This past Thursday evening I went to an event at Mistral in Boston hosted by an Internet consultancy named Molecular. Molecular began its web business in the mid-1990’s. They “did” Fidelity’s first website. That’s cool stuff in my book. Since then, they’ve done so much, and are now linked by Isobar.

My favorite part of a Molecular event is the opportunity to listen to smart people speaking about Internet innovation. Not to mention the fine food, good wine, and bright sommelier (who digs the first growth)… From a semiotic perspective, such a well-planned and engaging evening tells me a lot about Molecular as a company: focused, creative, organized, smart, connected, and successful.

So why I am telling you this on an analytics blog? Well, the evening’s topic was “user generated content”:

Today, technology has given customers control to determine what messages they will listen to and when they will listen – as well as a means to let their own voice be heard. This may be difficult, as it is much different than what we are accustomed, but denial of the customer voice will not make it go away - it’s only getting louder. Only marketers who can learn to adapt will remain successful in the jungles of untamable content.

Effective marketers must learn to utilize user-generated content to their benefit by creating authentic, positive, and valuable ways to engage customers in a “conversation” and incorporate their voice. During this provocative discussion, panelists will share their insight on this concept, its challenges, and benefits. These marketing experts will share their real world experiences and insight into such issues as managing, surviving, and spinning negative content, as well as maximizing the advantages of the positive.

UGC is powerful stuff. The mainstream internet and media meshing has made it unavoidable. Has what I said influenced your opinion about Molecular? Made you want to eat at Mistral the next time in Boston?

So how do you measure User Generated Content? That was the question I asked to the speakers from Reebok and TripAdvisor at Thursday’s party.

The good news is that both companies claim to use web analytics to measure UGC, and, like everyone it seems, looking to do it even better. That means making better use of existing data, deploying or upgrading technology, and/or extending their data model.

So I was thinking about making better use of existing data by working with and segmenting metrics and dimensions.

UGC dimensions could include:

• Event:
  • Post
  • Comment
  • Interaction (with types: play, pan, zoom, edit)
  • Contribution (with types: mashup and file)
• Visitor
• Persona

UGC metrics could include:

• Value scores.
• Counts of inbound/outbound links and new/return/repeat visitors.
• Search metrics, like organic search visits and visit rate.
• Time-based metrics, like total time online per visitor and average visit frequency and duration. 

When the web analyst creates this type of mental model for measuring UGC, selecting new technology or working with your geeks to extend the data model becomes more a lucid, focused activity.

For example, I could take a look at some cool UGC and:

• Value score events subordinate to the page view.
• Value score an engagement level of those events.
• Multiply the two together to generate a type of engagement metric.
• Identify the “Event Path” with the highest engagement.
• Identify the “visitor” or “visit” with the highest engagement. 

Then I could wield the extended data model in my analytics tool to identify the following online behavior and better understand my UGC during a period:

• Ratio of:
  • events:visitors
  • events:visits
  • contributions:visitors
  • contributions:cookies set
  • visitors:personas
  • comments:new posts
  • comments:existing posts
  • posts:visitors
  • comments:visitors
  • mashups:visitors
• Percent of:
  • high/medium/low contributing visitors
  • high/medium/low interacting visitors
  • high/medium/low engaged visitors
  • new posts
  • new comments
  • new mashups
• Number of:
  • events per page
  • interactions per contribution
  • comments per post
  • mashups created
  • linked posts
  • contributions per persona
  • visitors per persona
  • total events by post, comment, contribution, interaction

I know I could create other derivatives and use other metrics too. Events, like Interaction and Contribution, need more edification in future posts, but I think the beginnings of this model are clear.

The User Generated Content revolution doesn’t just affect Web business. It’s becoming part of modern capitalism whether you make sneakers or sell ads. This revolution is making web analytics an even more critical process in your value chain.

One of the web analytics bloggers in my blogroll is Robbin Steif.  She runs LunaMetrics, leads the Marketing Committee for the Web Analytics Association, and was even recently elected to the Board of Directors for the Web Analytics Association.  Her history includes an impressive set of initialisms: IBM, HBS, MBA, CFO, CEO. 

A few weeks ago she invited me to guest blog on how to measure Rich Internet Applications and enable event tracking. The post evolved into a three-part series:

• Rich Internet Apps for Beginners, Part I of III: What is it?
• Rich Internet Apps for Beginners, Part II of III: Google Analytics
• Rich Internet Apps for Beginners, Part III of III: Unica

Check Robbin out at Emetrics in San Francisco.  She’s going to tell you how to put your best foot forward and understand the wild, wide world of web analytics.  And, if you’re lucky enough to attend Emetrics, also come see me and Ian Houston on Wednesday, May 9th.  We’re going speak about Web 2.0 analytics and present a conceptual framework for measuring all the new and cool stuff going on today.

American’s don’t want to hear about audits in April, so I can only imagine how comScore and Nielsen felt after receiving that letter from the IAB. 

The letter made salient points.  It was “right on.”  While audience panel measurement is a time-tested method for deriving conclusions about “audience,” it must evolve beyond current maturity to fit today’s Internet.  The long tail, cookie usage, and impact on b2b traffic measurement can’t be rolled up into a bunch of people “at-home” visiting one portal site and using one ad network.   “Event” tracking, rich internet, digital video, and connected device measurement make it all even more difficult.

Panel selection must avoid coverage error and selection bias.  And that seems really hard, to me, to do on the modern Internet.  I’ve heard rumors these panels tend to self-select, offer participation based on incentives, or random dial yr digits.  Well, ah, see, I’m too busy. I buy what I want.  I have two cell numbers, three laptops.  Those methods missed me.  And guess what?  I use the Internet too.  A lot. 

So the question must be asked, do existing methods for panel measurement frame judgment samples leading to nonprobable data? 

Well, I don’t really know and I sure hope not.  comScore and Nielsen are good companies, but I’d sure like to learn more about what goes on inside. 

The panel measurement that will “win” in the long run is the company that understands it’s just one, external, metrical input into an online company’s value chain.  The internal metrics are another input (and output), and one much more valuable because I can reconcile them.  If questions arise, I can identify the derivation of my internal numbers and release that data for auditing by IPRO or ABCi or processing by any number of vendors who want my lucre.  External metrics are the Web’s dark matter.

I’ll propose that the smart option for companies with the ambitious goal of measuring the entire Internet for everybody everywhere is to think with “open” in mind.  What that means is take that black box methodology and make sure it’s simply:

-
Radical, I know.  Otherwise, we’re left with the “damned statistics” and the perception of the first part too (lies, lies).  I have no way of knowing if comScore’s recent data is representative of the Internet population or if the data is simply representative of the “frame” they sampled using whatever clever method.  “Trade secret” or “proprietary,” but certainly not standard or open. Even the answers to Eric’s questions left more questions.  

A band named Pavement once sang “questions are the answers to questions in themselves.”  It sure sings true here.

• Hello there! My name is Judah. Welcome to my new blog!

When Eric invited me to blog under my own name @webanalyticsdemystified.com, I thought it would be an excellent opportunity to contribute to the global web analytics community, providing a voice from the East Coast of North America. I live outside of historic Boston, Massachusetts, in the United States of America.

I’m the Director of Web Analytics at a large media company with more than one-hundred informational, navigational, search, transactional and data-driven websites. I stay active in the industry and am currently a member of the Web Analytics Association (WAA) and the Interactive Advertising Bureau (IAB). I have an MBA and an MS in Finance. Besides the “web” and “analytics”, I enjoy technology, music, art, exercise (biking!), the outdoors, and the Red Sox.

Here’s my deal with you, I’m going to do my best to ensure my blog is:

The title quote above, however, is from Johann Wolfgang von Goethe.

Stay tuned to this URL. Add me to yr aggregator. Leave me a comment. Drop me a line at judah@webanalyticsdemystified.com.