Eric Peterson of Web Analytics Demystified invites all practitioners, vendors, and consultants to participate in the Fall 2007 Web Analytics Demystified Survey.  This season’s survey focuses on web analytics tools and examines distribution of deployment and overall satisfaction.

It takes about 15 minutes to complete.  As an incentive Eric Peterson is offering a 50% discount on his Big Book of KPI’s. 

And the big bonus is that all the resulting research will be made available on the WAD site for free (the Spring 2007 survey research is here).  Please lend your voice at:

Take the Web Analytics Demystified Fall 2007 Survey Right Now!

Forrester’s Megan Burns is seeking ALL web analytics consultants to complete this 10-minute survey:

http://globaltestmarket.com/survey/s.phtml?sn=86482&lang=E&secid=0fd357

Megan will be publishing a list of every web analytics consulting firm later this year.

In addition, if you would like to meet Megan in person, listen to her speak, ask her questions, and receive a FREE copy of Forrester’s Web Analytics Vendor Evaluation (the $995 Wave), you should attend the Boston Web Analytics Wednesday I host every month.  Sign up to attend the event in Cambridge MA on 10/24:

http://www.webanalyticsdemystified.com/wednesday/?event_id=2102

Last week I attended the 1st Annual SEMPhonic XChange and led a collaborative discussion on “deploying measurement systems in distributed companies.” In case you hadn’t heard about SEMPhonic, the company is a boutique consulting firm in Novato, CA (near one of my favorite towns on Earth: San Francisco).  They do some very unique work with web analytics (Functionalism) and other facets of new media technology.  A fine gentleman named Gary Angel leads the group. He’s recently hired smart folks, like long-time web analytics expert, June Dershewitz, and notable blogger and author of the Web Analytics Report, Phil Kemelor.

A few months ago the idea came up for me to lead a “huddle” at their Xchange conference.  I was intrigued with this huddle idea.  It was different. New.  I’d facilitate a discussion on a topic of my choice in a small, Socratic, group setting.  No PPT!

Fast forward to last week, and I found myself sitting in Napa, CA at COPIA: The American Center for Wine, Food, and the Arts. COPIA was a brilliant place for an industry colloquy.  Being a guy who likes culture (and conferences), this venue offered the best of both worlds.  Instead of a hotel, I found myself surrounded by gardens, vineyards, art, food, wine, web analytics, and the brightest in the industry.  Cool!

Thinking back on the event, SEMPhonic Xchange, in my opinion, is a “must-attend conference.”  Not only is the “huddle” format unique and fun in which to participate, it’s also a format that promotes deep discussion that leads to truly actionable insights. It’s a conference based on dialog and collaborative discussions between participants.  The huddle format provides 10 hours of free collaborative consulting (5 huddles) with employed people you can’t hire (and some consultants you can)!  Compare a daily consulting rate to the conference cost, and it’s a no brainer.

My discussion on best practices for the successful deployment of measurement systems lasted a little over two hours.  My group collaborated nicely (so I thought).  It included very intelligent folks like Jared from Intuit, Scott and Christel from Xilinx, Sami and Fred from Adobe, Renata and Matthew from American Express, Aaron from Webtrends, Rupa from Cisco, Amy from JPMorganChase, Jeff from New England Journal of Medicine, and Kevin from Charles Schwab.  Thanks to anyone reading this blog who attended.  Your valuable insights and knowledge sharing contributed to the success of the huddle.

At the ends of the huddle I went over a tips for a successful deployment.  Here are a few:

• Identify business goals, match those goals to business strategy, and align metrics and KPI’s to support those goals.  I always say “metrics and kpi’s have significance in position and relation to a goal.”  You can’t measure against performance unless you’ve identified your business goals.  Goals are supported by strategy.  You create KPI’s for measuring against goals and for guiding work toward objectives.  Every business unit could have different goals.  Management must align and support the standardized goals that you bake into your KPI’s (and any specific derivatives you create to support the goals of differentiated business units).
• Verify the technology implementation and the metrics collected.  A web analytics or other measurement system must be verified to ensure conformance with “standard” best practices based on the company’s goals.  You need to make sure the numbers can be trusted.  That means, validating data and reconciling differences with historic reporting systems or whatever the business demands, understands (and possibly pays for in real dollars, time, or resources allocated), such as ABCe, WAA, IAB, MRC, XYZ, 123, FBCINSA whatever it takes…
• Provide education and training.  While some analysts want to keep all the data within their analytics group, I don’t think that practice scales across a large enterprise unless you are lucky enough to have a large analytics team.   I know I can’t individually and alone satisfy the metrics needs for thousands of stakeholders or hundreds of brands.  Successful companies deploying on a large scale adopt a “train the trainer” approach.  The trainers guide their business units, become local experts, and help foment a data-driven culture.   Let the data be free and the people educated, I say. 
• Consider the corporate culture.  A metrics tool changes organizational culture (for the better or worse).  Suddenly, everyone is being measured and perhaps evaluated on goals implicit in the measurements.  Some will greet the tool with open arms while others will see it as a threat.  Solid management needs to foster buy-in and support for the tool.  That way, organizational resistance is overcome and clarity of mission is realized.
• Help business units ”use the metrics” to improve performance.  My friend Eric Peterson likes to say “web analytics is hard.”  Yes it is!  That means the expert needs to work with global business teams to mentor and teach how to separate signal from noise.   As the tool is used, business units will identify “pain points” that will need to be addressed.  The analytics team should work with business units heal the pain and improve performance.
• Plan to ”get granular” and the “get integrated” with the measurement system.   Additional requirements will come out of the woodwork due to organizational learning after you golive (even if you think you’ve elicited all reqs prior to deploying your tool and building reports).  New requirements are an early sign of success (people are “getting it” after all).   As the business learns, it will become necessary to extend the system.  Consider brainstorming about the possible ways in which the system should be extended prior to rollout, and perhaps create a basic plan for extending the system. When the system is launched, modify that system enhancement plan and execute on it to support business goals.  Employ a project manager to plan and help execute!
• Manage and guide stakeholder expectations to minimize risk.  Be realistic when for guiding and setting expectations so that you can minimize risk (to your overall mission, your job, the company ;).  Risk comes from incorrect metrics, organizatonal issues with adoption, changes in business goals, shifting managerial priorities, technology problems, and issues resulting from resource allocation.  Make sure you manage around these issues or find ways to directly deal with them. 
• Generously explain why the measurement system is being deployed and more.  You must create a well-thought out communication plan for promoting adoption and use of a metrics tool.  The communication plan should focus on answering:
  • Why the tool is being deployed.
  • What people are supposed to do with the tool.
  • How people should use the tool.
  • What key metric/KPI’s people and business units should be looking at to manage their performance.
  • How to go from “insight to action” based on analysis of the metrics.
• Share best practices and lessons learned across the enterprise.  As new insights are realized and the company starts taking action from the metrics, you should provide a way for the enterprise to communicate the “highest and best use” of the tool.  By promoting collaboration and knowledge sharing, the company is more likely to succeed quickly with the measurement tool and realize a demonstrable ROI from it.
• Realize that “premature optimization is the root of all bugs.”  When deploying a measurement system, you need to establish a baseline system before extending the system to get more “granular.”  An implementation must be granular before integrating data from other systems.  While these concepts will overlap in deployment and may occur in close proximity or in a waterfall (i.e granularity may be enabled via integration) you need to ensure you don’t put the cart before the horse.  Make sure you correctly measuring and understanding the basics (like recency, frequency, clickstream, referrers, bounced visits, and depth) then moving forward with more advanced and necessary measurements and reporting (like bounce rate, conversions, view thrus, voice of the customer, and ”engagement.”)   Set clear expectations and guidelines with the consultants.  Don’t move too fast with development.  QA, then segment away, I say… ;-) 

A lot of more was discussed and shared over in Napa and throughout the SEMphonic XChange conference.  Please share your thoughts, if you feel like it!  Thanks for reading!

Awesome news.  Thanks to my friend, Dylan Lewis -some call him Bob or Meriwether- the web analytics industry has a WIKI.  According to the almighty “define:” operator at Google via Answers.com, a Wiki is:

• A website or similar online resource which allows users to add and edit content collectively.
• A collection of websites of hypertext, each of them can be visited and edited by anyone. “Wiki wiki” means “rapidly” in the Hawaiian language.
• Online collaboration model and tool that allows any user to edit some content of webpages through a simple browser.
• A web application that allows users to add content, as on an Internet forum, but also allows anyone to edit the content. Wiki also refers to the collaborative software used to create such a website.

In true New England diction, it’s a wicked wiki.  Wicked awesome that is.

Here’s the word from the Passionate Analyst, himself:

I am pleased to announce that WikiWebAnalytics.com is now up and running. WikiWebAnalytics.com is THE place to provide details, articles, lore, and information about the world of web analytics.

http://www.wikiwebanalytics.com/

This wiki is meant to provide an online resource for web analytics professionals and people wanting to know more about web analytics. Contributing to it will help shape the web analytics industry, community, and future web analysts.

Here is the goal - create 300 articles in 3 months. 300 articles will help the wiki become THE resource for new and existing web analytics professionals.

Check it out at http://www.wikiwebanalytics.com.  Have fun starting an article or editing one. 

It may be high time for the Standards Committee at the Web Analytics Association to add currently-approved definitions, methinks.

Found this site in blogistan:  The Open Web Analytics Project. 

Peter Adams, former CTO of LookSmart (NASDAQ:LOOK) wants to “make analytics free.”  While I already thought we had a rather awesome free tool, it looks like Peter may also want to “make analytics open.”  That’s inspired me to alert you about his work in my blog.

I quote:

“Open Web Analytics (OWA) is an open source web analytics framework written in PHP. OWA was born out of the need for an open source framework that could be used to easily add web analytics features to web sites and applications. The OWA framework also comes with built-in support for popular web applications such as Wordpress and MediaWiki. As a generic web analytics framework, OWA can be extended to track and analyze any web application.”

While I haven’t dug into this project deeply, I’m intrigued on the surface for a number of reasons:

1) Free.  OWA even has a wiki.

2) Open and Interoperable.  Supports a PHP API, PHP invocation, HTTP API, and Javascript.

3) Integrated with WordPress and MediaWiki. New media features are provided out of the box.  RSS tracking is present.  There’s Google Maps integration (visitor plotting), and it outputs Google KML files (for Google Earth).

4) Event-based framework.  Composed of ”event types and event handlers“ that perform a specific analytic or logging function. “Events are composed of an Event type and a message. An Event’s message could be an array, object or any other data type.“ 

5) Provides developers with a feature set including a full model-view-controller based framework, a extensible module and plugin framework, an object relational mapping layer, and a lite templating layer.  Database-driven configuration.  There’s even a heatmap (ClickHeat project).

OWA provides an interesting model for how vendors can move toward technical openness.  To me, OWA is another sign of how innovation outside of the “top vendors” pushes our industry forward to adapt to the rapidly-evolving internet and the future need for system and business actuation from integrated analytics.  

If this innovation can generate scale, it has the potential to be disrupting, but right now it still seems a bit esotericly technical and overly dependent on one person (but that’s how Linux started isn’t it…).  The average marketer wouldn’t know how to get started with it, but the Web 2.0 geek would know how use it.

I’m looking forward to seeing if new mashups provide open access to their analytics using OWA… 

One to watch…

I’ve opened a can of worms!  

First read these posts:

• Eric, which if you’ve found me, you’ve probably already read.
• Avinash, which if you’ve already read, you probably found me.

Here’s my take, and let the flames begin:

• Enterprise-class web analytics is SOFTWARE. 

Personally, I’m just not the biggest fan of on-demand, SaaS, ASP, or whatever term you want to call it for web analytics.   I’ve certainly considered and used a whole bunch of hosted solutions.   The limits of a hosted solution quickly became abundantly clear to me in this industry when I needed to “do web analytics” on a real scale that required deep integration, beyond my past of one site, subdomains, or a couple of sites and subdomains. 

Maybe those aren’t your needs.  A hosted solution may be the right choice for you.  That’s great.  In fact, maybe if those are your needs and you have an unlimited budget for rollups, extracts, segmentation, filters, that model may be absolutely perfect for you.  They all have excellent features.  They all were built by smart people and have good support teams.  They all help solve real business problems.   They are proven to work (usually).  I may use them again in the future.

Don’t get me wrong, I appreciate and respect the on-demand, SaaS, ASP model.  Big time, mucho respect.  Other systems, like CRM (salesforce.com), work very well for companies everywhere, and the model works well for the many wonderful web analytics vendors who have entertained (and frustrated) me and other customers with the hosted model.  I find hosted web analytics models just fine and dandy for reporting and analysis, not integration.

Wikipedia is right.  Enterprise class software brings together all departments under one tool:  from finance, to editorial, to production, to IT, to product development, to product management, to marketing, to sales, to executive leadership, to customers.

• Enterprise class web analytics impacts the entire value chain.  

When you have deep integration needs and desire to join yr data mart with the data-warehouse and do real integration beyond simple summary extracts or Excel dumps, you need software that is interoperable, portable, and supports open software standards.  You need a system that feeds a real database like Oracle.  Then you can extend the goodness of web analytics data across the enterprise and even collect data at the edges of the enterprise to drive your value chain. 

When a corporation is dependent on web analytics data across the entire enterprise, you need control that software brings- over the data and over the system.  I also want an an open database that doesn’t have contention issues.  Somebody at one eMetrics told me “I don’t care about an open database” and “My IT department sucks.”  So software isn’t right for you.  Fine with me. 

• Buy what you need based on your requirements.

What real control do you have over a hosted model?  Calling support who will tell you after the report times out, “it’s a feature because we email the report to you in 30 minutes or less (or more).”  “But I need it now for a meeting in 10 minutes!”  ”Sorry, your query was too big.”  Huh?  Yeah, right, and so was the subscription cost. 

But “we have an SLA (service level agreement) and a T&C (terms and contract).”  So you think you have control because you signed a contract?

Who ya gonna call?  These guys:

What happens when some executive or engineering team totally and repeatedly ignores you when really need support?  Or the system goes crazy and you get no data, just error messages, with promises to fix at some time in the future?  It’s like a chapter out of Sartre.  Existential dread.  While people may have never lost their jobs for buying enterprise class software, I know people have lost their jobs from being forced to use the wrong delivery model. 

When $#1+ hits the fan, I’ll try to query the db myself, or I’ll call my wonderful team, and say hey “what’s up?”  I’d look at the artifacts of process, like a change management system.  Perhaps the DBA’s are doing fun stuff with partitioning.  I’ll call them too and ask “what’s up?”.  I’ll get the truth.  And verum factum, indeed.

Software is also a wonderful enabler for web analytics adoption and support in a business full of process.  It makes process even more optimal, and you the web analyst get to define that process.  The success (and risk for failure) is shared by everyone, up and down and across.  Web analytics is cool.  People want to do it.  The DBA’s want to use new technology.  The server team wants to virtualize.  The scripters want to write Perl to generate XML.  The analysts want the latest and greatest tool, whether created by Quahogers or Gamers.  Give the team what they want so they can be all they can be. So that’s what I’d want to give them through interoperable, portable web analytics software that supports open standards.

Eric brings up a very salient points.  Here’s one that I can’t emphasize and agree with enough: PROCESS.  P - R - O - C - E - S - S.  Live it.

Here’s a high-level process-based framework that works for software and hosted deployments:

1. Baseline - The software (or hosted) system up and running, out of the box, maybe with some light customization to feed your data warehouse.
2. Granular - Site specific meaningfulness, semantics, and metadata, and things like funnels, conversion points, and success events.  Maybe you build new metrics, add filters, and extend the data model.
3. Integrated - EAI across financial systems (like Oracle/Peoplesoft), ERP (like MS Great Plains),  and CRM (like SAP).

Avinash brings up a very salient point as well, which I can’t emphasize and agree with enough.  I quote “in the end people matter, tools don’t.”  P-E-O-P-L-E.  Believe it.

And Bill Gassman is right too: “a lot of enterprise class organizations don’t have the skills to operate an enterprise class Web analytics program.”  S-K-I-L-L-S.  Trust it.

Web analytics success comes from people who have skills and who employ process to use and extend tools.

Virtual Worlds and Web Analytics… Y’all ever play around with Second Life or World of Warcraft?  I have.  I think the concepts and worlds are very, very interesting and fun.  I find their messaging around the analytics of their user base even more entertaining though.  It’s like looking at ComScore and NNR for accurate web analytics data… really fascinating demographic stuff of questionable accuracy outside the frame of their audience panel and technology.  For example, I have three avatars, but have only downloaded one client. The trends are compelling though…

Some CMO’s I know won’t touch Second Life with a virtual ten foot, paisley, polygon pole.  Some finance folks I know laugh over beers about Linden Dollars.  Does that mean specific corporations become a central bank setting monetary policy subordinate to the central bank in the server’s home country?  How do International Fisher Relations apply when you have no interest rate?  My friends who have physical bodies say “virtual worlds are for when you have no friends in the real one.” Harsh criticisms, but they don’t negate the fact that something is happening and people are participating on some scale.  We’re all going to “do web analytics” on virtual worlds some day (maybe sooner than we think).

Where are the API’s for analytics data from these companies?  I believe Linden Labs announcing an analytics API would help push adoption by marketers forward and increase spend rates.  When I look at emerging technologies for 3D online collaboration, like OpenCroquet, I see the end of walled gardens like Second Life and WoW unless they open up the platform:

“Second Life doesn’t create a computational environment that belongs to its users - it uses a constrained computational environment (its servers) to capture “eyeballs” for a variety of schemes to derive revenue from them. With Croquet, users/developers may freely share, modify and view the source code (due to Croquet’s liberal license), the technology is not hosted on a single organization’s server (and hence governed by that organization as was the case with ViOS and now with Second Life), and it provides a complete professional programmer’s language (Smalltalk/Squeak), integrated development environment (IDE), and class library in every distributed, running participant’s copy (the programming development environment itself is simultaneously shareable and extensible). Croquet based worlds can also be updated while the system is live and running.”

Other online collaboration environments that would benefit from an open source of verifiable measurement include:

• Uni-verse.  An “open source Internet platform for multi-user, interactive, distributed, high-quality 3D graphics and audio for home, public and personal use.”
• Muse. A “software platform allowing organizations to create collaborative custom solutions that utilize rich media, 3D environments, and multi-user capabilities. Using Muse, developers can create immersive 3D environments that unite video and animation, audio, html, 3D models and much more.”
• Virtual Object System.  A “free and open platform for multiuser 3D virtual reality and interactive, collaborative 3D virtual spaces, and collaborative data systems in general.”

And the big guys and gals over at Microsoft and Sun are experimenting too (where’s Google and Yahoo? - do tell me!):

• Microsoft’s Task Gallery.  A “novel approach to bring existing, unmodified Windows applications into a running 3D virtual environment. The result is a working platform for experimentation in 3D user interfaces, in which the user retains all familiar productivity tools. This also allows for a smooth transition between traditional 2D interfaces and our new 3D territory.”
• Sun’s Looking Glass Project. A “Java technology and explores bringing a richer user experience to the desktop and applications via 3D windowing and visualization capabilities.”

Notice what all of these visionary ideas have in common: openness.  It’s only through open standards to key interfaces in these systems that we web analysts will be able to do what we do.  

So that beckons the rhetorical question, which web analytics tools right now could even work with extended data models for 3D virtual collaboration environments? 

I’m looking forward to how management at the following companies evolves their business models to focus on openness through analytics enabling their sustainable growth rate:

• There.com
• Multiverse
• Forterra Systems
• Whyville - ahh, my favorite question “why?”
• ProtonMedia
• Entropia Universe
• Habbo
• Areae

As Marshall Sponder forms the Web Analytics Association’s Social Media working group, I’m looking forward to hearing your voice on the phone calls.  Make sure you also read my good friend Eric Peterson’s take on some of this area as well.

On Sunday night May 6, the Web Analytics Association had their annual meeting.  Attended by about 100 hardcore members who trekked from all over the Earth to participate, we went over the business at hand.

Some of the highlights for me:

• Positive cash flow.  The WAA’s budget is looking strong.

• Solid executive management.  I spent some time with Bryan Induni and was impressed with his plans for the organization.  I also learned that in Idaho, if you like to hike in the woods (I do), it’s a good idea to bring a gun (to prevent cougar bites).

• Strong strategic leadership.  Directors Emeritus, best-selling author Bryan Eisenberg, and savvy WebTrends CEO, Greg Drew, were presented with honors for their significant contributions to the industry.  Jim Sternepresented them with “taking sticks” and a plaque commemorating their achievements.  In Native American culture, tribe leaders presented these foot-long intricately carved totems to individuals who wanted to address the tribe.  Since Jim didn’t take them back, and I saw the guys leave with them, that means they’re sticking around, if just a bit more “personamously!”

• Expanding education.  For those not familiar with the University of British Columbia’s Web Analytics award of achievement, check it out.  My friend and co-worker, Steve Mills, took the first course, and came back with stellar reviews.  Any wonder why he always asks me excellent, relevant questions at work?

Jim Novo, emperor of all things Direct Marketing and beyond, and Raquel Collins, analytics educator and master planner, have some forward-thinking plans for the UBC WA course.  We’re going to see partnerships with other institutions of higher learning and more significant credentialing of graduates.  

• International outreach.  We all live together on Earth.  The only things that make us different are language and location.  At the end of the day, the “smile” achieved from “getting it” is ubiquitous across humanity.  I’m glad to know such fine consultancies, such as OX2, and folks like Aurelie and Rene are doing smart and fantastic things across the pond with web analytics.

• Membership survey.  Check it out.  Audience questions showed we’re “wicked” geeks–New England slang for “awesome.”  My favorite: “Have we looked at how satisfaction levels across length of membership.”  Hear that WAA?  Let’s cross dimensions! Heh.

So the future is bright for the WAA.  If you aren’t a member, you are certainly missing out on what my Greg Drew said is, and I agree, “the most exciting time in your career!”

So join!  Membership has its rewards… and discounts… and hot tamales!

And, for regular readers, I’ll be back next week, once I return from VACAY, with an update all about EMetrics intertwined with some uniqueness of experience from my time out West.  Today, I’m off to Muir Woods…

My friend and a person whom I admire greatly has achieved the highest echelon of Maslow:

• Self-actualization - The fulfillment of the self through our efforts in developing our potential, the essence we are born with, and the acceptance of our limitations. Our life purpose unfolded, integrated into the self and lived.

Eric made the announcement at EMetrics after presenting very compelling research proving that a process-centric approach to web analytics yields:

• Quicker and clearer return on investment
• More satisfaction
• Increased value generation
• Higher salaries

Everyone in the industry is proud of Eric, for his graciousness, gentle nature, brilliant thought, and visionary leadership in helping drive the industry forward. 

The cosmos is the limit!  Go, go, go Eric!

New York City is always amazing, even if it’s full of Yankees fans (go Red Sox!). Pitching always beats hitting, btw. And I’m looking forward to my Green Monster seats versus the Tigers the Monday after Emetrics.

NYC Gotham is just so full of diversity, life, and energy, I just can’t help staying out really late and soaking it all in. Where else can you see a public installation of an Alexander Calder mobile and then walk down the street to check out a Hans Hoffman mural? Did your know the New York Public Library has the original manuscript for T.S. Eliot’s The Wasteland? And they let your look at it (if you are persistent and just keep asking for years). The original title, before Ezra Poundcrafted it, was “We do the police in different voices.” Ahhh, that helps understanding, ay?

So I was in and out of the world’s Great Metropolis for a whirlwind evening and day, thanks to an invitation to speak with the smart folks at ClickZ and Incisive Media.

Rebecca Lieb, EIC at ClickZ, impaneled me with the master of monetization, Jason Burby, and the savvy applier of insights, Neil Mason, to present on “Non-Transactional Analytics.” Y’know the kind when you don’t really sell stuff, and instead produce content and/or sites that are informational and navigational.

Neil riffed on context and the strategic approach to non-transactional analytics. Jason riffed on what I’ll call “monetization modeling.” Both had some brilliant thoughts and imparted actionable knowledge to an audience hungry for knowledge about metrics. I’m certainly looking forward to Jason’s forthcoming book, and reading Neil’s next column.

Me? We’ll I was nicely sandwiched in the middle, and presented a tactical, seven-phase methodology for “non-transactional analytics.” The process has measurement endemic throughout and is iterative and recursive (self-referential). Here it is:

• Phase 1: Identify
• Phase 2: Discover
• Phase 3: Understand
• Phase 4: Segment
• Phase 5: Create/Optimize
• Phase 6: Test
• Phase 7: Validate

In Phase 1, the analyst identifies:

• Internet ecosystem
• Tools
• Processes impacted
• Goals:
  • As I like to say “a metric/KPI has meaning in position and relation to a goal (the signified).”
• Revenue and contribution
• Impact on value chain

In Phase 2: Discover, the analyst discovers:

• Metrics
• KPI’s
• Clickstream data
• Event pathing
• Data model
• Data structures
• What the street has to say about your site(s)!

In Phase 3: Understand, the analyst reconciles:

• Origin of the traffic
• Sequences of events that generate value
• On-site success events
• Visitor population and how it responds to:
  • Recency – how recent is the content for the site’s audience?
  • Frequency – how frequent are visitors visiting?
  • Monetary– what’s the monetization impact? Jason Burby will know.
  • Engagement – I refer to my esteemed friend, Eric Peterson.
  • Attention – Stephane Hamel has some excellent thoughts on Davenport’s Attention economy.
  • Currency – How current is the content to your audience?
  • Relevancy – How relevant is the content to your audience?

In Phase 4: Segment, the analyst segments by:

• Behavior
• Demographics
• Referrers
• Time-based metrics
• Event orientation
• Psychographics
• Topographics

In Phase 5: Create/Optimize, the analyst should work with his geeks and other gurus to create and optimize:

• New dimensions
• Groupings
• Filters
• Content types
• Audience development strategies
• Metadata
• Self-describing naming conventions

In Phase 6: Test, you guessed it, the analyst tests using:

• The usual suspects:
  • Multivariate testing
  • AB
  • Split
• The unusual suspects
  • Binomial Distributions
  • Regression Analysis/ANOVA
  • Predictive Analytics(Bayesian, Neural Networks, ARIMA)

In Phase 7: Validate, the analyst watches the numbers:

• Key metrics from your data collection methods
• Surveying (in context)
• Audience panel data (in context)
• Backtesting:
  • Comparative reporting
  • AB reporting
• Counting the money

Then, you just keep on rinsing, lathering, and repeating across your business processes:

• Identifying goals
• Discovering new data/ideas
• Understanding online behavior
• Segmenting the data
• Creating new content and/or optimizing the delivery of existing content
• Testing hypotheses
• Validating your strategies to your goals

So there it is a simple model for “doing web analytics” for non-transactional sites.

Thanks for visiting! Please come again!