I kind of knew this was happening a week ago, but I didn’t want to post about it until things were finalized. As of November 2nd I will no longer be working at ZAAZ and Microsoft, because I’m moving over to Cobalt to be a web and optimization analyst there.  Cobalt is a Seattle-based company that does digital marketing in most of the automotive space in the U.S.  One of my Microsoft bosses made fun of me for moving into that industry, but I see it as continuing to work on analytics, whatever the client.  And Cobalt just made the Deloitte Fast 500 for the 9th time, so they’re doing ok.

It is a really cool and exciting opportunity for me, and it should be an interesting challenge to deal with monetizing site activity and conversions for cars instead of software. I’m lucky to have the chance to work on both analytics and optimization (finally!), which means I should start brushing up on my statistics now.  If anyone knows of good stats resources/tutorials, let me know!

I’m sad to leave the people at ZAAZ and Microsoft, but I’m glad to have had the chance to work and learn at both places, and I even got to play on the ZAAZ soccer team. Hopefully this transition means my blog posts will include even more interesting and complicated problems from working in a new area.

Twitalyzer Top 100 Most Influential #Measure Tweeters

Twitalyzer rankings for #measure

In other news, Eric Peterson’s Twitalyzer tool ranked the top 100 most influential people using the #measure hashtag on Twitter. And you’re probably thinking “Whatever that means”, which sounds about right. I’m currently #20 on the list, but it only shows people who have been “twitalyzed” in the last 14 days.  When I saw that in the fine print (I initially did not make the list), I ran the Twitalyzer tool on my account, and lo and behold I ranked at #19.

I’ve only sort of tried to understand the Twitalyzer metrics, but like most social media ranking/grading tools, I’m not sure what they define as success is always correct. It was useful for finding new people and for making me feel very important and influential until I dropped to #20 after 30 minutes.

I try to expand my knowledge of non-enterprise web analytics tools through this site. I’ve been using ClickTale and BTBuckets for awhile, Woopra for about a week. ClickTale is an analytics tool for seeing how users interact with pages, BTBuckets is a user segmentation and targeting tool, and Woopra is a real-time analytics tool.

Did I mention they are all free? (Note: with some limitations on free accounts.) I didn’t immediately see the advantage of using real-time analytics unless you were making real-time changes (here’s Woopra’s take on real-time analytics), and I challenged myself to use these tools together to do something cool.

1. ClickTale

In ClickTale I can see scrolling, clicking, and hovering behavior on my blog homepage (but not for other pages).  I noticed that although users scroll, attention is focused on the top 1/3 of the page. This reinforces ideas of user reading patterns noted by Jakob Nielsen and CX Partners. I also noticed a higher hover and clickthrough rate on my top-level navigation.

ClickTale scrolling heatmap

2. Woopra

Woopra dashboard

First, I really like Woopra’s dashboard. Features like seeing your top keywords in a word cloud help give a quick overview of user preferences on that day. You can set up alert notifications for different behaviors, referring URLs, and visitor types. Based on ClickTale data, I set up alerts for pages in the navigation.  At one point my About page was getting increased traffic compared to other pages.

3. BT Buckets

Previously I set up “buckets” that users were sorted into based on actions, referrers, or characteristics–i.e. user segmentation.  Because this was an experiment, I created a test page to do behavioral targeting and generate content tailored to a user segment.

Since a lot of users went from my blog, a landing page, to the about section, I wanted to continue engaging them. BTBuckets has built-in options for what you can change on the page when users from buckets see that page. I chose a shadowbox to appear on the test About page, to greet return visitors with a different message from new visitors…and it worked! (Note: I’m not planning on doing major debugging, so apologies if it stops working for some reason.)

Try the behavioral targeting test page here–you should get a custom message based on if you are a new or returning visitor.

Also try out these tools–they are really great additions to offerings like Google Analytics. I tried doing this for Twitter refers, but that didn’t work for some reason. Next time I would also speed up the process so changes were installed in a shorter timeframe. Overall I just want to make people think about how to combine free tools like these.

BTBuckets buckets

InfoCamp is an “un-conference” that encourages conversations about anything information related. Its supposed to be democratic, unstructured, and low-cost. Its in its 3^rd year (my 1^st year attending and volunteering), and had a great turnout:  350 people!

There seemed to be a good mix of professionals and graduate students, and topics ranged from UX to content development. I met lots of interesting people (which only added to my week of networking after attending Web Analytics Wednesday). The way it works is that people can prepare presentations ahead of time, or on the fly, and sign up to present and discuss an idea. The organizers want InfoCamps to happen in other cities eventually, and so do I.

On day 1 my former interaction design professor Axel Roesler gave a keynote on IXD, and design in general. There was one quote that resonated with me, but I forgot to note who originally said it:

“Design is the reconciliation of seemingly irreconcilable constraints.”

I also saw great presentations on user-centered design and information visualization from Noah Iliinsky, and on user-centered design, optimization, and kittens by Jason Carmel from ZAAZ. I live blogged from day 2 of InfoCamp (sadly I missed Vanessa Fox speaking) below.

Information Architecture and SharePoint

This one was presented by Microsofties, so I was a bit skeptical. I also typically hate dealing with SharePoint, and I’ve done an  IA project with it; maybe I’m just completely biased.

Someone asked about people who want to tag things with more terms than you’ve allowed, or conversely, don’t want to tag things. The answer was “I don’t think that’s a technology problem, that’s a people problem.” Not sure I agree with that. Yes, you need to establish a process that works for your users, but not allowing flexibility and user error recovery in the information system is poor usability practice.

In terms of metadata for SharePoint, their argument is that authors will automatically see the value in assigning metadata to documents and fill in metadata.  I believe unless people are educated in the value of metadata and there is some kind of control applied to what kinds of metadata terms should be used, SharePoint is not as effective.

Hm..and now he’s admitted “[Microsoft SharePoint is] not the best wiki, we’re not the best document and records management system…but we try really hard to make all of these things work together.” Fair enough.

How to start your own InfoCamp

Recommendations from the organizers, Aaron Louie and Rachel Elkington from ZAAZ. There’s tons more info on the wiki.

**NO FEAR**

1. community
2. $ – sponsorship
3. venue
4. publicity
5. logistics
6. personnel
7. social media (see the #infocamp hashtag on Twitter)

Came about from Rachel and Aaron attending IA Summit, and thinking it was good for theory, boring for practitioners.

“The best discussions happened in the hallways and afterparties.” –Rachel Elkington on typical conference experiences

Wanted to bring in the local community and reinvigorate the local ASIST chapter.  They also didn’t like that conference attendance is limited by cost and structure. Both of them wanted to imitate a bar camp format in Seattle and have it be be a movement–a viral form of conference.  The key was finding like-minded people and keeping the conversation going.

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!

As promised, my troubleshooting is done (with Wordpress and GA and Website Optimizer), so I can write about the latest attempt at optimizing something not really worth optimizing.  I was encouraged by a couple people to take the plunge with multi-variate optimization, and I finally did. Granted, its just the work section on this site, so there’s very little conversion, but it works! The steps are not too difficult or different compared to A/B testing, and I liked having the ability to test out a wider variety of combinations.

I kept things relatively simple, and tested 2 variations for the control and test. But I also wanted to go beyond having a pageview as the conversion tested, and instead, I set it up so that time spent on page was the conversion.  I figured if this page were actually getting lots of views, what I would want to test is if they are reading the content there.  Oh so fancy.

ClickTale scrollmap: I want to use this with optimization data

I also liked that I could enter in variation code directly into the Google Website Optimizer UI. Later I realized I should add event tracking to the links, but I could still do that by revising and copying the experiment. I was disappointed that follow-up experiments only allow you to compare 1 combination to the original, so its like going back to A/B testing. That seemed lame, but maybe there’s some secret way around that.

Ideally I would then combine the data from this experiment with other metrics like exit % and pathing to see what that tells me. And maybe scrolling data from ClickTale. Now I want to try these things out on a site with more data! Or on a more robust tool. Hopefully soon-ish.

It’s that time.  Some of these events aren’t until October, but that’s ok.

1. InfoCamp on Oct. 10/11 2009! It’s in its 3rd year, and this year I fully intend to go. From what Rachel Elkington tells me, it might sell out this year, so you need to get tickets soon.  Find out more about this “unconference” on UX/IA/information here.
   

   InfoCamp design by Aaron Louie and Josh Walker

2. Baron Brewing is awesome. Not only are they making beers for the Pillager’s Pub (pirate-themed) in Greenwood, they also have this tiny taproom in South Park only open on Fridays from 4:30-8:30 that I must go back to pronto.
3. The band formerly known as Ladies and Gentleman but now known as The Head and the Heart, is having an art/music show on Sept. 27th at the Jewelbox Theatre.
4. Everyone raves about Fremont Oktoberfest, but I think I’ll skip that in favor of the less crowded Enumclaw Oktoberfest this year on Oct. 9th and 10th.
5. Web Analytics Wednesday is back on Oct. 7th at Cobalt. 3rd time’s the charm for me and hopefully ZAAZ will not have a conflicting party.
6. There is an excellent SEO and GA post on Yoast (unintentional rhyme), on how to set up a profile in Google Analytics just to track keyword positions–not just pages. At first it didn’t work for me, and then it did and I don’t know why. But still, its good to know versus the basic page info you get on Google Webmaster Tools.
7. Most importantly of all…today is International Talk Like a Pirate Day.  To celebrate, here is a pick-up line:

“That’s the finest pirate booty I’ve ever laid eyes on.“

Otherwise, UW beat USC and Cal beat Minnesota!  I spent all day trying to re-educate myself on SEO and figuring out how to insert an Excel scorecard into the body of an email and not have it look janky. It took way too long to get a workable solution for that.

So I can’t really post on anything I’m doing, because I’m doing some troubleshooting on things, but expect posts on multi-variate optimization, a cool SEO hack for Google Analytics, and the ever growing list of data visualization tools I need to try out.  In the meantime, in case you missed it, Adobe bought Omniture today. Below is a model of Adobe’s take on how Omniture will fit into the grand scheme of things, and here is their press release.

Adobe + Omniture model

I don’t have a very strong opinion on this but I’m sure tomorrow my Google Reader feed will have a million posts on it. Everyone at ZAAZ was talking about it when we found out, but it should be interesting to see how they integrate aspects of Omniture page tagging into Dreamweaver and Flash. Hopefully it will be a good thing.

Last weekend I went to Arizona as a birthday trip. Not sure how I feel about all the malls and new-ness, but I loved the landscape, the weather (thunderstorms included), and how friendly everyone was. Some random lady at a restaurant bought our lunch for us on the first day. Didn’t leave a message, just did it. I wanted to go hiking, but I got too scared about hiking in the desert for the first time without a guide. Below are pics of Sedona and Montezuma’s Castle.

Sedona red rocks

Sedona thunderstorms

Thunder and lightning near Sedona

Montezuma's Castle

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.

I finally took the plunge and tried out optimization. I am (literally) surrounded by optimization at ZAAZ, since the optimization team sits near me and I’m hearing about it all the time. I really like the approach that ZAAZ takes, (see here for the ZAAZ process) with viewing optimization as part of a holistic process for website design/maintenance.  Once you analyze the data, you know what parts to improve upon, and optimization prevents blindly implementing things based on what the developer/designer/manager likes best.

All I knew about optimization was that its the process of designing different versions of a page and then testing them to see which performs better.  A/B testing is testing 2 or more different versions of a page (according to Google), while multi-variate testing is testing various sections within a page.  Since I’m a noob, I went with A/B testing in Google Website Optimizer because it is simpler to set up the experiment.

I will preface this with the fact that yes, its a fake experiment that I didn’t put much thought into, and no I don’t actually care about the conversions. Here are the basic steps to setting it up with some notes on my process:

1. Decide what you want to test and how you want to test it.  This is the hardest part I think, though if it were a more important site I would preferably base this on analytics data for underperforming pages, campaigns, or the key conversion funnels. I didn’t care, so I made 2 versions of my usability portfolio page and a super-obvious conversion CTA. I opted to have 50% of visitors see the original and 50% see the test page.
2. Enter in the URLs for the original page, test page, and conversion page.  Easy enough except I wanted to set up 2 different conversion pages, and that did not appear to be allowed.
3. Place the tracking code in each page.  Fortunately this plays nicely with Google Analytics, but you have to be careful about the placement of the tracking code–just after the head tag and just before the closing body tag, and after the Google Analytics code. Then click to validate the tags.
4. Begin the experiment…and wait for the results! It says the results come in within 24 hours, and I’m not sure how accurate that is because as of now I have more conversions than I have visitors. Not sure how that is possible.

Overall fairly painless process, though I’m skeptical about the accuracy of the data I’m getting so far. I think next time I will try out the multi-variate testing though for something more interesting. My colleague Rachel Elkington wrote a great article on combining UX principles with optimization that I also want to try out.

And I seem to not have enough hours in the day to do everything I want, which means the blog posts have been fewer and I haven’t gone running as much. My bad.

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