AVG has released an updated version that corrects the LinkScanner bot issue (build 138, July 4), which we’ve all noticed slamming our servers and analytics data over the last several weeks:

We have modified the Search-Shield component of the product to
only notify users of malicious sites.Search-Shield no longer
scans each search result online for new exploits, which was
causing the spikes that web masters addressed with us. However,
it is important to note that AVG still offers full protection
against potential exploits through the Active Surf-Shield
component of our product, which checks every page for malicious
content as it is visited, but before it is opened.

As you’ve just read in the quote above, AVG has stopped scanning each page that returns in a SERP for users of their free tool.  Instead pages will be scanned by proxy after a user clicks on the link. 

For paid users, it’s a little different.  SERP’s will still be scanned but via a pure database approach (not the DDOS approach :), which means the sites listed in SERP’s will be compared to a black list of known “bad” sites.  The blacklist is based on internal AVG research and from the real-time results reported by users who have opted-into AVG’s “prevalence reporting system” (a feature of AVG 8).  This means AVG is still scanning sites, but on a very limited basis, thus the detrimental effects on analytics should be very minimal and only caused by users who participate in prevelance reporting.  Still some data pollution will occur…  

AVG hasn’t confirmed that they’ve released a fix to the “noscript” issue I mentioned.  I do know they are working on it and have fixed the problem in internal builds.  Regardless, if the LinkScanner is working in the way they say it is, the problem will be negligible (but some data pollution will still occur ;).

Kudos to AVG Corporate, Roger Thompson, Pat Bitton, Greg Mosher, and all the other engineers who listened to the community on the web and worked quickly to fix the problem.  Now let’s hope the the build 138 update works as described. Time will tell.

AVG has obfuscated their user agent.  One of the current agents for customers of their free and paid tool now cloaks itself as IE6:

Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)

In addition to the easily detectable user agents:

Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1;1813)

User Agent:Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1;1813)  

User Agent:Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1; SV1)

This news is not good.  If you filter SV1 agent, you risk filtering legitimate traffic from the IE6 browser.  A few folks have commented to me that one should filter the user agent anyway, because 1) IE6 is in decline and 2) most IE6 users have .NET installed, which will show in the user agent.  Still filtering it makes me a little uneasy.

Is this the death toll for log file analysis and services provided by ABCe (since they can’t filter this user agent either)?  Maybe it is.  AVG is touting that agent lacks HTTP Accept-Encoding, which is just dandy, but that information isn’t normally captured in logs.

So the current situation is this:

1. AVG has two user agents.  Both are filterable, but the SV1 agent is problematic to filter because you risk filtering legitimate traffic.
2. Both agents in the current version request gifs in noscript tags, inflating counts in page tag implementations with noscript configurations.  AVG claims they will fix this issue.
3. The bot uses”mad” bandwidth.  I’ve heard stories of bandwidth increasing 100x normal levels.  Some webmasters are serving dummy files to the recognizable user agents, some aren’t serving content to IE 6 browsers (crazy), and some are redirecting the bot back to AVG (thus inflating AVG’s bandwidth, LOL!).
4. Evidence points to this bot NOT inflating clicks from paid search (i.e. PPC) and thus NOT committing click fraud.   But it doesn’t remain out of the realm of possibility that the scanner may be accessing an ad vendor click redirector and causing a click.  Not trying to spread FUD here, just making a point. 
5. AVG is looking at option of checking either an external db (hosted by AVG) or a local cache to verify sites in SERP’s have been “scanned by AVG,” instead of repeatedly scanning sites every time they are listed in SERP, to reduce the bandwidth issue and minimize fraudulent entries in log files.
6. AVG is thinking about enabling white listing of sites, so they are skipped by the scanner.
7. AVG is thinking about exposing a meta-tag that instructs the scanner to ignore the site.

Good luck with this nasty bot!  Interestingly, here’s how you smurf a site with the AVG LinkScanner. 

The  well-researched answer is “no.”  The AVG LinkScanner Bot appears to prefetch the js and the gif (and pretty much everything else on the page), which for certain tools and their tag configurations generates false page views and visits (and the derivatives thereof), just like it’s “legitimate” traffic. 

If your tag configuration is set up with noscript tags, AVG will fetch the content in the tags, including the gif, which means that:

• The bot may be infesting the data of customers of web analytics vendor who configure page tag-based data collection in this way. 
• The bot may be inflating the data in such products/services offered by various web analytics companies.
• Customers may be paying for server calls generated by this bot.

Vendors, of course, could easily filter the user agent to protect their customers:

Mozilla/4.0 (compatible; MSIE 6.0; Windows NT 5.1;1813) 

But I haven’t heard a peep from any SaaS vendors about excluding the user agent, filtering already collected data, or refunding customers the cost of robotically generated server calls (regardless of AVG). Have you?

Think about this: many SaaS page tag vendors don’t provide detailed visitor-level data and user agent reporting.  That means that their customers have no ability to investigate this bot or detect it by filtering their reported data by the the true user agent.

I’ve been talking about JS executing bots screwing with web data for about a year now.  SEOMoz and the folks at SlickSurface confirmed it quite recently (quoting me no less in their fantastic analysis).  So they do exist…

Now let me tell you a little story.  Once upon a time I was at a conference called eMetrics when the CEO of a company came up to me and said “hey I read your blog about bot detection, and I looked in my web metrics tool for traffic with high page view to visit ratios.”  Then he narrated a story to me about how he found a bunch of traffic that had page view to visit ratios of 5,000 to 1.”  I said “do you use page tags” He said “that’s all my vendor provides, so yeah.”  And I said “you’ve found a javascript executing bot in your data.”  “I know” he said. “Well did you call your vendor and let them know?”  I said.  Now for the punch line:  he told me that the vendor (who shall remain nameless) told him “well, the traffic executed server calls”  And they wouldn’t give him a refund!

It’s worth mentioning that this bot definitely affects log file tools and packet sniffer tools.  Both must be configured to filter the AVG LinkScanner user agent.

Now here’s the rub for me.  I use AVG!!!  But I now find it increasingly difficult to support the company or continue using their products.  Why?  Because they are wearing a “bad hat” here:

• First, they are fully aware of the affect of this bot on web analytics systems. They just don’t seem to care (yet).  UPDATE:  They have set up a Google Group to discuss this issue.  They must understand how companies of all types in all sectors use web analytics data to optimize their sites, set their marketing budgets, determine expected server load, and much more.  What do their Internet Marketers think? 
• Second, the Link Scanner tool may have a short shelf life and may offer limited protection.  Malware creators will easily adjust. Check out what my friend Steve McInerney, a very smart security expert, said on the Web Analytics Association’s Yahoo Forum:

What strikes me about this particular solution by AVG is how
incredibly … stupid it is on several fronts.

1. Noticeably impacting a users bandwidth is, technically, a security
breach in the first place, aka Denial of Service Attack.

2. Some of us live in countries that have rather severe bandwidth
charges/limits and the like, whom shall I send my excess bandwidth
bill to?

…(this) method is fundamentally
flawed. ie malware ignores any first request and only infects on a
second request - alternate cloaking. Whatever. This type of “solution”
only provides weak protection for a strictly limited period of time.

…not just “no security” but bad
security. Because folk feel they are being protected when they are
not, and hence will take greater risks and hence inflict greater harm
on themselves.  

Ignoring the balance of positive to harm that this problem inflicts on
the users who use this product.

• Third, AVG just doesn’t seem to “get it” yet.  They are potentially messing with the ability to drive commerce via data driven decision making, e-commerce analytics, site optimization, and online media measurement!  To quote The Register “chief of research Roger Thompson - who designed the AVG LinkScanner - indicated he may do away with that unique user agent. His chief concern is security, and he doesn’t want webmasters or malware writers gaming his scanner. “In order to detect the really tricky - and by association, the most important - malicious content, we need to look just like a browser driven by a human being,” he argues.

WebMasterWorld has some good stuff about to say here.  Read the Register’s first article here.  And check out the dude’s blog who broke the news first and responses from AVG here and here.

Interesting stuff. So what do you all think? Have you seen evidence of this bot in user agent data from your page tag solutions that use the noscript tag for the image? 

Mobile analytics for Internet-enabled wireless devices is a fairly hot topic for companies seeking to acquire customers, extend their brand, or expose content in “innovative” ways.  Obviously, the iPhone and Blackberry are pushing development in this area forward, but there really aren’t a lot of players in this space. 

Nedstat, CoreMetrics, and Omniture offer capabilities mixed into their current offerings.  Nedstat even carves out some mobile specific reporting.  You can gain some insight into mobile activity from companies that enable log file processing, like Unica and WebTrends, but be prepared to configure a bunch of filters to isolate the data.

Lesser known companies pushing mobile offerings include: Amethon, Mobilytics, Bango, TigTags, Xiti, and AdMob.  Some of these mobile players are even offering capabilities where they cross-sell analytics as an integrated part of their ad networks, content delivery  and transactional processing systems, marketing and barcoding services, and even as infrastructure or network appliances.

On the audience measurement side, we’ve seen comScore acquire M:Metrics, which was no surprise to me.

On the multivariate testing side, we see my friends at SiteSpect offering mobile MVT testing capabilities. 

And I’ll bet we see Google get into this space within the next 6 months…  I’d even wager an announcement at eMetrics DC…

From what I can gather, when we’re talking about “mobile analytics” we’re talking about “mobile browser” activity across a variety of handsets, not everything that happens on the device. 

Measurement issues in this area include:

• Data Collection.  As many of you know, not all mobile browsers will execute javascript.  They cached the imagesThus, vendors offer us choices.  Folks like Mobilytics and Bango use an image-based data collection method, while Amethon offers a packet sniffer (they call it wireline detection), and we even have Omniture and Coremetrics talking about “no tag” implementations - what my good friend Phil Kemelor mentioned on his CMS Watch blog (”To compensate, you need to stuff the image tag with query strings that will collect the data you require for reporting.”)  Then we have Unica and WebTrends with log files.  Interestingly, packet sniffing has some advantages here because some devices pass unique id’s (such as the phone number) in the HTTP header or other unique id’s.
• Unique visitor identification due to lack of cookie support and IP addresses changing.  IP addresses change, I’m told, as they switch from tower to tower.   In addition many mobile devices will take the IP address of the gateway, making all the devices look the same “person.”  I’ve certainly seen evidence of the host changing pretty quickly during a mobile session. Compounding the difficulty in assessing “uniqueness” is that not all mobile devices support cookies.  In web analytics, cookies are used to define uniqueness.  The fallback method when you can’t use a cookie is IP address/user agent.  If you can’t set cookies and the IP address and user agents are the same, how do you identify uniqueness?   However, when you can detect a unique value in the header, you can easily detect uniqueness.
• Handset capability detection.  Does the device support WAP pushing, streaming video, ringtones, downloading video clips, and so on?
• Phone and Manufacturer identification.  Database from WURFL and DeviceAtlas can be used to identify phone and manufacturer device attributes.  Larger vendors are further behind on integrating this data into their current offerings, whereas the smaller niche players are making use of it. 
• Screen resolution detection.  The Mobile Marketing Association’s (MMA) standards for the four “standard” screen sizes may carry enough weight to push this disdained piece of metrics trivia available from javascript based tagging in web analytics into a brighter spotlight.
• Traffic source detection.  Capabilities for traffic sources seem rudimentary.  I don’t just want to know about search and direct entry.  But I want detection of sources from my marketing and advertising campaigns, rss feeds, and email newsletters, if mobile visitors are coming in from those channels.   Interestingly, Bango solves the campaign tracking issue by pushing you to a Bango-specific URL.
• Geographic identification.  Where are the visitors viewing your site coming from?  And what does the mobile audience environment “look like” in each country.  From this information you can extrapolate country-specifics for site optimization.  But not all devices enable geographic detection because the gateway’s IP address is used or the IP address from the network is used, not a GPS signal.
• No standards.  There are few, if any, commonly supported mobile standards and no web data standards, so the problem is no standards for the devices and no standards for the tools.  There are no standards.  Did I mention that there are no standards. 

So I was thinking, what would I want to see in a mobile analytics solution?  Allow me to riff here.

• Dashboards for KPI and specific-metric reporting.  Views, visits, visitors, referrers, popular pages, traffic sources, resolutions, geography, time-based reporting and custom defined KPI’s….
• Support for multiple data collection methods.  Logs, no-js image tags , and packet sniffers.  Let me pick what I need for whatever application fits my goals.
• Support for mobile-specific constructs not present in historic web analytics data.  Manufacturers, operators, handsets, and device capabilities.
• Advertising-based reports.  CTR, CPM, eCPM, that stuff…
• Tracking for mobile downloads, installed applications, SMS, and MMS.  Seems like a no-brainer.
• API’s.  Closed systems are dead ends for integrated marketing, so give me an API or enable pre-built integrations with other systems, like CRM.
• Segmentation.  By country, by device, by network, by manufacturer, and so on.  It’s necessary.
• Repeat or return visitor identification.  Simple measures of recency and frequency, core to media buying and planning and to site optimization, should be a data point available in mobile analytics.
• Conversion and goal metrics.  Do visitors on mobile devices convert better, worse, the same?  Do they reach site goals?  Without tying performance data  and outcomes to mobile visitor activity, I’m left wondering…
• Value scoring for engagement or proxy scoring for revenue and ROI analysis.  I want to be able to score attributes or actions to approximate an engagement score or to identify value or indicate revenue. 
• Non-human traffic and web-browser based detection and reporting.  Mobile pages are full of links.  The ads are links.  Mobile vendors must support detecting, filtering, and reporting, non human and web-based agents from pure mobile agents - otherwise the mobile data gets muddled and skewed.
• Data Export.  Must be able to export reports to Excel or Word, and email them.

So there’s a quick blogviation on Mobile.  Am I right, wrong, what did I miss?  Let me know…

Wow!  It’s been a few weeks since I’ve had any time to blogviate. 

What other things do web analysts do?  Besides blog and do WAA stuff… And ensure tool configuration/administration, date collection, data verification/validation, reporting, KPI generation, conversion optimization, deep site analysis, stakeholder guidance, outcomes evaluation and so on… Well the fun answer is “it depends” on a things like your boss, the organization you work and the holy org chart, your recognized skill set, and what you want to do.   But as I talk to my colleagues in the industry, I’ve noticed some web analysts do a lot of different things.  Here’s a few beyond the norms (or in some case maybe part of the norm, but not often discussed):

• Write business requirements.  You may be writing biz reqs for the extension and maintenance of your own tool, or you may be asked to participate in the definition of the metrics strategy for product or site features.  The analyst may define the attributes, capability, and characteristics that are necessary to accomplish given business objectives.  Generally these biz reqs will be functional (the system must do this in this way and look like this) and not technical (but every so often you may need to justify why you keep saying “ah, page tags, not logs” or vice-versa or packet sniffers or hybrid).  Fun!  And time consuming! 

• Participate in product development and usability discussions.  A rich topic here for sure.  As web analysis sort of fractures into those who study how the site routes visitors, navigational elements, information architecture, and into those who prepare AB and MV tests and report the results, it’s not uncommon for analysts to be called into to determine what should go where and what functionality should or should not exist on the site in order to drive business or conversion goals.

• Contribute to the keyword set.  As I explained in my last post, web analytics is morphing into multichannel analytics.  Analysts are increasing leveraged to participate in and analyze the outcomes of SEO and SEM.  Based on keyword data, I have a few friends who spend a ton of time selecting and managing the keyword portfolio and even the bids! 

• Have a say in “strategy”.  Analysis informs tactical decision making, which is guided by strategy (and analysis and decision making and strategy again).  When fully leveraged, a web analyst has much to offer the strategic decision making process.  Think about something as simple as using referrers to establish content syndication and affiliate partnerships…  Cool.

• Guide the content agenda.  For those who work in what my buddy, Alex Langshur (who runs a boutique consultancy in the public sector), calls “content-rich” and “mission driven” sites, the web analytics tool has utility as an editorial or content research tool.  From understanding what keywords/phrases are driving traffic to determining whether the editorial plan is actually mapped to the information demands of site visitors, web analysts can have a lot to say, if asked.  But be weary, the last thing an editor wants is some hot shot web jockey telling them what to write. That’s not what I’m saying to do, rather, some analysts work with content and editorial teams to ensure frequently demanded content topics are rounded out on the site, expanded on/developed, put on the content plan, or simply just known about, so the content folks can do what they do… 

• Code. Yeah, some of us know how to do it, and many of us just don’t tell anybody.  Because “that’s not what I want to do anymore” as my friend who works at a local agency told me the other night.  My personal opinion is that code is better left to the coders, but any web analyst who can throw down with web development and talk about things like X-Forwarded From headers will only make themselves more valuable to the organization.  Then again, some analysts would rather analyze data than futz around with overly esoteric tags and variables and the plumbing of web pages.  Then again some of us love that.

• Direct IT.  Those of us fortunate enough to have control over our web analytics technology already know they’ll be spending perhaps inordinate amounts of time with our good buddies in IT.  They may be the audience for your business requirements, or you just may need to connect with them to ensure your technology is factored into the larger plan for next generation integrated, service oriented architectures.

• Due diligence on acquisitions.   A fun one for you MBA’ers is when you get drafted into the acquisition or merger process, having to examine the target’s web traffic.  You gain real insight into the core of their web business, and may even find things, I’ve heard, like page view inflation from not filtering bots on including things like favicon.ico to inflate page views.  Heh!

And more!  So yeah, it’s not all about spending all day just thinking about who comes to the site, why, what do they do, and do they complete their purpose according to specific goals.  While that is all a big and important part of it, the role of web analyst can go far beyond tradition, if you are capable and you work for the right business that lets you excel!

In Part 1, I mentioned that the Web Analytics team will look very different depending on company and business goals.  I identified three elemental constituents (business strategy, analytics, and technology) necessary to select a web analytics tool, and I divided them up into three different folks who fill those roles when you’re selecting an analytics technology.

Once the tool is selected, companies will want to create a structured team framework with defined roles and responsibilities in order to successfully deploy the tool.  What I’m describing is a suitable team-structure that enables you to successfully deploy a tool in your organization that finally gets you to a point where you are able to do web analysis. The team structure I describe below lets you get to the hub-and-spoke model that my good friend, Eric Peterson, described in these Part 1 and Part 2 of “what’s your web analytics communication strategy?”   What Eric excellently describes takes the team to the next level of actually doing Web Analytics.  It’s excellent stuff that I encourage you to read.

A formalized team structure for rolling out a web analytics tool may have the following constituents: 

• Executive Advisory Board.  Beyond the Executive Sponsor mentioned in Part 1, these board members are the ones who really control the budget and strategy at the highest level.  They may be your boss, your bosses’ boss, or board members at your company. Regardless, they are the analytics project champions at the highest level in your organization – often C-level executives.  They support the project structure and analytics strategy, confirm the scope of the project, and approve any budget allocation.

• Steering Committee.  You may be on the steering committee, Mr Web Analyst, or it may consist of very senior representatives of all the internal teams that the project touches.  These people work to define the strategic direction of the project, decide on how to resolve critical issues that come up during the rollout, and generally handle any escalations.

• Web Analytics Expert.  That’s probably you, fine reader.  You will provide analytics-based strategy and informed decision making across all aspects of the project. You’re obviously critical to the success of this project, and will ensure technical, tactical, procedural, functional, and financial adherence across the entire analytics program.   You are the chief evangelist, and will define the overall reporting and KPI structure.  In addition, you will be responsible for the overseeing the partnership with your vendor. Other things you may do will include managing costs, coordinating schedules, risks and resources, and reporting overall project status and important communications (often with the help of a project manager) to the steering committee and advisory board.

• Web Analytics Team.  If you are lucky enough to have a team, these folks will gather and document project and technology requirements, liason with business stakeholders, lead training, build awareness of and evangelize web analytics, and in general work with those who receive reporting and leverage the tool.  In many companies the solo web analytics expert will do all this stuff (and drink a lot of coffee or green tea too!).

• Project Manager.  A web analytics rollout can be complicated. While the solo web analytics team member may be expected to project manage, it may make sense to give that role to a formal project manager (y’know a PMP) who works with the Web Analytics Expert to manage the schedule, risks, resources, communications, change, and quality management plans.

• Business Partners.  Since web analytics will touch many different groups, you will need to ensure your analytics team communicates with them.  Business partner are critical stakeholders.  They can’t be neglected.  They will provide business requirements, test the technology, and work with analytics team to ensure the technology, reporting, KPI’s, and analysis you rollout helps drive business performance.

• Subject Matter Experts (SME).  Similar to business partners, these folks will probably be more technical in nature.  The Technology Expert you worked with when selecting the project will transition into a roll as a SME.  You may have one SME who oversees the overall technology architecture, another who coordinates BI resources, another who QA’s the system, another who creates interfaces to your data warehouse, and perhaps another who acts an IT contact covering issues across the operating system, database, security, and networks (especially if you are running an in-house tool).

• Vendor Professional Services Team Members.  Last, but certainly not least, are the folks sent from your vendor to do what you want them to do.  From installing the application (in a in-house environment), functional training, to advanced configuration, these people are critical to ensuring that you don’t make simple, avoidable mistakes that can thwart your efforts and delay the successful rollout, golive, and extension of the project.

In reality, you may not be able to effectively isolate all of these groups to support your analytics rollout.  To some degree I’ve presented big company structure above.  In smaller companies, one or only a few people may do all of the interlaced activities necessary to rollout a web analytics tool.  Regardless, I think the groupings I’ve presented above define the primary roles and responsibilities necessary for success when rolling out a web analytics tool (in fact I presented things in a general way to apply to other rollouts as well).  The next challenge comes once your up and running (make sure to read Eric’s posts)… You need to use the data to improve business performance and guide strategy, decision making, and online tactics that reduce expense and yield profitable revenue.


Image by Jim Sterne, from Emetrics 07 San Fran.

The best answer to that question is that “it depends.” The members of the Web Analytics team vary widely by company based on a number of factors, such as the company size, where you are in your rollout, capability maturity for analytics, established corporate processes, the number of sites to implement and maintain, the granularity of the implementation, the technology used, the number of people to which you give access, support requirements, and many more company-specific factors.

For many companies, the number of web analysts can be counted on one finger of one hand.  The lone cowboy is expected to champion the effort, and pretty much do everything under the sun - from orchestrating the tagging to reading the data to being a project manager.  Sure, that can work.  It just means empowering one individual to get the entire job done and giving them the budget, resources, authority, and clearance to make all the decisions - and communicate up the chain.  In reality though, few companies can find the right person who can do it all. Does it take a village to do web analytics?  We’ll not quite, but it does take many different people to select, implement, extend, and maintain a web analytics platform.

Over the next two (or maybe more) posts I’m going to cover my take on what skill sets, roles, and responsibilities are necessary on for doing web analytics - from when you start thinking (and believing) that you need a web analytics tool, to when you implement, to the ongoing day-to-day operations of the web analytics department and maintenance of the tool.

When you are just beginning you web analytics selection, prior to implementation, you want a small, focused web analytics team (watch out for too many cooks!):

• An Executive Sponsor.  This person is usually the HIPPO (highest paid person in the room) - until their boss gets involved ;).  For some companies this could be a C-level executive, VP, or Director.  The Executive Sponsor is in charge of setting the broad-based strategic vision for the analytics roll-out.  They may have hired you!  They help to set the overall scope of the rollout, remove obstacles, and set and control the budget. They are who you go to “escalate.”
• A Web Analytics Expert.  This person is most likely you. You may be an MBA, a techie, a marketer, an IT person, or someone who was promoted into the position.  Lucky you!  You will be in charge in identifying a vendor consideration set, writing an RFP (if you do one), identifying business requirements, collaborating with internal stakeholders, doing the due diligence with the vendor, determining the features and components needed in the web analytics product, figuring out the appropriate financial model, championing for the budget, communicating with internal stakeholders, debating the merits of the technology with your internal team, and generally supervising and stewarding the whole selection process along so that the job gets done (and your executive sponsor looks good).
• A Technology Expert.  This person could be you too, Ms. Web Analyst. Or it could be a systems architect, a data warehousing expert, a dba, an application engineer, or another tech-savvy colleague with a computer science degree (or maybe not - a degree from the school of hard knocks). This person will vet the underlying technology provided by the vendor.  You want this person to ask deep, hard questions about the innards of the technology offering to ensure the technology will match and scale to your internal technical requirements.  Say you want to integrate internal data with your web analytics tool.  This person should know all about your corporate systems, what data your company has, where/how it’s stored, other technology projects, and so on.  They’ll help you ensure technology you are leaning toward fits into the technology ecosystem at your company at a very deep level.

After short-listing vendors, doing the due diligence, pilot/proof of concept(s), you’ll finally make a decision about what tool to buy (or perhaps you’ll determine a free tool meets your requirements now (but will it in the future is the question you should be asking… LOL!).

At the “buy” decision is made, the Web Analytics team will grow to include a more people with different skill sets, roles, and responsibilities.  I’ll cover that in my next blog post.

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. 

One of my favorite personalities in Web Analytics is Phil Kemelor - author of the Web Analytics Report.  Phil is also Vice President of Strategic Consulting Services at SEMphonic and an analyst at CMS Watch. 

I first encountered Phil in late 2006 when he called me up to discuss my take on the vendor landscape at that time.  We instantly hit it off because, like him, I seek truth, and have a lot of trouble believing vendor spin and hype.   We found each other’s insights “refreshing,” and we’ve kept in touch ever since, grabbing food together/swinging back a few beers/hanging out at conferences, chatting via email, and just generally staying in touch.

Fast forward to late 2007, early 2008, when I find out that Phil was revising his awesomely comprehensive Web Analytics Report and releasing the 2.0 version.  We’ll the time has come, and WAR 2.0 is out.  If you can swing the cost (it’s over $1000 US), I highly recommend purchasing it, especially if you are new to the industry and trying to make a vendor selection, or if you are old to the industry and want to get a solid sense of current vendor capabilities.

The 343-page report goes over all sort of juicy stuff - from beginner information about “what is web analytics” to concepts around the “web analytics business case” to deeper dives into “web analytics technology.”  It covers an abundance of useful information about data collection, data sampling, data exporting, dashboarding/reporting, segmentation, licensing, organizational requirements, and how to select a web analytics vendor.  He’s also done a good job, imho, discussing 15 different vendor tools, which shows you that the vendor landscape is a lot larger than just Google Analytics and Omniture - that’s for sure.

So if you have the $$$ to spend, check it out.  It’s an excellent addition to my analytics library.  Good work, Phil!

I’ve been so busy folks, I’ve had no time to blog, so forgive me for my two week hiatus.   

The classic problem of “marketing versus IT” is real.  If you are lucky, you work with an excellent IT team (like me!), then this problem will be minimal if at all.  But in most cases, based on what I hear from my industry colleagues, the analytics team often has issues with IT resources being sufficiently delegated to supporting a web analytics implementation and program.

The classic problem goes something like this:

1. Marketing:  We need advanced customizations, deep integrations, increased scalability, better performance, and more control overall over Web Analytics.
2. IT: We don’t have resources, time, or budget to help you right now.  Fill out these forms and in the future maybe we can help.

In a nutshell, this is one of the reason why hosted solutions exist (SaaS, ASP, on-demand, whatever).  While it’s hard to do web analytics, it’s even harder to do it internally using actual software that you run.

Wouldn’t we prefer it to go something like this:

1. Marketing: We need advanced customizations, deep integrations, increased scalability, better performance, and more control overall over Web Analytics.
2. IT: Yes.  Can do.  Will do.  What do you need and when do you need them by?

My belief is that to “do web analytics” the right way, you need an allocation of IT resources to support your implementation and extend it to fulfill strategy and improve business performance.   After all, I firmly believe web analytics is for optimizing business performance, guiding strategy, and supporting tactical decisions.   And to do all that, you need resources when you need them.  The larger your site or portfolio of sites, the more resources you need.  It’s all pretty logical.  Getting back to IT, if you’re using a hosted solution, you need fewer IT resources.  The vendor takes care of a lot of IT stuff.  If you are running your analytics in-house, you need a team of IT resources because you will be doing it all yourself.  

I would prefer those technical resources report into Web Analytics, but I’m not sure if the general business world (as in non-Internet companies) sees the ROI of Web Analytics clearly enough to immediately delegate a full-time “mini IT” team to support analytics at phase zero (i.e. when you first get hired and plan the rollout).  And that’s why you need to be very wary of what vendors tell you about IT requirements and web analytics. 

If management expects that you just need to tag the pages and you the analyst can do that yourself, your company will be in for surprise.  It’s never that simple.  Smaller companies with one or a few sites that use the same technology may be able to pull off the solo cowboy analyst including tags and doing all the tech work.  Google has made that fairly easy.  But larger companies that have many sites and many different technologies serving those sites are a much different animal. 

My advice is that you can’t be fooled by vendor messaging that claims “you don’t need IT.”  That’s bull$4!+.  Marketers can’t do Web Analytics alone and in isolation.  You will need IT to help you extend your web analytics solution.   And as I’ve already stated, the level at which you need IT will vary on how you “do” web analytics.  It differs greatly if you are running an in-house proprietary solution, an internal vendor solution, or a hosted solution. 

If you are doing web analytics using a proprietary solution you created internally, you may probably then already understand what I mean when I say ”web analytics needs IT.”  Chances are you are using an OLAP-based solution that has huge BI infrastructure behind it and the cubes contain latent information.  Your data model may be limited compared to the major vendors.  Your tool may be overly complex, hard for business users to use, and limited in terms of features, or it may be the coolest thing since sliced bread, and the people who created it may know more than the vendors.  Still, unless resources are adequately delegated to support analytics and extending the implementation, your tool users and report consumers will make thousands of requests to IT, and they will go unfulfilled leading to user frustration.

If you are running an in-house software solution, such as that provided by Unica, WebTrends or Visual Sciences, you will rely on IT for all sorts of things, like hardware and software maintenance, database administration, network support, and will need to leverage help desk and ticketing systems.  In addition, web analytics projects become part of the IT project planning cycle with budget requests and consideration.

If you are having your web analytics tool hosted.  IT may be the ones who actually put the tags you field on your web site.  Modifications to any javascript may need to be done by IT.  You will need to reach out to IT for help with setting up cookies, changing the DNS, and writing any code that assists with web analytics.  “Change management” will be required. ;)

If a business wants to succeed with Web Analytics, it must determine how to effectively resource the implementation and ongoing extension of an analytics platform.  Here are some tips for ensuring you get the resources you need:

• Factor web analytics resource needs into the capital budgeting and yearly planning process.  Business stakeholders must identify the IT resources they need in advance, and then align the IT team according to business goals.  Resources must be allocated according to financial guidelines that maintain corporate profitability. 
• Document your web analytics projects and business requriements and share the documentation with IT.  Whether your web analytics projects are related to implementation, campaign optimization, data description, or integration, you need to share that information with IT so they can determine how to support analytics. 
• Identify and document why you need IT resources.   In other words, identify and document what IT will be doing for web analytics and how their work is necessary for improving corporate performance.  On the business side, explain that you won’t be able to fulfill X business goal without IT resources.
• Leverage a project manager.  Project managers are critical and important to cross-functional team success.  They focus work, align people, determine tasks, monitor completion, and allow a multifaceted team of business marketers and IT to do what they do without worrying about managing the project.
• Share your analytics success with IT and let stakeholders know how IT has helped you.  Often times corporations forget that these very talented IT folks are working really hard behind the scenes, often without getting much (or any) credit for the complex work they do.  When you have an analytics success, share it with the folks that helped you tag the pages or configure your servers.  When people are singing your praises in the cafeteria because they now have the data they need to do their jobs and/or you’ve improved their business performance, let them know IT backed you up and helped you deliver.  There’s enough glory to go around.

If you do what I’m saying in this blogviation, the problem  of ”marketing versus IT” will be minimized.  IT will be able to keep up with all of your constantly-evolving business requirements and the dynamic, high-maintenance nature of your web analytics program.   And your marketing department, business stakeholders, and executive team will be very happy with the results.