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!

Next Sunday afternoon I am moderating a panel at eMetrics San Fran.  The panel is called ”Web Analytics -vs- Audience Measurement.”  Andrea Hadley at NetSetGo was the brainchild of this panel idea (and yes that is her picture on her site :).  In fact, I was a panelist on the same panel at eMetrics Toronto, filling in for my friend Marshall Sponder.  Since he’s going to be in San Fran, I yielded my seat 0n the panel and decided to stand up at the podium.   Other panelists include Jodi McDermott, Director of Product Management, at ClearSpring, and some other surprise guests (from comScore and IAB maybe)… You’ll have to show up and find out…

The panel description is as follows:

Are you confused about the number of customers visiting your website? Are the metrics reported by your web analytics tool different from the metrics reported by your online media, or by audience measurement organizations? The WAA invites eMetrics Marketing Optimization Summit attendees and the local San Francisco business community of web marketers, publishers and agencies to attend this community meeting. A panel of experts will discuss the value of the metrics, methods and tools used by web analytics practitioners, online advertising media and audience measurement organizations. Find out how-to use these metrics and tools to better understand your customers, your website’s competitive standing and overall website value.

The goals for this panel include:

• Adding clarity around the tools and data associated with each set of technology and metrics - web analytics technologies and website data, ad servers and ad data, and audience measurement tools and data.
• Learning how each data source can be used to expand our understanding of customers, how effective our website is as a business channel, the website’s competitive standing and value, and so on.
• Providing insight into the role of the web analytics practitioner and how this role is growing in importance and influence over business, marketing, product, and strategic decisions.
• Discussing the role of the Web Analytics Association (WAA) and how the WAA serves the practitioner.  That the WAA is an unbiased organization that doesn’t serve advertisers, publishers, or technology vendors, rather that the WAA serves and exists for the benefit and betterment of the the practitioner and the web marketer/strategist.
• Articulating the announcement made at eMetrics Toronto on the important collaboration between the IAB and the WAA for standards review.

My goal as the moderator is not to critique, demean, or criticize audience measurement, Internet advertising technologies, or to embellish or hype up web analytics tools.  Rather I hope to clarify the differences between the technologies and speak about the value they hold together - like I did in my article for MediaPost called the Yin and Yang of Online Metrics.

So why am I telling you all of this on my blog???  Well it’s because I really want your help, whether you are going to eMetrics or not…  Since I’m the moderator, I get to ask the questions, and I don’t want to just ask “my” questions, I want to know what questions YOU would ask if you had the chance to ask.  Of course, those of you reading this and attending the panel will be given the microphone if you raise your hand.

Please help my crowdsource by telling me in comments or via email to judah (at) webanalyticsdemystified.com:

What questions would you ask to clarify the differences and value between web analytics and audience measurement tools?

Any questions you think worth asking from “why don’t the numbers match?” to complexly “what are the differences between audience measurement and web analytics systems in terms of data collection?” would be awesome and appreciated.  Thanks in advance for your help!  I’m eager to see if this social media experiment in blog-based crowdsourcing actually works!

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!

Hello good readers!  Every month I write a column for MediaPost’s Metrics Insider.  Here’s my most recent one:

Companies that derive revenue from multiple channels often have two analyst teams: the “database marketing team” and the “Web analysis team.”  These groups tend not to communicate.  In some companies, however, these teams are merging to form the “multichannel analytics team.”  This specialized team analyzes, reports, and evaluates both Web data and offline data — often in coordination with the “business intelligence team.”  The emergence of this new team structure makes sense for companies that are shifting their offline business models to become more online-centric, and thus want to understand value-generating connections among channels. 

Several macro-level catalysts are necessitating the shift to a multichannel approach to data collection and analysis.  The ongoing mainstreaming of the Internet channel for enabling commerce, conversation, and relationship marketing is certainly pushing this movement.  The burgeoning set of analytics tools that integrate with other technologies to enable event detection and trigger a customer-specific response is also promoting change in the way companies think about connecting offline and online data to improve overall business performance.

If database marketers and Web analysts are evolving into a new type of team, then what roles are necessary on this new multichannel team?  Here are a few:

• Web Analyst.  The overall Web analytics professional has a deep understanding of the Web channel.  This person uses a Web analytics tool to understand the performance of site traffic, online marketing campaigns, and to segment Web data in order to understand how visitors referred from certain channels navigate (or don’t) through the site.  They understand, measure, and report whether the site is fulfilling its purpose for conversion, task completion, and other KPIs when compared to business goals.  
• Site Optimizer.  A niche type of Web analytics professional, the site optimizer is in charge of determining the right approach for configuring and reporting the results for AB (champion/challenger) and multivariate tests.  This person is all about testing components of site and page design to yield the best combination of elements that provides a lift in a particular metric against a goal, such as conversion rate.  Content targeting may also fall under this person.
• Social Metrician.  Another niche type of Web analytics professional, the social media measurer is concerned about the performance of customer touchpoints outside of the main Web site.  He or she collects, monitors, and analyzes data related to things that happen “out there, on the Internet,” such as syndicated video, mobile, widgets, blogs, social networks, and other social media.
• Database Marketer.  The traditional offline analyst and database miner.  This role analyzes data from channels that are not online but may reference and promote online interaction, such as television, radio, print, catalogs, and direct mail.  Of course, these analytics skills can be applied to online data as well!
• Search Analyst.  The analytics professional in charge of keyword identification/selection, keyword management, bidding, and analyzing the outcomes of search.  He or she may be in charge of analyzing site performance against known SEO goals too, not just SEM.
• Market Researcher.  The traditional market researcher gathers, analyzes, and reports data about the overall market, key competitors, and customers. 
• Qualitative Analyst.  Part market researcher and part analyst, this individual is in charge of online customer and visitor surveying, relating customer feedback and visitor opinions to the context of on-site behavior to help deduce “why” people did something on your site.
• Ad Analyst.  Solely dedicated to assessing the performance of advertising campaigns, the ad analyst assesses and educates clients on ad campaign performance both online and offline.
• Audience Measurer.  The wielder of an audience measurement tool informs competitive decisions, influences media plans, and provides benchmarking and competitive data to give context to other data analysis activities, such as keyword bidding or media buying. 

How would these professionals all work together?  The market researcher’s data is used to help craft a customer-focused and competitively differentiated campaign strategy.  The audience measurer provides data that focuses the strategy on the right online demographics and sites, while the database marketer mines historic data to figure out the best-performing offline tactics for the identified demographics. 

Let’s say a mix of search, social media, and online and offline display ads are selected as part of the campaign.  The search analyst concentrates on SEO/SEM, while the ad analyst tracks the performance of display ads.  The social metrician examines the social media ecosystem’s response to the campaign.  The Web analyst analyzes how campaign-referred visitors behave and navigate through the site, taking into account the context of the qualitative analyst’s voice-of-customer data.  Meanwhile, the site optimizer tests landing pages and funnels to ensure they effectively convert visitors and fulfill business goals. 

For many companies, it would be unrealistic and perhaps impossible to find and hire people to fill each of the roles I’ve presented above.  In fact, in most companies these roles and activities are completed by only a few people, if at all.  An option for companies that seek to expand or combine teams is to look at consultants, contract workers, and full-time equivalents allocated across multiple people.

That said, companies that are unable to bridge together online and offline analytics teams will miss important data points.  In the digital future, we’ll see different types of analytics professionals working together across channels to yield profitable insights that support campaign and business goals.

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.

eMetrics Toronto is about two weeks away, and Boston Web Analytics Wednesday is tomorrow night.   I’m pretty excited for both events.  

I think eMetrics is thee premier web analytics and marketing optimization conference.  I’ve been to a bunch of them, and I always walk away with new ideas with which I can hit the ground running when I get back to work.   The real world case studies, practitioner advice, vendor spiels, and the cadre of notable analytics and marketing professionals who attend and make themselves available to you, the attendee, is unmatched.  

Web analytics pals Jim Sterne (and Andrea Hadley in Toronto) in association with Rising Media ensure the content and tracks focus on the knowledge needed today to drive the real-world application and usage of analytics and marketing measurement technologies in way that enables your online competitive advantage tomorrow.  eMetrics is far beyond a beginners conference (though there’s always plenty of good stuff for beginners).  Gone are the days talking about simple definitions and whose tool can do what (though they’ll be plenty of that stuff covered in some sessions, at lunch, in the bar).   Today’s eMetrics is focused on the application of analytics in business context, especially in the context of marketing.  The conference, as I see it, is about what you should measure and how to take action from what you measure in order to improve business performance and increase top-line revenue and bottom line profits (while reducing middle-line expenses).

I’ll be there in two sessions.  The first session I’m in is on Monday afternoon and occurs in two parts.  The first part is where I’ll fill in for my buddy Marshall Sponder, Director of the WAA and Chair of the Social Media Committee, and give an update on Social Media Committee activities.  During the second part of session, I’ll participate on a panel moderated by Chris Williams, Managing Director, Media Contacts Canada, and panelists Brent Bernie, President, comScore Inc., Paula Gignac, President, IAB Canada, and Jodi McDermott, Director, Product Management Clearspring Technologies.  We’ll be talking about the importance of standards, collaboration between industry organizations, and the real-world application of all the measurement tools you can use to run an online business (and more).

In the second session, on Wednesday afternoon, I’ll be on another panel speaking about the analysis of audience behavior and engagement levels on media and content sites.  Sitting alongside me will be moderator Mitch Joel, President, Twist Image, Sibel Satiroglu, Interactive Marketing, Hewlett Packard, and Mike Sukmanowsky, Web Analytics Specialist, Rogers Media. 

Should be some good conversation.

For those people trying to gain insights from the data, to those actively working on taking action from the the data, and for those who are trying to manage it all, I highly recommend attending one of 2008’s eMetrics Summits.  If you’re in Canada or nearby or really anywhere on Earth, now’s the time to sign up for Toronto.   

And for those in the Boston area tomorrow night (3/19), please join me at the monthly Web Analytics Wednesday I host.  This month, Jonathan Mendez, Founder of RAMP Digital, will be presenting on the “Crawl, Walk, Run” approach to onsite targeting.   Omniture is sponsoring and providing free food and drinks for all attendees, so swing by and swing back a drink whilst enjoying some smart conversation.

See you at both events.

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

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

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

Now for some random thoughts:

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

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

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

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

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

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

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

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

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

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

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

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.

I’ll get back to talking about the web analytics team soon, but I’ve been getting a few emails from folks just starting out who are a bit confused about data collection.  So I figured I’d blog about it…

When web analysts talk about data collection, they are referring to the method by which counts and measures of things, like page views and durations, are captured by a web analytics tool.  If you’re new to web analytics, data collection can be slightly confusing.  There are three “generally-accepted” methods for data collection in the web analytics industry: 

• Page tags.  Client-side data collection involves using little snippets of HTML code that reference a JS file and communicate via a beacon to a “page tag server” - the machine that collects the data so it can be sessionized by the web analytics tool (it may not be called that by your vendor).  As a web analyst, if you are using page tags you will have lots of fun tagging every page on your web site and instrumenting the tags with custom variables and campaign codes.  Reasons why people like page tags are numerous, and include the fact that they are fairly efficient in filtering out non-human traffic (as long as the robot doesn’t execute javascript) and can count proxy cached pages (improving accuracy). Page tags are probably the most ubiquitous method for collecting web data today.
• Log files. Server-side data collection involves parsing text-based log files generated by Web servers.  The server, when instructed to do so, logs every request received by clients in a file called the “log file.”  There are many formats for log files.   Each line in a log file is called a “hit” and contains lots of different stuff - from the ip address, a request date/time stamp, the item requested, user agent, referrer, and more.  Many “hits” make up a single page view - that’s why it’s incorrect to use the term “hits” to refer to “page views.”  As a web analyst you will be defining the format of the log file within your tool and moving and synchronizing log files so that they can be processed by your tool.  Some people will claim log file analysis is dated (historic may be more appropriate), or less accurate than page tags (due to caching issues).  Other people like logs because they can reprocess their data. 
• Packet sniffers.  Network data collection involves deploying either software or hardware that intercepts and logs traffic coming over a network.  Every packet is captured and decoded according to a configuration you define.  Your web analytics tool can be configured to process the data captured and decoded by the sniffer.  Packet sniffers are a less common approach for data collection by web analytics vendors.  

Interestingly some vendors offer “hybrid” data collection, which combines multiple data collection methods.  This mode could be considered a “fourth type” of data collection.  Most commonly hybrid data collection means using logs and page tags to collect different data elements, but other combinations are possible as well. 

As you investigate the best data collection method for your implementation ensure you deeply consider the pros and cons of each method.   For example page tags capture information about the browser (like screen resolution) that logs just can’t.  But what about if you need to measure non-javascript executing clients, like some mobile devices?  Log files capture information about crawlers (i.e. robotic traffic) that page tags just can’t.  But can you adequately filter robotic traffic and maintain host exclusions?  Packet sniffers capture pretty much everything, but can be challenging to customize to your exact data needs (and you’ll need a fair amount of IT support). 

Which one is correct for your implementation?  It depends on your business goals defining what you need to measure…  

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>