At some point in the career of a web analyst, you will be asked to investigate, assess, and possibly judge the current state of how a company “does” web analytics.  What are some of the areas you should ask about?  Here are some thoughts and a few questions to ask to help inform your analysis (and grease your mental gears):

• Business strategy.  Why does the organization do web analytics?  What’s the goal of having a web analytics team?  Who defines the strategy?  What is the strategy?
• Analytics organization and team structure.  Who is the chief owner of web analytics?  What does the analytics team look like?  How has the team structure been formalized in the organization?  Is the web analytics team effectively staffed and have enough control over resources to do the job?
• Process.  What analytics processes have been defined?  How does a site or site feature progress from not being measured to being effectively measured?
• Data collection. What methods for data collection are being used?  How much data is being collected, and for how long is it stored, and at what level (i.e. detail, aggregate)?
• Reporting.  What data is reported?  What do the reports look like?  Who creates them?  How are they distributed, and in what format?  To whom?  When?  How?
• Analysis.  What’s the difference in this company between reporting and analysis?  How is analysis communicated to stakeholders?  When?  How?
• KPI’s.  What Key Performance Indicators are you measuring?  How are they relevant to the business?  What actions have people taken from KPI analysis that improved business performance?
• Segmentation.  What audience and customer segments exist?  What audience and customer dimensions and attributes are segmented?  Why are they meaningful to the business?  What has the business learned and what action has been taken from the current segmentation analysis strategy?
• Technology.  What analytics technologies are being used?  What does the schema for web analytics look like?  What homegrown technologies are used?  What external technologies have you bought or deployed for analytics?
• Integration.  How is web analytics data integrated with other internal and external data?  Is it integrated with other systems, how? 
• Site Optimization.  Does the company test landing pages, and/or use AB or Multivariate testing software?  If so, whose software, and what business gains have been realized?
• Advertising/Advertisers. How is analytics used to inform or enable advertisers and advertising?
• Privacy.  What safeguards does the company take in protecting analytics data? 
• Qualitative Data.  Is qualitative data contextualized with web analytics data? Do you capture voice-of-customer data?  Use Net Promoter Scores?  Have a research department?  Does web analytics collaborate with research? 

Those are just a few questions to ask.  Many others can be asked.  What would you want to know, and what would you ask?  Please leave a comment.  I’d love to hear your thoughts.

Now for some random thoughts:

• News from Orem.  API / Fusion / Video Tracking… cool.  I’m pretty psyched that Omniture announced a web services API.  That’s fantastic, and confirms how truly important integration is now and will be in the future for analytics data (as I’ve been saying for years… Google will be next). 

Omniture has announced a new methodology, Fusion, and improved capabilities for tracking video.  All sounds very exciting.  But, like Eric, I’m wondering what revolutionary new methodology Fusion really is?  Or is just what Eric’s been saying for the last 4 yearsbranded by Omniture and delivered by the Great Belkin? 

Regarding the video capabilities, I haven’t seen a real demo yet, but I wasn’t immediately impressed with what I saw on my friend Marshall’s blog.  Instead of quartile tracking, it seems like you track the playhead (the part of the video playing) across audience aggregates in increments of one-twelfth, and you get some bubbly visualization (what would that look like with 10,000 videos on your site?), and better access to forums.

I’m hoping I haven’t seen the whole ball of wax, and I look forward to Omniture giving me the grand tour. 

But for a playhead visualization, I was much more impressed with what I saw from Visible Measures and their engagement curve.  And what the heck are those folks at Divinity Metrics up to for measuring video? 

• News from Novato.  One of my favorite gangs of web analytics folks reside in Northern California.  My colleagues at Semphonic have just released a rather impressive “Omniture Implementation Toolkit.” 

I was able to procure a copy, and I’m totally impressed.  It’s full of hard-learned and hard-earned real world practitioner knowledge.  If you are trying to implement Omniture, it is well worth the money. 

Now I’m not sure if this document competes with or acts as a companion to Fusion.  All I can say is that I know the folks at Semphonic are smart, savvy, and very experienced, and there are thousands of Omniture customers out there who could benefit from this document.

• X Change Conference.  I am totally excited for X Change brought to us this year by Semphonic and Web Analytics Demystified.  The last X Change in Napa at COPIA was one of the most intimate, educational, stimulating, and enjoyable conferences that I’ve been too (and did I mention the wine?).  It was pure “class” all the way (in both the sense of style and learning, and did I mention the wine? ;-). 

This year attendance is limited to 100 folks (99 if you count me ;).  Last year, I huddled on “Deploying Measurement Systems in Globally Distributed Enterprises.”  

If you aren’t familiar with X Change or Semphonic  check them out, and make sure to read a few of my favorite bloggers - the prolific deep thinker and expert Gary Angel, the always impressive (and fun) June D(ershewitz), and bright author and web analytics veteran, Phil Kemelor.

Every month I write a column for MediaPost’s Metrics Insider.  This month I wanted tackle my evolving take on Internet video measurement.  Very few companies offer solutions in this space.  Only a few are really differentiated.  Check out Visible Measures, NedStat, TubeMogul, Divinity Metrics, and the usual suspects, Omniture, Unica, WebTrends, ComScore, and Neilsen NetRatings. 

Here’s my column:

IN LATE 2007, THE DIGITAL Video Barometer Executive Survey indicated that more than 80% of media and entertainment executives believe tracking, measuring, and monitoring Internet video content is critical to bottom-line profit.  That’s not surprising. Accurate measurement informs decision-making and improves business performance, and Internet video is more mainstream and popular than ever before.  What may be surprising to those executives is that technology for measuring Internet video generally focuses on video content served on-site, not off-site.  It’s fairly straightforward for a Web analytics tool to tell you how people are consuming and interacting with on-site video, but consumption and interaction of videos distributed across multiple sites, perhaps virally or via social media campaigning, aren’t directly measurable by Web analytics tools.  Panel-based technologies can approximate certain off-site measures of video consumption and distribution, but don’t provide very deep on-site metrics. Measurements of Internet video consumption, interaction, and distribution may be categorized as follows:

• Instream measurement.  Refers to measuring the video itself and the various events and behaviors that occur during a video viewing experience, such as time-based duration metrics and interaction and behavioral metrics (for example, the number of stops, plays, pauses, rewinds, fast-forwards, sites that posted or syndicated the video, clicks on hotspots and social media features).
• Outstream measurement.  Refers to measuring the content environment and user experience surrounding the video on the site or in the skin, such as the conversion metrics (percentage of visitors downloading or viewing a video), source metrics (refers to the video page, players used), and content metrics (percentage videos viewed by topic, percent videos viewed by file type). 

Those categories form a framework for Key Performance Indicators (KPI’s) that help to identify how people interact with videos, how videos perform when compared to other videos, and against pre-defined business goals.  Analysis of KPIs enables video content to be tailored to maximize performance.  Example KPI’s include:

Instream KPI’s:

• Percent high, medium, and low duration video views
• Average viewing time per video
• Percent visitors who complete the video
• Percent visitors that stop the video within 10 seconds
• Percent visits when this video was the last video viewed
• Percent visits when this video was the first video viewed

Outstream KPI’s:

• Conversion rates by video, topic, channel, taxonomy node, referrer, geography, keyword, and so on
• Average video views per visit
• Percent visits/views from different channels (such as email/rss, organic search, paid search, direct)
• Average time between visits that include a video view
• Repeat visit rate for visits involving a video view or download

These KPIs are measurable using a Web analytics tool, and perhaps a few of them are possible using traditional panel-based measurement.  But if off-site video distribution creates a whole new set of challenges to using current analytics and audience measurement tools to track instream and outstream metrics and KPIs, what are publishers and advertisers to do?  It’s a business problem that demands a new technology solution for understanding audience behavior, consumption, and distribution patterns of off-site syndicated or viral video content.

So what would a new technology solution for measuring Internet video and audience behavior do?  First it would have to fill the gap between panel and census-based measurement systems in a way that helps both publishers and advertisers  – not just one or the other — understand audience reach, frequency, and behavior.  The technology must enable tracking and actionable reporting and dashboarding of key metrics and KPIs, distribution patterns, behaviors, and interactions regardless of where the video “goes” on the Internet.  Audience characteristics from external databases (like OpenID for example) and internal company databases (like subscription and registration dbs) should be able to be integrated with data collected about behavior, video metadata, and instream and outstream metrics. 

If measuring digital video is as important as eight out of 10 media and entertainment executives believe it to be, there are some huge money-making opportunities on the horizon — for companies that are already providing technology for tackling this emerging business need, for advertisers using Internet video to drive awareness and response, and for measurement professionals who can help make sense of the Internet video ecosystem, solve measurement challenges, identify significant business opportunities, and use video metrics to improve business performance.  We’re certainly at the beginning of the J-curve for Internet video measurement for both publishers and advertisers.  After all, Forrester predicts Internet video advertising spend to increase from $471 million last year to $7.1 billion in 2012.