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:

Ok yes I am being a baby because I’m not used to the weather, but its really hot for once in Seattle, so I feel uber lethargic. I think I’m typing at about 40 wpm, that’s how lethargic I am. Pyramid beer probably did not help. Below is a picture of the weird clouds hanging out now that we have crazy hot weather, courtesy of Cydne.

Today at work finally gained some momentum on a project, got to do some event tracking, and figured out how to get rid of those pesky parameters appended to the end of URLs in Google Analytics like: “sarahdeatley.com/index.php?id=13c4eb92kp“.  Sometimes they are useful for tracking different content within a site or for campaigns, but other times its the same content, and yet you’re seeing 20 different URLs that all are the same page.

I thought that you’d need to create complicated filters to accomplish this, but turns out its a really simple fix in the profile settings. Its easy:

1. Click “Edit” when viewing profile settings.
2. Click “Edit” in the first box that says “Main Website Profile Information”
3. Enter the offending URL Query Parameter in the form. So in the example above you would enter in “id.”

Yay for simple solutions, but if you have more complex needs, see this post by Justin Cutroni. Or if you need web analytics inspiration in general, read Avinash Kaushik’s latest post.

In other news I discussed my page tagging ideas with someone at work, and found out that the excessively complex page tagging is mainly in Omniture, and not so much WebTrends.  Basically we decided that controlling too much of the tagging limits creativity, but lack of documentation/control can lead to a chaotic mess.  We also talked about the advantages and disadvantages of automation in extracting data from reporting tools.  We both find the idea scary, but I know there are others who think its key to having more time to focus on analysis. I’m too hot to figure out an answer. Someone else should do it for me please.

I was minding my own business, looking at some data in Google Analytics, and then I realized that one data set pretty much was a perfect example of the long tail. A) I was excited that I even recognized it when looking at a table, and b) I didn’t know what it really meant, but I did think it would be important to investigate.

General definition: increasingly shifting away from a focus on a relatively small number of “hits” (mainstream products and markets) at the head of the demand curve and toward a huge number of niches in the tail.

SEO definition: lots of key phrases individually account for little traffic by themselves but collectively all those key phrases often could account for a huge amount of traffic.

long tail example

As usual, I first turned to the Occam’s Razor blog for answers, and it seems like the long tail can mean different things in different contexts for analytics.  When you are looking at keywords, and there a lot of keywords with small usage that add up to a big percentage, you would be interested in learning more about the tail. The tail keywords tend to be subject based versus branding keywords. So ours might be “Northwest Indians” versus “Burke Museum.”  These keywords could be better utilized in the content of the site if this is what people are searching on.

On the other hand, I was looking at the top pages for a subsite, which Avinash compares to a “cliff” at the edge of the long tail.  You should be trying to move the cliff further along the long tail ideally.  In that case, most people are looking at the head pages only, and very few reach the long tail pages.

Content Long Tail

The overall gist of the long tail examples was that keyword analysis should focus on the long tail, and with content you can initially focus on the head of the tail.  I guess what I’m having trouble with is how you apply this to other metrics, like average time spent on page, or bounce rate.  Are keywords the primary instance in which you want to initially focus on the long tail to get more insight into user behavior?  How do I decide which pages in the long tail to focus on for top content? If I see another long tail, should I just pretend like I didn’t see it so I don’t get confused again?

Last day of work at the Burke Museum. I am sad I won’t get to finish some projects or keep working on things, but hopefully they get a lot of benefits from what I did while I was here.   Mainly I’m excited to start at ZAAZ after I relax for a few days.

So if you were ever wondering how to tell what people are doing on your site, how they’re getting there, or where they are going instead…Avinash Kaushik tweeted this ginormous (but valuable) list of 75 resources that are mostly free: http://designm.ag/resources/website-analytics-toolbox/. I’m still in the process of checking some of them out.  There are a couple cool ones that do heat tracking so you can see what areas of your site are “hot” or “cold”, and are getting the most or least attention.

I can think of a number that the Burke Museum should use, such as one of the rank checkers for Google, but chances are no one will have the time or interest when I leave.  I’m not sure which (if any of these outside of Google Analytics) that ZAAZ uses, but I from what Chris Kerns told me, the tools are fairly interchangeable with variations depending on what metrics you are looking for, or the size of the site.

Here is a really good article that I think explains how important web analytics is to understanding the user, and how it integrates with user experience (which is my ultimate goal): http://www.boxesandarrows.com/view/web_traffic_analytics_and_user_experience.

Also we lost our indoor soccer game last night. Vacca Patrol has gone way downhill with all the flaky guys not showing up. Now I’m trying to decide if I should play soccer this summer or not? Or do bikram yoga instead?

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.