Those are also the main benefits to using this tool, overall I didn’t think it was a huge step above using Excel. I guess I was expecting more utilization of Flash or interesting visualizations instead of standard charts and graphs because it was in a web environment. Basically you just upload the data, and then you have to “clean it up” so that Swivel can work with the data, and then choose colors and font/pixel sizes. I tried to take out some of the words in my chart so that I could use a readable font size and not have overlap, but now they are overlapping again. They did have a lot of options for embedding and sharing, so that was a plus. Overall it was a “meh” experience. Here’s the final chart that’s supposed to be of Browsers and OS:

Tableau is a software application you can download (I’m using a 2-week free trial), that does cost money. For personal use its a bit pricey, but maybe if all you did for fun was manipulate data into different graphs and charts it would be worth it. I thought they had some interesting visualization options, like heatmaps and text graphs with corresponding color and size variations. For me there was a steep learning curve, and a lot of options for customization that I wasn’t sure would be useful to me. Its a fairly simple drag and drop action to set up the axes, but I found myself performing actions by clicking on things and not really being sure of what I had just done to change the graph. It would have been nice to have a history of actions for people like me who just click on stuff. Still, I wasn’t blown away by the graphical representations in Tableau either. I guess its hard to be impressed by these visualizations when I read about innovations like this.

Tableau Heatmap

Forgive me for the continued alliterative titles.  So I have a bunch of things I’d like to write about at the moment but not much overlap.  I’ve had Tableau recommended as a tool to use for data visualization, Avinash posted on trying out other web analytics tools on your own blog, and I just want to try out optimization for fun. My sister’s puppy is adorable, but not totally related to most topics on this blog.

For those of you kind enough to read and/or participate, what would be more interesting:

Yay for alliterative titles. As I watch the new season of the Real Housewives of Atlanta, I also have to think about a web analytics reporting challenge.

Imagine you have a large, complex website with data pulls for monthly scorecards/dashboards, but the stakeholders viewing the scorecard have diverse, possibly mutually exclusive interests. For instance, one stakeholder might want to look at visitors to one section of the site, and another only wants to see the number of downloads for a different section. And you have to create one scorecard (for some reason I was just reminded of LOTR “one ring to rule them all”) to make everyone moderately happy.

Do I argue for creating more specialized scorecards or try to make a one-size-fits-all report? If I do choose the 2^nd option, do I try to include basic traffic reports along with a few more specialized metrics? I could also make the executive decision that a metric like average time on site is a metric that will not lead to actionable insights, and replace it with one of the stakeholder’s ideal metrics. Probably no one will be 100% happy but we’ll see how it goes. I’m open to suggestions.

Here’s the latest cool data visualization found on information aesthetics that shows a tool leveraging media aggregation and overlaying it on a map of New Orleans. Pretty cool, but kind of confusing. I’m also looking for data visualization tools (free and online accessible preferably) to try out with my own data sources–any recommendations?

Citymurmur New Orleans

Seattle finally cooled down, which is nice because I have a gross bruise on my leg from soccer that no one should be able to see.  Also I’m excited for Web Analytics Wednesday this week!

The reason I keep posting about data visualization is not just because I think these things are pretty or interesting, but I think the things you learn about data visualization are directly applicable to reporting in web analytics. People are always decrying the “data puke”, and I’ve seen scorecards that range from Windows 95 looking spreadsheet to graphic designer Excel masterpiece. I am hoping to end up somewhere in the happy medium, where you marry design with data in a way that it helps show the reader what is important and what is actionable.

Definition: A scorecard is a visual display of the most important information needed to achieve one or more objectives, consolidated and arranged on a single screen so the information can be monitored at a glance. Unlike dashboards that display actual values of metrics, scorecards typically display the gap between actual and target values for a smaller number of key performance indicators.

I don’t think Excel was originally envisioned as an application where form matters as much as function, but I’m trying to learn how to manipulate spreadsheets to make them look more attractive. I haven’t found many resources yet on how to do this, but already I see parallels to web design/graphic design. A scorecard is a visual presentation similar to a page in a magazine or a book–maybe it would be useful to take a page from that field and create mock-ups/wireframes in Adobe InDesign or Illustrator before you just start throwing data in?

This would require taking the time to learn the program (which is not going to happen for most), but I do think its worth thinking about it from a designer or information architect’s point of view. For instance, how do people read things online? They scan web pages in a F-format generally, put the most important things along that F shape if you’re sending an online copy of the scorecard. Maybe its too much effort put into something that you just have to get done and not fixate on design, but the designer in me thinks that creating a well-designed scorecard and consciously thinking about how the audience will read it (user-centered design), might help the client understand and agree with you.

I think Shane Atchison might disagree slightly with me. Am I completely right/wrong? Let me know.

Omniture

These topics may not be entirely related, but I am making them related because I don’t want to devote an entire post to each one. Between playing with Bentley and watching reality tv on Bravo, I played around with Omniture, an enterprise tool for web analytics.  I read some about page tagging variables in Omniture, but I’m not quite sure I understand when you use eVar versus sProp for every situation. Because my primary experience is with Google Analytics, what I’m noticing so far is the difference between the 2. Main things I’ve noticed:

1. Omniture has way way more metrics that can be measured with a lot of granularity.
2. Google Analytics has a better UI and is more concerned with making things easy for the user (novices especially), so metrics like bounce rate are automatically calculated for you.
3. I like the visualizations better in Google Analytics and the site overlay tool helps to show click maps visually on any page in the site.
4. Omniture might help make more informed decisions because it is drawing so much more data and aggregating it for the user.

Overall I think I will grow to like Omniture more because it is so powerful, but I wish that they would include some of the better visualization tools from Google Analytics, or calculate bounce rate for me. Maybe that is asking too much, but from what I hear, free tools like GA are catching up to Omniture and WebTrends quickly, so they might offer the same things eventually.

Google Fusion Tables

I had never heard of Google Fusion Tables before, but that might be because its in Pre-Alpha right now. It basically takes data sets from things you import (like spreadsheets/csv files) and uses different visualizations like the ones in Google Analytics and Google Maps.  One cool part of this new tool is that it allows collaboration and you can combine other tables if they have the same columns (because its probably treated like tables in a database). They also allow sharing of certain sections (like database views I’m guessing), and easy online publishing of the visualization.  There is a lot of potential to use this in web analytics I think, but so far I found the visualizations and UI to be somewhat confusing to manipulate. Below is a motion chart showing predicted temperature change for the US.

DD4D

Finally to continue the visualization fixation I have, I found a cool blog, information aesthetics, that posted about the DD4D (Data Designed for Decisions) conference. There were some cool things, but what I thought was most interesting was a way to show the overall change in various factors of a problem, which predicted an end result. It would be interesting to try, but I’m not sure how you assign numeric value to subjective things in a meaningful way.

DD4D Sense Change Making Visualization

Wow. Longest post ever. So now I’m going for a run to not think about web things for a little bit.

So in my continuing quest to figure out new ways to visualize data, I came across this article through The Grok, (which I realize is from 2007) in Smashing Magazine on new and interesting approaches to data visualization.  I tested some of them out and I wanted to share and post pictures of the results (though some are better when in action than still).

1. Amaztype.  These people utilize Amazon Web Services to make a word of your choice based on book/album/dvd covers. You can sort of see the graphic design trends that people follow. I especially like that Goodnight Moon made it onto the Night visualization.
   

   Night

   

   Light

2. Death of the Pie Chart.  Using pixels instead of pie charts to demonstrate relative size. I like it.
   

   Pixel graphs

3. We Feel Fine.  This site does amazing things to get a sense of how the world is doing by “harvesting feelings from weblogs.” You can filter based on feeling, gender, age, weather, location, and date for 6 different ways of viewing the data. I tried out Madness, Montage, Murmurs and Mobs.
   

   Filtered Madness by the feeling "sad", possibly about Michael Jackson.

   

   An image from Montage.

4. Websites as graphs.  Graphs by the HTML code, so tables, links, images, etc. get different colored nodes. I made a graph of this site but I didn’t think it looked too interesting.
5. Book/essay word visualization.  A German Interaction Design Institute wanted to show the connection between words and ideas better and made an awesome sort of Venn diagram. One pretty much includes everything that I learned at the iSchool, and some extra German words tossed in.
   

   Visualization of words in an interaction design text.

6. The Shape of Song.  Graphical representations of music. I did one for Chopin’s Nocturne in E flat.
   

   Visualization of Nocturne in E flat.

7. Visual Complexity.  The mother lode of data visualization, a large gallery of different types. I was really fascinated by the transportation ones.  The ones I’m showing here are of the global internet distribution and the blogosphere from “inspirer” radiating to “inspiree.”
   

   Global internet distribution

   

   Blogosphere from inspirer in the center radiating to inspiree.