Anyone who has spent any time doing web analytics knows that you get a lot of requests for analysis.  The bigger the company and the more serious they take analytics, the more requests you will get.  And the requests will range all over the map - from simple data pulls to dashboarding/reporting requests to comprehensive analytics projects to statistical modeling to pretty much everything under the sun - whatever people consider “analytics.”

People have even told me that requests for analysis can even be a tactic for people outside your analytics team to pass the buck in order to make an excuse for not delivering on their own work.  The idea being that because you do analytics, you instantly have all the data at your fingertips and can deliver it in a flash, so why aren’t you helping me? 

False conclusion.  Analytics is hard and complex.  And the bigger the corporation and more integrated the analytics, the harder and more complex.

In many cases with web data, the data may not already have been collected, the data may have to be sourced from another system, extracted, transformed, or made available in a dashboard or a report - if at all even possible to report and analyze. 

The data may only exist as a figment in the imagination of the requester. 

The data may be impossible to report because you have inadequate data model or an entrenched BI team that doesn’t get how the schema affects reporting and doesn’t care enough to help. 

And real analysis of the data takes uninterrupted time, which you may or may not have time to get to today, next week, or next year because you are working at correcting the data model, ensuring the right data is collected, letting queries run, dealing with the intracacies of overly complex tools, building reports, dealing with other requests, working on already prioritized projects, and trying to answer your email and attend meetings. 

I am sure this all sounds familiar to the 1000’s of practitioners who subscribe to my blog…

That’s why when you, data and analysis consumers, ask for data or analysis, you sometimes don’t get it quickly from the web analytics team.  You are just one of the many people making many requests to what in many companies is an already overburdened, often understaffed team dealing with non-standardized or clearly-defined data coming out of many different systems and third party applications.   

Thus, when you are a web analyst, you need to carefully consider what you say yes to do and how you respond to requests for analytics work.  Because as soon as you say “yes, will do” you’ve committed to what could be the analytics equivelent of daisy pulling in a sunny meadow on a summer’s day or a Herculean cleaning of smelly crap-filled stables in freezing weather.   What follows is some advice on how to prioritize your requests for reports and analysis:

• Is Revenue at Risk?  Anyone who has worked with me knows this is one of my favorites. If revenue is at risk, then the analysis will be done!  Profitable revenue is the chi, the lifeforce of any business.  And analytics that supports revenue generation is of the highest kind of analysis.  But you gotta prove revenue is at risk.  Just because you work for a group that produces revenue doesn’t mean your request going unfulfilled puts revenue at risk.  Tell the team, exactly why revenue is at risk…  Not just that you think it is.
• Who’s asking?  Is it your boss asking, her boss, their boss’ boss?  Then the work gets done.  We’re not talking HIPPO here.  We’re just talking MOPPO (most powerful person in the organization!).  Keep your boss happy.
• How difficult is the request?  Just because something is “too hard” doesn’t mean it won’t get done, but as an analytics professional you need to set delivery expectations when requests are so difficult that they will take time.  Perhaps the schema needs to be modified, changed, or just simply remodeled in order to get that data, maybe you need to rewrite the tags, reconfigure the tool, build a bunch of new reports, figure out the data delivery tool.  Maybe 5 other groups need to work collaboratively in coordination with all their other projects just to get the data to a point where it can be reported.  Manage the expectations of the requester.    
• Can it be self serviced? Just because requesters don’t know how to use the tool (RTFM), it’s too slow, don’t know where the report is, can’t understand the report, don’t get web analytics, don’t know how to write SQL, or don’t where to look, doesn’t mean the web analytics team is going to do for you what your job requires you to do.   The analytics team should teach self-servicing as a best practice because wasting time easy fishing in shallow waters means you may miss the big analytics catch in the deep data pool! 
• When is the analysis needed?  Of course, it helps to know when the analysis is needed in order to prioritize.  Requester wants the weight of the world at microsecond N during the equinox by the end of the day tomorrow?  They’re probably out of luck unless 1) revenue is at risk or 2) they are the boss.   A week?  Well maybe, but the weight of world requires querying the Atlas database and queries don’t run like Mercury.   The analyst needs to set expectations based on a number of interplaying factors about when the work can be delivered.
• Why is the analysis needed?  Just curious about the number of X that goes to Y from Z?  Time spent on page Z of your microsite? Or do you need to make a real business decision to advance the core mission of your company?  By communicating to your analytics team the importance of the request’s “why” you can get better service.   Analysts that know why they are delivering can more effectively prioritize.

As an analyst, use these questions above to:

• Help you prioritize your work
• Figure out what’s really important
• Frame how to manage expectations
• Deliver what’s really necessary to drive the business as soon as possible
• Not get caught in the tarpit of wasted time constantly servicing low value requests

And if you made it this far into this blogviation, leave me a comment on what you think.  Am I right, wrong, on target, misguided, and how do you do it?
 

From an article I wrote for MediaPost a few weeks ago:

Reach and frequency and the core concepts of traditional media planning and advertising.  For a given site, program, channel, radio station, billboard, newspaper section, a target audience (the reach) is exposed to a certain number of occurrences of the media (the frequency).  On the web, these concepts manifest themselves in metrics collected and reported from a number of recognizable services.  Audience measurement firms, like comScore and Nielsen, web analytics firms, like Omniture and Unica, to companies somewhere in between, like Quantcast and Google, all have reach and frequency data.  Many new media metrics can be used to proxy frequency- from time-based measures, espoused by audience measurement firms, to concepts like visitor retention or the repeat visitor rate cited by web analytics firms.  On the reach side, companies refer to concepts like “unique visitors.”

These data, of course, available in free tools or in for pay tools are certainly helpful for planning campaigns.  But reach measures can be dirty (cookies, unduplicated unique users, estimates from panels, coverage error).  Frequency measures can be just as dirty (problems recording time in single page visits or visits on the last page, do page views really matter with AJAX and rich media, cookies again, and so on).  We all are aware of the challenges.

Thus using basic reach and frequency measures for planning or evaluating a campaign does not suffice.   So advertisers and agencies target demographics, like gender, age, income, education, and job title.  It’s a given that advertising in the Robb Report reaches a different audience segment than advertising in Popular Mechanics. 

These brave new days we have “behavioral” tracking too.  By taking into account visitor activity across sessions, such as past actions taken on a site or a roster of previous purchases, we can attempt to deduce what a person or segment responds to or is interested in based on their behavior.

Even with reach, frequency, demographics, and behavioral data to help guide advertising and media buying, we are missing an important attribute for maximizing the potential success of our campaigns.  We do not have an available tool, whether free or paid, for advertising or buying media on or across sites according to measures of past performance.  Such measures include ad clickthrough rates, conversion rates, goal completion rates, delivered impressions, and perhaps even harder to quantify financial measures such as ROI, ROAS, and ROMI.

Sure, historic, tacit knowledge of campaign performance exists and is used by agencies or publishers.  However, there is no shared industry source that can help us answer “how has a site for display advertisement historically performed toward goals based on the reach, frequency, demographic and behavior of its audience segments?”  Interestingly, a company minting money right now, named Google, can masterfully demonstrate performance in paid search campaigning and help advertisers unify it with segmented reach, frequency, and demographics.

Outcomes based performance measurement unified with reach, frequency, demographics, and behavior is what is missing in audience measurement tools, not frequently reported externally by web analytics tools or ad serving tools, and not available in ad planning tools.  When advertisers can target display ads, or even video ads, to desired audience segments by reach, frequency, demographics, behavior in the context of known performance, media planning will be more effective.  

Web Analytics Key Performance Indicators (KPI’s) are critical for breaking through the dataglut spewing forth from your web analytics tool.   I mean there’s a just a ton of data in web analytics, and the majority of it tends not to be very useful or applicable for improving your business performance.  While it’s wonderful to have a tool that lets you cut, cross, and slice loads of data every which way but loose, its can be a real challenge to frame the data or put it in context in a way that helps your business optimize the web site.   That’s why I like KPI’s - they identify meaningful, business-focused relationships in your analytics data.  By understanding KPI drivers, setting expectations for KPI performance, and analyzing your KPI’s toward defined goals for those KPI’s, you increase understanding of data, alleviate data confusion, and provide focus for the usage of your web analytics tool.

For those of you who don’t have a KPI strategy or who are just getting into analytics, an easy way to understand a KPI is to consider the example of when you are driving somewhere and trying to get there within a certain period of time.  If your goals is drive 60 miles (kilometers, my European friends) in exactly 60 minutes, you know that you need to drive 60 miles per hour (or KPH).  If you go faster, you will arrive early, if you go slower you won’t meet your goal and will arrive past your deadline.   So as you travel along the road, you measure the KPI of your speed. That’s what is important to measure on your trip.  Of course you may measure other KPI’s like the amount of fuel left or the miles you’ve traveled… those certainly may be KPI’s you measure.  But you definitely don’t need to measure you compression ratio or oil pressure even though it’s available data from your car.  In the same way, when you are looking at web analytics data, you don’t want to track everything, only those things that are important to your business performance toward goals. 

Several activities can assist the creation of KPI’s.  Here are a few of them:

• Determine the Business Strategy.  Why is the company funding and developing an online mission?  What is the strategy?  KPI’s can help you figure out if it’s working.  To find the KPI’s that will help, the web analyst should be asking the question how can web analytics be used to formulate, implement and evaluate cross-functional decisions that will enable an organization to achieve objectives? How will web analytics be used in the process of specifying the organization’s objectives, developing policies and plans to achieve these objectives, and allocating resources to implement the policies and plans to achieve the organization’s objectives?
• Define the Site’s Goals and why the Site Exists.  I covered this in a post a few months ago.  A understanding of why your site exists enables you to effectively use online metrics.  You need to define the purpose of your site in order to create effective KPI’s.  Once you’ve defined your site’s purpose, you are positioned to examine Web data in way that helps you determine whether your site delivers on its purpose — does it exist effectively?   Create your KPI’s, identify goals for your KPI’s, and track your performance against those goals.
• Recognize Value Drivers.  How does the business make money on the site? Monetization, in cases where profitability is important, influences what you should be measuring.  If you run a media site, you probably make money from content consumption (the recency and frequency of content consumption), conversation (social media, such as contributions or comments), and conversion (the rate at which people complete certain value driving actions, like signing up for newsletters, rss feed, webcasts, print subscriptions, or downloading certain content types, like white papers).  So you create goals for and measure KPI performance around those value drivers.
• Map Organizational Roles.  Classify your organization into audiences for your KPI’s based what they do on your web site.  You may create KPI’s around function or action of the actors who receive your KPI reports.  Function defines the group that KPI’s are focused for, such as product development or editorial.  Action defines what those people do on the site to make it successful.  By understanding function and action of key actors on your sites, you gain insight into the type of data needed in KPI’s and the number of different KPI reports you may need to roll out.
• Understand the Customer.  KPI’s purely focused on internal function and actions are important, they need to be customer focused.   If you think measuring conversion is important, while your customers tend to come to your site for informational or non-transactional purposes and then go elsewhere to convert, you may be disconnected from the reality of why your site exists.   Learn customer goals from VOC (voice of customer) data and by examining historic behavioral data of key segments.  Make sure you don’t create KPI’s that are vain or inane.  Instead create KPI’s that help you guide action internally so that your business meets the needs of your customers.

Framing your KPI development around the five bullet points I listed above will help you create KPI’s that assist your team in guiding business performance toward goals - while not forgetting to consider some of the core elements of online business: business strategy, site performance goals, value drivers, the human organization, and the customer. 

Now segment, segment, segment your KPI’s!

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!

The infoglut in web analytics is enormous.  So much data.  Companies report that 69% of all people who consume the data don’t understand it.  How does a business go about making sense of it all?  Formulating a comprehensive KPI (Key Performance Indicator) strategy is a big part of differentiating signal from noise and directing appropriate tool usage.  We’ve all heard about KPI’s before.  They are ratios or derivatives of metrics that pinpoint critical, business relevant web performance.   My good friend, Eric, even wrote a book (a BIG one) about it. 

The process of moving an organization through KPI Change Management starts with a well formulated plan for doing so.  Here are some tips for formulating your KPI plan: 

• Educate senior management and get managerial buy-in.  Education and buy-in can take shape via a number of methods.  Maybe you publish and circulate an internal-only white paper about the importance of KPI’s measurement.  Maybe you leave Eric’s book on the chair of your C-level executives.  Perhaps you hold a meeting and present the web site optimization process and how measurement via KPI’s provides the foundational informational on which to make site optimization decisions.  Perhaps you take your boss out to lunch and explain that basic reporting and tool access is helpful, but “Web analytics is hard” and that KPI’s give context to the data to staff that’s otherwise somewhat confused about what they pull for the tool.  You explain that KPI’s provide a focal point for centering analysis around business goals.  Whatever the method, the goal is managerial approval that “yes, you can do KPI’s.”
• Determine the audience for the KPI’s and train them.The importance of KPI’s will vary by stakeholder, and your KPI strategy needs to take that into account. Different segments of stakeholders will be interested in specific KPI’s, and you must accommodate that need.  As an analyst, you should identify the functional roles and job responsibilities of the people who are going to receive KPI reports.   Everyone may not be the right choice (though it could be), and it may make sense to concentrate a KPI rollout on the needs of the few or it may make sense to “go broad.”  Follow up with comprehensive training about your KPI project and how KPI’s can most effectively be used.
• Start with simple, well-qualified, highly relevant KPI’s.  While some folks with want to throw a “kitchen sink” strategy at KPI’s.  That’s a mistake.  If you report more than 5 to 10 KPI’s (imho) per stakeholding group you may end up with a set of unworkable, confusing, and neglected reports.  It’s better to report just a few, well qualified, highly relevant KPI’s.  How do you qualify them? By mapping KPI’s to important business objectives.  How do you know they are highly-relevant? Because you’ve compelled management to buy-in and to agree that they are critical indicators of site success. 
• Elicit the business goals for the KPI’s, compare KPI’s to goals, and report associated variances (i.e. deviations). Make sure you have determined business performance goals for KPI’s.  Goals give context for performance. It’s that simple.  Without goals, you have no context for determining what’s good and what’s bad.  If your conversion rate KPI is 5%.  Great!  So what though?  If you know your goal is 3%.  Awesome job.  If you know your goal is 10%.  Stop reading now, and get back to work - you have much work cut out for you. 
• Identify the frequency and format for reporting.  You need to determine a frequency that is timely and sustainable, and the format in which you present KPI reports needs to common enough that people can easily examine the data. Perhaps you deliver the reporting in Excel, make it available directly in your tool, use Xcellius, or create reports using a BI tool. 
• Automate the delivery of the reporting.Without automation, you may put on the Report Monkey suit and enter Excel hell.  Critical to the successful rollout of any KPI reporting is an automation plan.  Do you email reports, put them in a shared directory, create a set of reports in the tool and provide access, or deliver them in weekly presentations?  The best choice is the option that gets people to use them, listen, and understand what you are trying to do with KPI’s.
• Following the reporting up with analysis and guidance.  Depending on the size and scale or your organization and the resources you have to work with, it may not be possible to provide every stakeholder with detailed analysis.  But you need to do your best to follow up KPI reporting with true analysis and guidance.  Why are KPI’s going up or down?  What are the drivers of the changes? 
• Segment, segment, segment. Site level KPI’s are helpful in understanding overall audience and customer behavior, but they hide important details.  When you slice a KPI by a specific segment, you will realize insights that help you conclude what action to take next.  Overall site repeat visit rate is 37%, but the repeat visit rate for customers who use your “product lookup tool” is 96%.  What does that data indicate about how you market the site, or about why people are coming to the site? 
• Test, test, test.  As you measure > report > analyze > guide based on KPI’s you will undoubtedly determine actions to take on the site.  You should be testing the hypothesis behind these actions via controlled experimentation.   

There’s obviously a lot more to talk about here - from what constitutes a good KPI, to what types of KPI’s different stakeholders should examine, to what are the best KPI’s for particular site types and more.  I guess there’s more blog posts for that, but in the meantime I hope you’ve found this blogviation useful.  Let me know if you have any thoughts to share.

That’s the first question to answer when determining strategy for using online metrics.  You should be able to answer in 10 seconds.  If you don’t know, or if key stakeholders can’t agree on your site’s purpose, then you are unable to use online metrics efficiently.  And, worse yet, you are missing chances for improving your business performance. 

Your web site exists for a purpose, perhaps multiple purposes, such as:

• Providing information or data.  Many sites entice people to visit for access to valuable, differentiated information or data.  Traffic is then monetized primarily through site advertising.  Many internal and external analytics packages will tell you where visitors come from and what they do onsite, which, when combined with demographic information, can be used to qualify a specific audience to an advertiser.
• Generating leads.  A content asset is placed on a site and gated using a form.  People fill out the form and download the asset.  The information captured in the form is stored and used by the company that generated the leads or profitably sold to another company.
• Selling products.  The typical ecommerce model involves acquiring customers via some method or offer, providing a product catalog or landing page, and creating a strong call to action and funnel that persuades people to purchase a product.
• Connecting people.  The explosion of social networking sites where people connect to other people, interact with each other, and use widgets, apps, and data services is a modern phenomenon in which many of us participate. 

Understanding why your site exists enables you to effectively use online metrics.  Once you’ve defined your site’s purpose, you are positioned to examine web data in way that helps you determine whether your site delivers on its purpose – does it effectively exist? 

Metrics and ratios that help you assess if you site fulfills its purpose are called Key Performance Indicators (KPI’s) – see Eric Peterson’s Big Book of KPI’s for a detailed review of the topic:

• For information or data driven sites, you may want to look at KPI’s that measure goal or task completion and conversion rates.  For example, if your site’s purpose is to expose video content to an audience, then a relevant KPI would be the percentage of all visitors that streamed a video or the number of streams per visit. 
• For lead generation sites, a key KPI you will track is the lead conversion rate.  In other words, of all the visitors that came to your site, what percentage of visitors successfully filled out a form and generated a lead. 
• For ecommerce sites, a key KPI that you might track is average order value, which is how much money the average visitor who purchases a product spends on a single transaction.
• For social networking sites, you may want to measure the average time between visits (latency) and the repeat visitor rate. 

But here’s the challenge with KPI’s: they are all academic, unless you have business goals for KPI’s.  KPI’s help you track progress toward predefined business goals.  What are the business goals associated with your site’s purpose?  For your informational site, what’s the goal for video streams per visit or time spent?  For your lead generation site, what’s the goal for the lead conversion rate?  By comparing business goals for KPI’s to actual KPI’s, you can begin to answer the question: “is my site successfully existing and fulfilling its purpose?”

You will continue to answer that question by segmenting your KPI’s, investigating distributions beyond averages, and using other techniques for data analysis.  You may ask: do certain referring sites, have a lead generation conversion rate higher than other referring sites, and why?  Do certain audience segments spend more time on site?  If so, where do they go on the site and what do they do?  If my goal for average time between visits (latency) to my site is five days, and certain customer segments haven’t visited in ten days (recency), what does that indicate about current business performance?

By defining why your site exists, creating KPI’s based on your site’s purpose, establishing business goals for KPI’s, and investigating what’s driving those KPI’s, you can enhance your online business performance in a way that increases bottom-line profit – from optimizing user experience and landing pages, to more efficiently allocating your marketing budget, to improving your product mix, and much more.

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.

About a year ago, I wrote a guest blog post over on Robbin Steif’s blog about using Google Analytics for tracking Javascript and Flash events.  This weekend Jeremy Geelan, SVP over at Sys-Con Media, asked if he could republish the work.  Of course I said “yes.”  Then I noticed that a lot has happened to GA in a year (and more to come, ahem, API’s!).  What I had wrote was now incomplete, so what you’ll find below is my attempt to sum up “event tracking” using ga.js and the Great Google’s Event Tracking Data Model.  Let me know how I did covering it, and if you think I should clarify of expand on anything.

Since we all know about page tags, let’s get down to business with “the Google” and how it tracks “the Rich Media.”  Google Analytics currently has two different javascript page tags:

• urchin.js.  The legacy version of the Google Analytics page tag.
• ga.js.  The current, rebranded version of the Google Analytics page tag.

How you track rich media depends on which page tag you are using.  I’ll discuss using urchin.js first, then ga.js.  I’ll also provide some information about Google’s Event Tracking function for capturing specific “events” within their event architecture.

Tracking Rich Media using Urchin.js

In the legacy version of Google Analytics, the smarties at Google created a little JavaScript function called urchinTracker() that enables event tracking.  Use the JavaScript function with an argument specifying a name for the event. For example, the function:

javascript:urchinTracker(’/mysite/flashrichmedia/playbutton’); 

logs each occurrence of that Flash event as a page view of:

/mysite/flashrichmedia/playbutton

Some caveats:

1. Always use a forward slash to begin the argument.
2. Actual pages with these filenames do not need to exist.
3. You can organize your events into any structure or hierarchy you want.

Important: Google says to place your tracking code “between the opening tag and the JavaScript call” if your pages include a call to urchinTracker(), utmLinker(), utmSetTrans(), or utmLinkPost(). For example, if the page view is the major event and the “play” event a minor event; then, your hierarchy would be Page View > Event, where the page contains an event, such that:

/mysite/ria_bittons/playbutton
/mysite/ria_bittons/pausebutton
/mysite/ria_bittons/playbutton
/mysite/ria_clips/clip

Some examples of the code (from Google Help):

on (release) {
// Track with no action
getURL(”javascript:urchinTracker(’/folder/file’);”);
}

This one above tracks when you click and release (although technically, it just notices the release) of a flash button (and records the file you specify as a page view).

on (release) {
//Track with action
getURL(”javascript:urchinTracker(’/folder/file’);”);
_root.gotoAndPlay(3);
myVar = “Flash Track Test”
}

The second one is the same, but by using a function, passing it a parameter, and identifying the instance you want to track, you can measure when your file was used in a specific scene in a little flash movie. So it is a more specific method for handling event tracking in Flash.

onClipEvent (enterFrame) {
getURL(”javascript:urchinTracker(’/folder/file’);”);
}

And the third one repeats the action throughout the movie so that each time the file is loaded, it gets tracked as an event. If you were to pass a unique file at the end of the movie, you could recognize it using this method (or the other methods) to know that the whole movie was watched (as long as your session doesn’t time out). Next, wait until Google updates your analytics, then check the Top Content report to see if it all worked. Now let’s discuss how to the exact same thing using the new trackPageview function released with ga.js.

Tracking Rich Media using ga.js

In the current version of Google Analytics, the brainiacs at Google created a little JavaScript function called trackPageview() that enables event tracking.  Use the JavaScript function with an argument specifying a name for the event.For example, the function:  

javascript:pageTracker._trackPageview (“/mysite/flashrichmedia/playbutton”);

logs each occurrence of that Flash event as a page view of:

/mysite/flashrichmedia/playbutton

Some caveats:

1. Always use a forward slash to begin the argument and use quotes around the argument.
2.  Actual pages with these filenames do not need to exist.
3. You can organize your events into any structure or hierarchy

You must put calls to _get._getTracker and _initData above the call to _trackPageView.  For example, you would insert the following code:

<script type=”text/javascript”>
var pageTracker = _gat._getTracker(”UA-xxxxxx-x”);
pageTracker._initData();
pageTracker._trackPageview();
</script>

Here are some examples of the ga.js code (from Google Help) that replicate what I described above using the most recent code:

on (release) {
// Track with no action
getURL(”javascript:pageTracker._trackPageview(’/folder/file.html’);”);
}

This one above tracks when you click and release (although technically, it just notices the release) of a flash button (and records the file you specify as a page view).

on (release) {
//Track with action
getURL(”javascript:pageTracker._trackPageview(’/folder/file.html’);”);
_root.gotoAndPlay(3);
myVar = “Flash Track Test”;
}

The second one is the same, but by using a function, passing it a parameter, and identifying the instance you want to track, you can measure when your file was used in a specific scene in a little flash movie. So it is a more specific method for handling event tracking in Flash.

onClipEvent (enterFrame) {
getURL(”javascript:pageTracker._trackPageview(’/folder/file.html’);”);
}

And the third one repeats the action throughout the movie so that each time the file is loaded, it gets tracked as an event. If you were to pass a unique file at the end of the movie, you could recognize it using this method (or the other methods) to know that the whole movie was watched (as long as your session doesn’t time out).

Tracking Rich Media using Google Analytics Event Tracking

When Google released ga.js in fourth quarter 2007, Google also released a data model for tracking events.  It provides more flexibility and ease of customization than the methods I described above.   The data model makes use of:

• Objects. These are named instances of the eventTracker class and appear within the reporting interface.

var videoTracker = pageTracker._createEventTracker(”Movies”);

• Actions. A string you pass to an event tracker class instance as a parameter.

videoTracker._trackEvent(”Stop”);

• Labels. An optional parameter you can supply for a named object.

downloadTracker._trackEvent(”Movies”, “/mymovies/movie1.mpg”);

• Values. A numerical value assigned to a tracked object.

To set up event tracking you should:

1. Identify the events you want to track.
2. Create an event tracker instance for each set of events.
3. Call the _trackEvent() method on your page.
4. Enable “event tracking” in your profile.

To instantiate an event tracker object, you might do something like this:

var myEventObject = pageTracker._createEventTracker(”Object Name”);
myEventObject._trackEvent(”Required Action Name”, “Optional Label”, optionalValue);

createEventTracker() is order dependent and must be called after the main tracking code (ga.js) has been loaded.Next you would call the _trackEvent() method in your source code either on every page that contains the event or as part of the tracking code for every page:

_trackEvent(action, optional_label, optional_value)

If you wanted to track interaction with the Flash UI, such as the button on a Flash Video Player, you would create a videoTracker object with name “Video”:

var videoTracker = pageTracker._createEventTracker(’Video’);

Then, in your Flash code for the video player, you would call the videoTracker object and pass a value for the action and label for the event:

onRelease (button) { 
   ExternalInterface (”javascript:videoTracker._trackEvent(’Play’, ‘MyVideo’);”)
}

You could also use the ExternalInterface ActionScript function as an eval() function to parse FlashVars and attach them to every Flash UI element that needs a tracking action.  For example, the code below associates a Stop action for the Video object and retrieves the provided label and value from the FlashVars:

onRelease (button) { 
   ExternalInterface (”javascript:videoTracker._trackEvent(’Stop’” + label + “,” + value + “);”)
}

Adding event tracking code would generate event reports in the Content section of the Google Analytics Interface.  Pretty cool stuff, Google!

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, un