Web Analytics Blogs

Judah Phillips is an experienced web analytics practitioner and Internet expert currently working as a Director at a large multichannel media company. His blog is full of useful, unbiased, actionable insights learned from the real-world practice of a process-oriented, integrated approach to strategic Web Analytics for improving business performance.

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Archive for 'Performance Management'

Performance, Performance, Performance

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.  

Some More Thinking about Key Performance Indicators for Web Analytics

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 ExistsI 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!

The Multichannel Analytics Team?

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.

Part 2: What Does the Web Analytics Team Look Like?

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.

webanalyticsteam_part2.bmp
Image by Jim Sterne, from Emetrics 07 San Fran.

Tracking Rich Internet Applications with Google Analytics

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!

google-analytics-event-tracking.png

Web Analytics needs IT and the Business needs Web Analytics

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

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

The classic problem goes something like this:

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Part 2: Web Analytics Tools – How Do I Know I’ve Outgrown Mine?

Web analytics tools can be outgrown, like houses, clothes, shoes, music, books, and ways of thinking about the world…  But how do you know when you’ve outgrown your web analytics tool?  In part 1, I began the list of five symptoms of an outgrown web analytics solution, which was spawned out a preso I recently gave.  The five symptoms include:

So without further adieu, here’s the rest of the list and some thoughts regarding these symptoms (click here for Part 1):

  • Limited Integration.  Soon after deploying a web analytics solution, you will become intimately familiar with clickstream data and simple counts of things (like page views) and measurements (like time).  You will hopefully have deployed Key Performance Indicators for understanding how effective your web site is at converting visits and meeting defined business goals.  Depending on the web analytics tool you use you may even have insight into the behavior and KPI’s of visitors from online channels like newsletters, search, and rss because you have applied “tracking codes.”

Soon will come a time when you may ask yourself how do I integrate data from other data sources?  You may want to bring data from an email service provider, CRM system, and registration databases, so that you can see delivery rates next to conversion rates from newsletters, or so that you may pass behavioral information about a visitor who registered on your web site.

You may want to move data out of your web analytics system.  Perhaps you want to feed your data warehouse?  Or you may want to feed web analytics data into a targeting system.   Simple XML-based feeds from a hosted solution may not suffice.  You will need access to your data in a open database. You may even want to stop non-human readable text and character strings from appearing in your reports. To do so you may need to lookup data using various methods in order to make reporting comprehensible.  All of these goals require some level of integration.

If your current web analytics tool can’t:

  • Provide insight into all online channels
  • Enable you to bring data from other systems into your web analytics platform
  • Pass Web Analytics data to other systems.
  • Manipulate data by looking up values, resolving urls, and decoding parameters

And do all of this at a reasonable cost in a maintainable way using in-house resources, then you may have outgrown your web analytics solution.

  • Cost.  Web analytics done right isn’t cheap.  It costs money to maintain and extend whether you run an in-house solution or external solution.

When running an in-house web analytics costs are spread out across hardware and software and resources:

  • Software license.
  • Recurring maintenance costs.
  • Servers (one or more).  Perhaps you virtualize (it cost money for the virtualization software).
  • Database license(s).
  • Storage.
  • IT resources - people like project managers, application engineers, and dba’s.

As you expand your web analytics operation, all of these resources and technologies will need to scale.  Time will need to be devoted to maintaining it all, and time costs salary dollars. 

Your company will, hopefully, grow.  Then you will have more sites.  These will need to be tracked.  New reports will need to be created, tested, and rolled out into production.  New data and systems integration requirements will spring up.  All this has cost.

On the other hand, if you are using a hosted solution, you will need to extend the page tag and tool configuration when you want use more features or integrate systems and data.  That means spending money to use vendor professional services or consultants, unless you want to dedicate internal resources in IT who may already be overburdened.

At some point you say enough is enough. The COST is too much!  You then decide to invest in well-negotiated vendor solution that provides a lower TCO over some horizon.  When you start to run up against the barrier of cost, you may have outgrown your web analytics solution.

So that’s the list.  I can think of many more reasons why companies outgrow their web analytics tools…  What have I omitted?  What do you think?

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Web Analytics as Performance Management and Optimization means defining Goals and KPI’s

A successful web analytics practice helps a business manage its performance toward goals.  If you believe the statement, then you understand that in order to manage for site performance, a web site must exist to support one or more goals.  Pretty logical, right?

Then why is that web analytics practitioners tell me they often encounter web site owners who have no clear, measurable goals?  It’s really strange.  In fact, it’s vexing and frustrating because without known goals you OBVIOUSLY can’t manage site performance.  Without goals you can’t really optimize anything and are left to simply tracking trends related to basic metrics and/or derivatives thereof.

Thus, one of the responsibilities of a web analyst is identifying and confirming site goals.  Once you have site goals, you can create KPI’s that you monitor on a regular basis investigating variances, anomalies, and outliers affecting site performance. 

Undoubtedly one of the goals you will identify for your site is some type of conversion.  A conversion is a value-generating transition on your site.  For example, the successful completion of a form that enables a visitor to download a content asset or completing the purchase of a product may be a type of conversion you measure. 

While overall site conversion rates for value-generating events are important to know, real insights come from segmenting visitors or other dimensions by conversion rates.  The best analytic tools enable you to identify the conversion event and slice the conversion by any dimension: page, geography, referrer, keywords and so on. Thus measures of conversion will be instrumental KPI’s when using analytics to manage performance. 

The notion of a “funnel” in web analytics is a sequence of one or more pages that a visitor clicks-through until reaching a final destination, the conversion event.  The “funnel” assists the analyst in understanding the discrete clickstream that led to conversion.  For example,  a pre-defined path through the pages in the subscription or download process could be considered a funnel.  Funnels can be linear and non-linear and are affected by all sorts of things like detours, fall out, abandonment… That’s a post for another topic…  Yet, the metaphor of the funnels is applicable across all sites…  This notion becomes problematic when we consider multichannel attribution of the conversion process (again another blog post when I have time).

So what’s an analyst do when they want to begin to use web analytics to manage performance against goals? Here’s are some tips:

  1. Investigate the business’ revenue model. Advertising-based sites generate revenue from selling various types of ad units (rpm/cpm), contextual advertising (rpm/cpc), lead generation programs (rpl/cpl), revenue sharing, and via affiliate syndication and content sharing deals.  Ecommerce sites generate revenue by selling products or brokering services or transactions.  How does your site generate revenue?  If the goal of the site isn’t to generate revenue, then skip this step.
  2. Ask key managers to identify business goals.  Top-level managers have a better grasp of the vast ecosystem of suppliers, buyers, and other priorities that you, the analyst, may not be privy to.  Your manager should be helping you put your analytics work in context of the business goals.  So ask your boss what are the site goals?  Don’t accept the answer “to drive revenue.”  Ask how the identified goals support value creation and revenue generation.  The measurement of events supporting business goals should be a focus for performance management and optimization. 
  3. Identify the conversion events that support businss goals and the revenue model, including any necessary steps in the funnel.   The actions that satisfy goals are the conversion events. The transition involved when the visitor clicks and makes the site money is your discrete conversion event. The page immediately preceding the conversion event is the last step in the funnel. 
  4. Determine the actors on the site.  Actors can be categorized into internal/external actors.  For this exercise, concentrate on identifying the roles and responsibilities of the internal actors who DIRECTLY influence site production.  In other words, who are people modifying the site and what do they do?  The indirect actors, like your boss, also affect the site, so make sure you consider their role and responsibility in advanced site goals and fulfilling the objectives of the business model. 
  5. Determine the goals of the actors.  Like site goals based on revenue, all indirect and direct site actors will have goals specific to their jobs.  Actor goals support site goals.  Thus, actor goals can be translated to tactical KPI’s.  For example, the editorial actor may want to ensure that X number of newsletter-referred visitors subscribe to the print magazine, so you create a KPI’s “subscription conversion rate by newsletter” and “number of online subscriptions generated per newsletter.”  Based on the site goals for conversion and the number of subscriptions generated from the online channel, you can start managing editorial performance.
  6. Document site goals, actor goals, conversion events, and funnels, including a diagram a hub-and-spoke model of actor roles and responsibilities and flow diagrams of funnels.  In order to establish a process for performance management via web analytics, all the actors must generally agree on roles and responsibilities.  By documenting your investigation, you confirm correctness, identify gaps in business process, and create alignment among actors and management.  You may notice breakpoints in site production processes too.  The end result is a fully-documented operational model of how your site is created, monetized, and deployed.  In the same way that you can’t manage what you don’t measure, you shouldn’t be measuring things you can’t manage.   
  7. Have key managers who direct site actors sign-off approval on the documentation.  The holy sign-off confirms you correctly identified the revenue model, site and actor goals, site navigational flows that lead to conversion.  When questions arise you can reference this process artifact to backup the conversion events you defined, the KPI’s you’ve created, and subsequently the performance recommendations you will make and manage.

Then:

  1. Configure your web analytics tool to report conversion rates for revenue-generating site transitions and events and to report on funnels.  All tools can do this. 
  2. Build KPI’s based on specific functional goals performed by actor’s on the site. Base KPI’s around activities that support the core revenue model and the activities performed by site actors.
  3. Review KPI’s with actors.  Bring your documentation and identify how the KPI’s will be used to identify performance, contextualize optimization recommendations, and help each actor be more successful at their job. 
  4. Report conversion rates and KPI’s to key managers and site actors.  Optimally these performance metrics should be available for actors and other stakeholders whenever they want them, preferably in the form of dashboards elicitable from your web analytics tool.  The goal should be identified, the target value for the goal, the KPI measurement,  and any deviation from the goal should be noted along with written performance recommendations.
  5. Research site performance by segmenting conversion rates and KPI’s and investigating drivers.  KPI’s provide context for understanding the actions that influence site performance.  Overall conversion rate will only tell you so much.  For example, to the SEO conversion by organic search referrer is more informative.  Other actors will require reports on segmented conversion specific to their function. 
  6. Make optimization recommendations.  Whether you deliver recommendations via reporting or manage the multivariate testing function at your company, you’ll need identify the events or actions to optimize.  Then you need to get buy-in from various gatekeeping actors.
  7. Test and implement optimizations.   Use a multivariate testing vendor to test combinations of content and creative that drive KPI’s and that provide lift in conversion.  Work with site actors to ensure optimization testing and controlled experimentation occurs.
  8. Rollout optimization that increase conversion, improve goals, and drive revenue.  Once you are reasonably certain the optimizations you are suggesting will improve performance work with the web or product development team to realize these changes.

Thus web analytics for performance management involves:

  • Goal Clarification.  Why does this site exists in the first place?  Don’t be surprised to learn different actors have different goals, and no one is aligned!  From what I hear on the street that’s a common issue!
  • Stakeholder Alignment.  Do all stakeholder and actors agree on the reasons why the site exists?  If not, be prepared to mediate.
  • Experience Optimization.  How is the visitor interacting with my site, and do those interactions channel visitors to conversion funnels?  Do relevant calls to action and points of resolution work for persuading visitors to convert.  What’s working?  What’s not?  Figure it out.
  • Controlled experimentation.  Based on potential optimizations available, what do you test?  Multivariate testing software can help, as can VOC research.  Talk to your research team.  Use the AB testing feature of your web analytics tool…  Whatever you do, you should establish a repeatable process for doing so. 
  • Outcomes measurement.  If you set up a KPI dashboard with goals, actual performance, and variances you will be able to answer that question “so I did all this stuff, so what effect did it have?”

Easy right? Now get to managing performance using web analytics! :)

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