Web Analytics Demystified
COMPETING ON WEB ANALYTICS

Introduction
• Founder, Web Analytics Demystified, Inc.
• Author of three books:
– Web Analytics Demystified
– Web Site Measurement Hacks
– Big Book of Key Performance Indicators
• Focused on measurement process, organizational
structure, and overall digital analytics strategy
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@ericTpeterson
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@ericpeterson
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Web Analytics Demystified
COMPETING ON WEB ANALYTICS

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“Businesses can create
sustainable and strategic
competitive advantages by
investing in analytics.”
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What is Analytics?
“By analytics we mean the extensive use of data,
statistical and quantitative analysis, explanatory and
predictive models, and fact-based management to
drive decisions and actions…analytics are part of
what has come to be called business intelligence: a
set of technologies and processes that use data
to understand and analyze business
performance.”
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What is Analytics?
“By analytics we mean the extensive use of data,
statistical and quantitative analysis, explanatory and
predictive models, and fact-based management to
drive decisions and actions…analytics are part of
what has come to be called business intelligence: a
set of technologies and processes that use data
to understand and analyze business
performance.”
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Key Ideas
• Depends on operational interpretation and
visualization, not data collection and reporting
• Managed globally for all processes and functions,
not departmentally or in silos
• Requires continual monitoring and response
based on observed changes, not episodic changes
and re-engineering
• Powered by people and process, not just
technology
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Key Ideas
• Depends on operational interpretation and
visualization, not data collection and reporting
• Managed globally for all processes and functions,
not departmentally or in silos
• Requires continual monitoring and response
based on observed changes, not episodic changes
and re-engineering
• Powered by people and process, not just
technology
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The Big Problem?
• It is very easy to
profess a great love
for data …
• … and still fail to
use that data to
inform action!
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Consider Starting Small …
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^
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“Businesses can create
sustainable and strategic
competitive advantages by
investing in analytics.”
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“Businesses can create
sustainable and strategic
competitive advantages
online by investing in web
analytics.”
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“Businesses can create
sustainable and strategic
competitive advantages
online by investing in web
analytics.”
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The Same Key Ideas
• Depends on operational interpretation and
visualization, not data collection and reporting
• Managed globally for all processes and functions,
not departmentally or in silos
• Requires continual monitoring and response
based on observed changes, not episodic changes
and re-engineering
• Powered by people and process, not just
technology
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The Big Problem
Overly complex and expensive segmentation tools Expensive software
Web analytics and audience research solutions give different numbers
No real web analytics community association Data integration nightmares
No standard definitions of engagement and influence
No information about visitor and customer intent Crummy data export tools
No standard qualitative inputs Poorly defined key performance indicators
Poorly defined processes for using web analytics Lousy vendor documentation
Smarmy web analytics sales people Not enough great books on web analytics
Crappy implementations Too few relevant case studies
No data about statistical relevance Software is too complex
Too many reports, not enough information Expensive consultants
No help from Information Technology (I.T.)
No real tools for modeling and predictive analytics Few formal web analytics training courses
No standard definitions in the industry
Too many HiPPOs
Contradictory explanations of what the data means
Too few people who understand web analytics
Cookie deletion, cookie blocking, and cookie‐less mobile browsers
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The Real Problem
Overly complex and expensive segmentation tools Expensive software
Web analytics and audience research solutions give different numbers
No real web analytics community association Data integration nightmares
No standard definitions of engagement and influence
No information about visitor and customer intent Crummy data export tools
No standard qualitative inputs Poorly defined key performance indicators
Poorly defined processes for using web analytics Lousy vendor documentation
WEB ANALYTICS IS HARD
Smarmy web analytics sales people Not enough great books on web analytics
Crappy implementations Too few relevant case studies
No data about statistical relevance Software is too complex
Too many reports, not enough information Expensive consultants
No help from Information Technology (I.T.)
No real tools for modeling and predictive analytics Few formal web analytics training courses
No standard definitions in the industry
Too many HiPPOs
Contradictory explanations of what the data means
Too few people who understand web analytics
Cookie deletion, cookie blocking, and cookie‐less mobile browsers
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The Real Problem
Overly complex and expensive segmentation tools Expensive software
Web analytics and audience research solutions give different numbers
No real web analytics community association Data integration nightmares
No standard definitions of engagement and influence
No information about visitor and customer intent Crummy data export tools
No standard qualitative inputs Poorly defined key performance indicators
Poorly defined processes for using web analytics Lousy vendor documentation
WEB ANALYTICS IS HARD
Smarmy web analytics sales people Not enough great books on web analytics
Crappy implementations Too few relevant case studies
No data about statistical relevance Software is too complex
Too many reports, not enough information Expensive consultants
No help from Information Technology (I.T.)
No real tools for modeling and predictive analytics Few formal web analytics training courses
No standard definitions in the industry
Too many HiPPOs
Contradictory explanations of what the data means
Too few people who understand web analytics
Cookie deletion, cookie blocking, and cookie‐less mobile browsers
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There is a Solution!
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How to Compete on Web Analytics
1. Architect Your Web Analytics Technology
2. Manage Your Web Analytics Talent
3. Focus Your Analytical Efforts
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How to Compete on Web Analytics
1. Architect Your Web Analytics Technology
2. Manage Your Web Analytics Talent
3. Focus Your Analytical Efforts
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Architect Your Technology
• Web analytics absolutely depends on technology
• You can put too much emphasis on software
• Key challenges:
– Right data
– Right systems
– Right output
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What is the Right Data?
• The “right” data
Visitor
comes from
Voice of
Customer
multiple systems
Scope of Insight Session
• Integration of Integrated View of Visitor Behavior
these systems is
the new Web
Analytics
opportunity Customer
Experience
Management
Quantitative Type of Data Qualitative
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What Are the Right Systems?
Visitor
Scope of Insight Session
Integrated View of Visitor Behavior
Quantitative Type of Data Qualitative
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What is the Right Output?
Analytics
Decision Optimization What’s the best that can happen?
Competitive Advantage
Predictive Analytics What will happen next?
Forecasting What if these trends continue?
Statistical models Why is this happening?
Alerts What actions are needed?
Query/drill down Where exactly is the problem?
Ad hoc reports How many, how often, where?
Standard reports What happened?
Reporting
Degree of Intelligence
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Unfortunately …
Analytics
Decision Optimization What’s the best that can happen?
Competitive Advantage
Predictive Analytics What will happen next?
Forecasting What if these trends continue?
Statistical models Why is this happening?
Alerts What actions are needed?
Query/drill down Where exactly is the problem?
Ad hoc reports How many, how often, where?
Standard reports What happened?
Reporting
Degree of Intelligence
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How Are You Doing with Technology?
• Four signs of the “right” technology:
1. Nobody says “if only we had Solution X”
2. Nobody questions the money you’re spending
3. Nobody uses Excel because they have to
4. Nobody is forced to whine on Twitter for help!
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How Are You Doing with Technology?
• Four signs of the “right” technology:
1. Nobody says “if only we had Solution X”
2. Nobody questions the money you’re spending
3. Nobody uses Excel because they have to
4. Nobody is forced to whine on Twitter for help!
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Architect Your Technology
Visitor
Scope of Insight Session
Integrated View of Visitor Behavior
Quantitative Type of Data Qualitative
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How to Compete on Web Analytics
1. Architect Your Web Analytics Technology
2. Manage Your Web Analytics Talent
3. Focus Your Analytical Efforts
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Manage Your Talent
• People are critical to analytics
• But analysts alone cannot get the job done
• Analytics is a team effort
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Analytical Executives
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Analytics Amateurs
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Analytical Professionals
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The Description Has Not Changed
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How Much Should You Spend?
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The 50/50 Rule for Analytics Investment
• For every dollar you invest in technology
• Spend one dollar for dedicated resources
– Using free tools? Estimate costs
– Hiring freeze? Consider consultants
– No budget? You get what you pay for
• This is how the analytical
competitors are getting it done
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The Analytical Organization
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How Are You Doing With Staffing?
• Five signs of the “right” staffing model:
1. You have a senior person who “owns” analytics
2. You have dedicated resources for web analytics
3. You know who your “analytics amateurs” are
4. Your analytics hub supports the whole company
5. Your analytics hub produces insights and
recommendations, not just reports
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Manage Your Analytical Talent
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How to Compete on Web Analytics
1. Architect Your Web Analytics Technology
2. Manage Your Web Analytics Talent
3. Focus Your Analytical Efforts
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Focus Your Analytical Efforts
• Fewer than one-in-five companies have a
company-wide strategy for web analytics *
• Lacking strategy, chaos reigns
• Developing a strategy requires understanding the
Hierarchy of Analytical Needs
* Econsultancy 2008 51

The Hierarchy of Analytical Needs
Recommendations
Insights
Information
Data
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What Most Companies Get Today …
Recommendations
Insights
Information
Data
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What Companies Really Need
Recommendations
Insights
Information
Data
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What Management Really Wants!
Recommendations
Insights
Information
Data
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Recommendations Require Maturity
Stage 0 Stage 1 Stage 2 Stage 3 Stage 4
Relative Number of
Staffing Chasm
Companies
Investment
Chasm Process Chasm
Maturity of Analytics Use Source: JupiterResearch (8/05)
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Cross the “Process” Chasm!
• To provide insights and
recommendations you
must first define
analytics processes
• There is simply no way
around this
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Focus on Internal Analytics Process
• Ask yourself?
– Does the business understand what you do?
– Do you present data or generate recommendations?
– Do you have clearly defined workflow?
– Do you have a governance model?
– Do you know where our internal
processes break-down?
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How to “Kick-Butt” with Analytics
• Six hallmarks of “Analytical Champions”:
1. Clearly defined analytics governance model
2. Appropriate technology investment
3. Appropriate resource allocation
4. Intense process-awareness
5. Ability to generate recommendations
6. Ability to measure impact of
recommended actions taken
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Focus Your Analytical Efforts
Recommendations
Insights
Information
Data
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At the End of the Day it Takes …
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People …
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Process …
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… and Technology
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… in Roughly Equal Measures
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Success is Awesome!
• “Our success is split evenly between building
authentic brands and using analytics to leverage
and innovate pull demand marketing online.”
– Dustin Robertson, CMO
Backcountry.com
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“If it’s worth doing, it’s worth
doing analytically.”
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“If it’s worth doing, it’s worth
doing web analytically.”
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Want to Know More?
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Eric T. Peterson
eric.peterson@webanalyticsdemystified.com
www.webanalyticsdemystified.com
Twitter: @erictpeterson
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