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!

As you may have noticed, I’ve talked about the new beta from WebTrends before, but I wasn’t able to really talk about it until today now that its been publicly released! I’m posting the press release below for those who are interested, as well as screenshots.

I spent a loooong time playing with the beta and overall I was really pleased with the user experience. Its leaps and bounds beyond what it used to be, and is employing lots of the things I like most about Google Analytics in terms of ease of use and flexibility.  My initial impressions are mainly focused on the UI and UX, and some things might be nitpicky, but I automatically do heuristic evaluations. Blame the iSchool. So in no particular order:

1. The main dashboard for profiles within accounts is great because a) it has a bunch of commonly used metrics (pageviews, visits, BOUNCE RATE (finally!!), avg. time on site), and b) you can easily compare across profiles for these metrics, which is immensely useful!
2. My one complaint about the account profiles dashboard is that the columns have a fixed width, and a lot of the profiles I work with have longer names, which makes it slightly difficult to scan for the correct profile. Maybe I’m just getting a Web 2.0-ish feel and wanting everything to have dragging capabilities?
3. I really liked the default graph for viewing a particular profile (with the same common metrics); being able to see data for any date in the selected time period at a glance is a nice feature. Sadly, you can’t use the same visualization for the secondary metrics.
4. The user can choose between the default line graph, RSS overlay (which I don’t entirely understand yet), table view, and “story” view. I like that there are more choices for data output within WebTrends, and I think the “story” part was intended to make data more accessible, but some people I spoke with worried that the “story” could become an excuse for lazy analysis.
5. Overall, navigation is easy to figure out and to switch between modes/options. In an interesting IA choice, the rest of the metrics are listed below the main div in a flat navigation, but still in a secondary location to the more common metrics. It might be because the less prominent metrics need more space because they involve less numbers and more words?
6. Minor detail, but when looking at a report in detail, or when there is pagination, things look clickable when they should not be, i.e. being able to click on “previous” when viewing the 1st page in a series.
7. I think I was happiest when I could export a report in 2 clicks in either CSV or REST URI. I am always getting errors normally when exporting in the current version of WebTrends, so this was refreshing. I wasn’t clear on why you would use REST URIs (even after looking up what that is) or why you would choose Excel vs. XML vs. JSON?
8. My biggest complaint is with the bugs (expected in a beta) that led to numerous error pages, and no real help for explaining how to do things or why errors were happening. This feels like the bane of my existence the past couple days, but in a new system it seems so necessary to have help documentation easily accessible versus just a brief overview of the tool.

Despite the minor complaints, I think WebTrends is becoming more of a happy medium between the power of enterprise analytics tools and great UX in tools like GA. You can tell that they have spent a lot of time thinking about how web analysts (and non-web analysts) will be using their tool, and I think it has paid off in a great product. I look forward to seeing the beta work out its kinks. Apologies for the lengthy post, but its probably an easier read if you can try out the beta!

Official Screenshots

*I’m too lazy right now to make these photos align correctly. Sorry.

RSS Overlay: Add external RSS feeds and items will group by date snapping to any of the key metrics, providing unique correlation opportunities.

profile dashboard rss

Share to Web Services: Easily generate web service URI’s to embed in applications, widgets, and Excel (for live dashboards).

profile dashboard story

Story View: View data in a whole new way with story view.  This narrative flow with embedded metrics allows for quick comprehension and with a quick copy and paste, a user can embed these descriptions right into an email, presentation, or document.

exporting files

WT Press release

Webtrends Analytics 9 Sets New Standard in Enterprise Customer Intelligence

New On Demand version simply, powerfully uncovers customer insight with a click-to-crunch interface, data-in/data-out API and the industry’s most powerful core analytics

PORTLAND, Ore., – Aug. 4, 2009 – Webtrends, the enterprise customer intelligence company that started the web analytics industry, today introduced its most significant advances in user experience and data integration in its 15+ year history.

Webtrends Analytics 9 makes data the interface. Uncovering customer trends is as simple as clicking on numbers on the screen.  Cross-channel insight emerges from RSS-enabled overlays of company news, sales and other business data on top of trended web metrics.  Key web metrics are automatically translated to plain English text, shared throughout an organization and viewed in any interface.

“Webtrends has created an entirely new user experience that makes it remarkably easy for us to quickly retrieve and provide key decision makers with necessary web analytics data. This sleek new design will provide better top-line perspective while allowing us to think about and leverage this data more effectively,” said Kate Johnson, Digital Relationship Marketing Manager, Kimberly-Clark. “Many analytic providers are lacking in this need so we’re very excited to see the direction Webtrends is going with this powerful new visual interface.”

Webtrends Analytics 9 is comprised of three primary components:

Insight Interface: No Instructions Necessary

The new Analytics 9 Insight interface offers breakthroughs in data exploration and visualization, including:

· RSS Overlays. Quickly determine how other marketing investments are influencing your  web site by visually overlaying data from any RSS feed on top of trending web metrics.  Overlays from Webtrends Social Measurement, for example, provide direct insight into the relationships between web site traffic and activity on enthusiast blogs, video channels and other interactive media.

· Story View. Automatically convert data and metrics into non-technical narratives that offer  written context that graphs and charts can’t. The text can be downloaded and shared as PowerPoint, Word, and other formats.

Data-in, No Restrictions. Data-out, No Fees

Webtrends’ industry leading application programming interface (API) provides self-service access and integration of online and offline data without any added charges:

· Live spreadsheets. Review web site metrics throughout the day in live spreadsheets that anyone can access. Create Excel dashboards with live data in three easy steps.

· Data collection. Uncover cross-channel trends and business opportunities by programmatically sending data from mobile applications, devices and any other standards-based source to Webtrends hosted collection service for processing and analysis alongside your web site traffic and other data.

· Data Extraction. Populate widgets, dashboards and other applications with Webtrends data using reliable, no-cost Webtrends Web Services, built with Representational State Transfer (REST) URLs and other web standards. Or  combine data from Webtrends and other business intelligence tools to create best-of-breeds solutions catered to your business.

Powerful to the Core

Analytics 9 provides all of the core analytics features customers depend on with Webtrends On Demand, including:

· Unlimited scale, capacity. Distinct and fully redundant data collection, analysis and rendering help absorb even the largest spikes in traffic without system outages or lost data.

· Unmatched data flexibility. Unlimited dimensions and measures based on any attribute or parameter let you explore your data without restrictions or incurring extra charges.

Analytics 9 is available for purchase beginning today. Current Webtrends On Demand customers have access to Analytics 9 at http://Insight.Webtrends.com.

“I am enormously proud of this release.  It represents a commitment we made to our customers just last April at our Engage conference —we are the most Powerful, we are the most Open and we will be the most Elegant solution in the market.” said Alex Yoder, CEO of Webtrends.  “Analytics 9 turns the page for an entire industry that has just been focused on reporting and brings the depth of the data that Webtrends uniquely collects to life for the entire enterprise to analyze and take action with.”

Learn more about the breakthrough features of Analytics 9 (including screenshots)

About Webtrends Inc.

Webtrends is an enterprise customer intelligence company that turns online and offline data into understanding. Webtrends delivers the industry’s most recognized search engine marketing, visitor intelligence, and analytics solutions to enable companies to understand their customers, drive engagement, and enhance marketing and brand awareness. Thousands of global organizations, including Microsoft, Reuters, General Mills and Ticketmaster have chosen Webtrends business solutions and client services expertise to optimize their customers’ online experiences. You can learn more about Webtrends products and services at http://www.webtrends.com/ or call 1.877.932.8736.

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.

I think its only appropriate that in honor of my father, an accountant, that I spent the day BBQ-ing and playing with Excel.  Apparently in web analytics, reporting tools gather the data, but you manipulate or “do cool stuff” with it in Excel.  So I now know way more than I ever thought I needed to about PivotTables and such (which will come in handy at ZAAZ). Excel 2007 does seem to make it pretty easy to do all of the basic things like calculating sums, but I have a sneaking feeling that I will be doing more complicated things than this.

I should probably be focusing equally on data visualization (i.e. charts and graphs), because that’s how I’ll be getting my point across to clients.  Avinash Kaushik says that the best visualizations come from:

“1) a deep understanding of the goal / objectives 2) from thinking beyond what standard trend lines or stacked bar graphs can provide.”

I tried to emphasize my points in my last 2 web analytics reports for the Burke through varied and clear charts and graphs, but I haven’t gotten feedback yet on those.  I think the challenge is in making the numbers tangible without inducing death by bar graph. I tend to understand things better through words, so it requires creative thinking for me to not rely on rhetoric.

First day of summer in Seattle.