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

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!

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.

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.

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.

Page Tagging

As promised, I said I would post about social media and page tagging. Even though I haven’t done much page tagging outside of Google Analytics, I had a few discussions about it at ZAAZ this past week.  Omniture and WebTrends have some structure around the variables you can tag links/onload events within a page, such as campaign variables and traffic counting variables.

One co-worker showed me her process for keeping track of what she was tagging and how you could use the tags for a variety of purposes when thinking creatively. She had to create a data dictionary to keep track of what she was tagging and why she was tagging it that way for herself, the developer, and any future people working with these pages.

To me this seems like a less than ideal system, and the information science training kicked in and made me think that there should be some kind of taxonomy or controlled vocabulary for page tagging within a company or group.  At least on a project, or in the long term, it would make it easier on everyone if people were naming their variables in a similar way, especially if someone has to decipher your tags later.  It seems almost necessary for Google Analytics, where the user has complete freedom in naming each part of the event tracking tag. I will want to discuss this idea with other people, maybe there’s some obvious reason I don’t know about that prevents people from creating a taxonomy.

Social Media

So I won’t repeat how to do this because I just followed the instructions on this very useful post, but I created a custom advanced segment matching a regular expression in Google Analytics to track the social media traffic sources as a group.  Very easy to setup, you basically just list all the sources you want to track (e.g. “Facebook | Twitter”). It showed social media traffic as much lower than I expected based on the referrers, especially from Twitter, but I’m not sure why that is. I had an interesting discussion today at lunch in the Microsoft Commons, about whether there is really an ROI in social media, and basically I thought that it was more about brand perception and viral marketing, and he thought you had to rely on organic interest and creating a tsunami effect with your sphere of influence.

Side note: GA now offers pivot tables?? But is rolling them out gradually. I am not one of the lucky first.

Why so low social media?

Other Things

Last night FC ZAAZ 99 lost, 4-2 (I think?).  It was a frustrating game not because we lost but just the playing style and some of the issues that come when playing with new people and boys. I felt like I was running like a maniac all over the field and not getting the ball enough to make it worthwhile. Also how ghetto does a high school have to be when they lock their toilet paper dispensers to the wall?

Today I officially became a real person at Microsoft because I show up in the system and have my ID badge. So now I’m not just a pseudo-person getting locked out all the time.  I’m working on a laptop that runs Windows 7, and so far I really like the new features. Then I got to play with a Surface table for the first time, which was very exciting after all of the videos/discussions/projects I’ve worked on this year that relate to it.  It does work pretty much as I thought it would, though this one was not interacting with devices.

Just for fun, the Microsoft Surface parody video:

I’m really tired so this will be the quick and dirty version as my geometry teacher used to say.  Today was a really long, but really productive day from a personal and work perspective.  I will summarize below.

1. First group lunch with a bunch of people from the analytics team. Really fun hanging out and I got to have dim sum, which leads to…
2. First time successfully using chopsticks! I seriously failed at this all my life until today and then I just randomly got the hang of it.
3. Finally put into practice what I preach, and created a wireframe (in PPT) of a scorecard based on what I thought would be a good layout. I tried to include the top KPIs in a prominent location, visual representations of the data, and a clean and simple layout that I think reflects the whole “people read along the lines of the letter ‘F’” thing. Then once I got manager approval I created a more hi-fi representation in Excel. I think its ultimately a time saver like sketching is in UX, if its a wireframe, people aren’t going to ask me to change every box line and color, and will pay more attention to the organization and structure.
4. Got to play with making advanced segments in Google Analytics for social media. Will probably post more on that at a later date.
5. First time eating cocktail buns, which sadly, do not contain alcohol.
6. Rode on the new Seattle light rail in the tunnel. It was very fast, clean, and convenient! Now if only it went to more useful places…

Now I just want to sleep, but I am moving this weekend, so I must pack instead. And tomorrow is the first day at Microsoft (due to bosses being on vacation forever), and game #2 for FC ZAAZ 99!