A V I N A S H K A U S H I KKAUSHIK

SERIOUS SKILLS.

Web Analytics 2.0

Shift to Data-Driven Decision Making and Leverage the Complete Power of All Web Data

Web A

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& SCIENCE OF CUSTOMER CENTRICITY[ ]TH

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INSIDEYour Google AdWords™ Gift Card Worth $25

The Web, online marketing, and advertising have been revolutionized in the last few years, yet the approach to using data has remained largely the same as a decade ago. Web analytics thought leader Avinash Kaushik presents the next-generation framework of web analytics in this exciting book that will dramatically enhance the ability of your organization to think smart and move fast.

In this book, Avinash lays out specifi c strategies and execution models to evolve from simply lever-aging clickstream tools to incorporating the insightful elixir of qualitative data, experimentation and testing, and competitive intelligence tools.

While expanding upon the industry-shaping lessons from his bestselling book Web Analytics: An Hour a Day, Avinash explains how to measure, analyze, and act upon today’s quickly evolving web technologies and trends—including social media, video, mobile, and online user-centric design options. As he updates traditional approaches, Avinash debunks myths, identifi es traps, and reveals specifi c, simple and advanced methodologies to transform your thinking, making this book the ultimate guide for all web professionals.

Avinash Kaushik is the author of the leading research & analytics blog Occam’s Razor. He is also the Analytics Evangelist for Google and the Chief Education Offi cer at Market Motive, Inc. He is a bestselling author and a frequent speaker at key industry conferences around the globe and at leading American universities. He was the recipient of the 2009 Statistical Advocate of the Year award from the American Statistical Association.

The author donates all proceeds from his books to two charities, The Smile Train and The Ekal Vidyalaya Foundation.

www.sybex.comwww.webanalytics20.comCOMPUTERS/Internet/ecommerce

$39.99 US$47.99 CAN

• Discover the solutions for the hardest challenges, including multichannel analytics and multitouch campaign attribution analysis

• Quantify the holistic economic value of your website and measure macro and micro conversions for ecommerce, non-ecommerce, and B2B websites

• Profi t from analytical methodologies that attack the holy trinity of search: internal site search, pay-per-click marketing, and search engine optimization

• Pinpoint the most relevant Key Performance Indicators for your organization and create actionable dashboards that drive change

• Master crucial emerging analytics fi elds including Twitter®, YouTube®, blogs, mobile, and rich-media analytics

• Leverage experimentation and testing to create truly customer-centric websites and innovate by failing faster

• Create data-driven bosses and organizations, and cultivate the skills and background you need for a successful analytics career

• Continue learning with four hours of video, an hour of audio, and valuable presentations, templates, and models on the CD

ISBN 978-0-470-52939-3

“Analytics is vitally important, and no one explains it more elegantly, more simply, or more powerfully than Avinash Kaushik. Consider buying up all the copies of this book before your competition gets a copy.”—Seth Godin, author, Tribes

“Lots of companies have spent lots of time and money collectingdata—and sadly do little with it. In Web Analytics 2.0, Avinash Kaushik helps us grasp the importance ofthis underused resource and shows us how to make the most of on-line data and experimentation.”—Dan Ariely, Professor of Behavioral Economics, Duke University, and author of Predictably Irrational

“Kaushik takes the witchcraft out of analytics. If venture capitalists read this book, they would fi re half of the CEOs that they’ve funded.”—Guy Kawasaki, Co-founder of Alltop & Garage Technology Ventures

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Praise for Web Analytics 2.0

When it comes to the digital marketing channels and understanding what and why people do things online, there is no one smarter than Avinash Kaushik. His first book, Web Analytics: An Hour a Day, should be on every marketer’s desk. Now, with Web Analytics 2.0, there’s a wor-thy accompaniment. When people ask, ‘Who is the smartest guy in the room when it comes to online marketing?’ only one name comes to mind: Avinash. I’d tell you to buy this book, but I would prefer if you didn’t. I’d love to keep these concepts and theories all to myself and my cli-ents. Yes, it’s that powerful, awesome, and actionable.

—Mitch Joel, president of Twist Image and author of Six Pixels of Separation

Analytics is vitally important, and no one (no one) explains it more elegantly, more simply, or more power fully than Avinash Kaushik. Consider buying up all the copies of this book before your competition gets a copy.

—Seth Godin, author, Tribes

Lots of companies have spent lots of time and money collecting data—and sadly do little with it. In Web Analytics 2.0, Avinash Kaushik helps us grasp the importance of this underused resource and shows us how to make the most of online data and experimentation.

— Dan Ariely, professor of Behavioral Economics, Duke University and author of Predictably Irrational

Kaushik takes the witchcraft out of analytics. If venture capitalists read this book, they would fire half of the CEOs that they’ve funded.

—Guy Kawasaki, co-founder of Alltop & Garage Technology Ventures

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Web Analytics 2.0

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Web Analytics 2.0The Art of Online Accountability & Science of Customer CentricityA v i n a s h K a u s h i k

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Senior Acquisitions Editor: Willem Knibbe

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Dear Reader,Thank you for choosing Web Analytics 2.0: The Art of Online Accountability &

Science of Customer Centricity. This book is part of a family of premium-quality Sybex books, all of which are written by outstanding authors who combine practical experience with a gift for teaching.

Sybex was founded in 1976. More than 30 years later, we’re still committed to producing consistently exceptional books. With each of our titles we’re working hard to set a new standard for the industry. From the paper we print on to the authors we work with, our goal is to bring you the best books available.

I hope you see all that reflected in these pages. I’d be very interested to hear your com-ments and get your feedback on how we’re doing. Feel free to let me know what you think about this or any other Sybex book by sending me an email at nedde@wiley.com, or if you think you’ve found a technical error in this book, please visit http://sybex.custhelp.com. Customer feedback is critical to our efforts at Sybex.

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Neil EddeVice President and PublisherSybex, an Imprint of Wiley

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AcknowledgmentsWere it not for the love, patience, and support of my family, it would be impossible to write this book and hold down a few full-time jobs, advise three companies, write a blog, and travel the world evangelizing the awesomeness of data. I’m lucky. My wife Jennie is my biggest cheerleader and counsel, and for that I shall remain in debt to her for several lifetimes. My daughter Damini’s courage and kindness is a constant source of inspiration. My son Chirag’s intellect and energy reminds me to always be curious and strive for more.

I would like to express my deep appreciation to the readers of my blog, Occam’s Razor. In approximately three and a half years I have written 411,725 words in my 204 blog posts, and the readers of my blog have written 615,192 words in comments! Their engagement means the world to me and motivates me to make each blog post better than the last. It is impossible to thank each person, so on their behalf let me thank three: Ned Kumar, Rick Curtis, and Joe Teixeira.

As the song goes, I get by with a little help from my friends… in the last few years I have benefited from the help of two dear friends in particular. Bryan Eisenberg, the author of Always Be Testing, has consistently shared life lessons about this business and helped a ton with my own journey. Mitch Joel, the author of Six Pixels of Separation, has helped me become a better public speaker and, as if that were not enough, connected me with anyone worth connecting to! Thanks, guys.

A huge motivation behind this book was the incredible work done by The Smile Train, Doctors Without Borders, and Ekal Vidyalaya. They make the world a better place, and I feel blessed that the money raised by my books helps me be a small part of their mission.

Last, but not least, my fantastic team at Wiley. This book was written and published at a pace that would drive mere mortals crazy, but not them. They worked harder than I did, they pushed deadlines (and me!), and they made the impossible hap-pen. Stephanie Barton, Kim Wimpsett, Liz Britten, and Willem Knibbe, you rock!

To the wind beneath my wings, my inimitable wife Jennie.

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About the AuthorAvinash Kaushik is author of the best-selling book Web Analytics: An Hour a Day (http://www.snipurl.com/wahour). He is also the analytics evangelist for Google and the cofounder of Market Motive, Inc.

As a thought leader, Avinash puts a commonsense framework around the often frenetic world of web analyt-ics and combines that framework with the philosophy that investing in talented analysts is the key to long-term success. He is also a staunch advocate of listening to the consumer and is committed to helping organizations unlock the value of web data.

Avinash works with some of the largest companies in the world to help them evolve their online marketing and analytics strategies to become data-driven and customer-

centric organizations. He recently received the 2009 Statistical Advocate of the Year award from the American Statistical Association.

He is also a frequent speaker at industry conferences in the United States and Europe, such as Ad-Tech, Monaco Media Forum, iCitizen, and JMP Innovators’ Summit, as well as at major universities, such as Stanford University, University of Virginia, and University of Utah.

You’ll find Avinash’s web analytics blog, Occam’s Razor, at www.kaushik.net/avinash.

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ContentsIntroduction xxi

Chapter 1 The Bold New World of Web Analytics 2.0 1

State of the Analytics Union . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

State of the Industry . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Rethinking Web Analytics: Meet Web Analytics 2 .0 . . . . . . . . . . . . . . 4The What: Clickstream 7The How Much: Multiple Outcomes Analysis 7The Why: Experimentation and Testing 8The Why: Voice of Customer 9The What Else: Competitive Intelligence 9

Change: Yes We Can! . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10The Strategic Imperative 10The Tactical Shift 11Bonus Analytics 13

Chapter 2 The Optimal Strategy for Choosing Your Web Analytics Soul Mate 15

Predetermining Your Future Success . . . . . . . . . . . . . . . . . . . . . . . . . . 16

Step 1: Three Critical Questions to Ask Yourself Before You Seek an Analytics Soul Mate! . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17Q1: “Do I want reporting or analysis?” 17Q2: “Do I have IT strength, business strength, or both?” 19Q3: “Am I solving just for Clickstream or for Web Analytics 2 .0?” 20

Step 2: Ten Questions to Ask Vendors Before You Marry Them . . . . . 21Q1: “What is the difference between your tool/solution and free tools from Yahoo! and Google?” 21Q2: “Are you 100 percent ASP, or do you offer a software version? Are you planning a software version?” 22Q3: “What data capture mechanisms do you use?” 22Q4: “Can you calculate the total cost of ownership for your tool?” 23Q5: “What kind of support do you offer? What do you include for free, and what costs more? Is it free 24/7?” 24Q6: “What features in your tool allow me to segment the data?” 25Q7: “What options do I have for exporting data from your system into our company’s system?” 25Q8: “What features do you provide for me to integrate data from other sources into your tool?” 26Q9: “Can you name two new features/tools/acquisitions your company is cooking up to stay ahead of your competition for the next three years?” 26Q10: “Why did the last two clients you lost cancel their contracts? Who are they using now? May we call one of these former clients?” 27

Comparing Web Analytics Vendors: Diversify and Conquer . . . . . . . . 28The Three-Bucket Strategy 28

Step 3: Identifying Your Web Analytics Soul Mate (How to Run an Effective Tool Pilot) . . . . . . . . . . . . . . . . . . . . . . . . . 29

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Step 4: Negotiating the Prenuptials: Check SLAs for Your

Web Analytics Vendor Contract . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 32

Chapter 3 The Awesome World of Clickstream Analysis: Metrics 35

Standard Metrics Revisited: Eight Critical Web Metrics . . . . . . . . . . . 36Visits and Visitors 37Time on Page and Time on Site 44

Bounce Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 51

Exit Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 53

Conversion Rate . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 55

Engagement . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 56

Web Metrics Demystified . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 59Four Attributes of Great Metrics 59Example of a Great Web Metric 62Three Avinash Life Lessons for Massive Success 62

Strategically-aligned Tactics for Impactful Web Metrics . . . . . . . . . . . 64Diagnosing the Root Cause of a Metric’s Performance—Conversion 64Leveraging Custom Reporting 66Starting with Macro Insights 70

Chapter 4 The Awesome World of Clickstream Analysis: Practical Solutions 75

A Web Analytics Primer . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 76Getting Primitive Indicators Out of the Way 76Understanding Visitor Acquisition Strengths 78Fixing Stuff and Saving Money 79Click Density Analysis 81Measuring Visits to Purchase 83

The Best Web Analytics Report . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85Sources of Traffic 86Outcomes 87

Foundational Analytical Strategies . . . . . . . . . . . . . . . . . . . . . . . . . . . 87Segment or Go Home 88Focus on Customer Behavior, Not Aggregates 93

Everyday Clickstream Analyses Made Actionable . . . . . . . . . . . . . . . . 94Internal Site Search Analysis 95Search Engine Optimization (SEO) Analysis 101Pay Per Click/Paid Search Analysis 110Direct Traffic Analysis 116Email Campaign Analysis 119Rich Experience Analysis: Flash, Video, and Widgets 122

Reality Check: Perspectives on Key Web Analytics Challenges . . . . . 126Visitor Tracking Cookies 126Data Sampling 411 130The Value of Historical Data 133

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The Usefulness of Video Playback of Customer Experience 136The Ultimate Data Reconciliation Checklist 138

Chapter 5 The Key to Glory: Measuring Success 145

Focus on the “Critical Few” . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 147

Five Examples of Actionable Outcome KPIs . . . . . . . . . . . . . . . . . . . 149Task Completion Rate 149Share of Search 150Visitor Loyalty and Recency 150RSS/Feed Subscribers 150% of Valuable Exits 151

Moving Beyond Conversion Rates . . . . . . . . . . . . . . . . . . . . . . . . . . . 151Cart and Checkout Abandonment 152Days and Visits to Purchase 153Average Order Value 153Primary Purpose (Identify the Convertible) 154

Measuring Macro and Micro Conversions . . . . . . . . . . . . . . . . . . . . 156Examples of Macro and Micro Conversions 158

Quantifying Economic Value . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 159

Measuring Success for a Non-ecommerce Website . . . . . . . . . . . . . . 162Visitor Loyalty 162Visitor Recency 164Length of Visit 165Depth of Visit 165

Measuring B2B Websites . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 166

Chapter 6 Solving the “Why” Puzzle: Leveraging Qualitative Data 169

Lab Usability Studies: What, Why, and How Much? . . . . . . . . . . . . 170What Is Lab Usability? 170How to Conduct a Test 171Best Practices for Lab Usability Studies 174Benefits of Lab Usability Studies 174Areas of Caution 174

Usability Alternatives: Remote and Online Outsourced . . . . . . . . . . 175Live Recruiting and Remote User Research 176

Surveys: Truly Scalable Listening . . . . . . . . . . . . . . . . . . . . . . . . . . . 179Types of Surveys 180The Single Biggest Surveying Mistake 184Three Greatest Survey Questions Ever 185Eight Tips for Choosing an Online Survey Provider 187

Web-Enabled Emerging User Research Options . . . . . . . . . . . . . . . . 190Competitive Benchmarking Studies 190Rapid Usability Tests 191Online Card-Sorting Studies 191Artificially Intelligent Visual Heat Maps 192

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Chapter 7 Failing Faster: Unleashing the Power of Testing and Experimentation 195

A Primer on Testing Options: A/B and MVT . . . . . . . . . . . . . . . . . . 197A/B Testing 197Multivariate Testing 198

Actionable Testing Ideas . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 202Fix the Big Losers—Landing Pages 202Focus on Checkout, Registration, and Lead Submission Pages 202Optimize the Number and Layout of Ads 203Test Different Prices and Selling Tactics 203Test Box Layouts, DVD Covers, and Offline Stuff 204Optimize Your Outbound Marketing Efforts 204

Controlled Experiments: Step Up Your Analytics Game! . . . . . . . . . 205Measuring Paid Search Impact on Brand Keywords and Cannibalization 205Examples of Controlled Experiments 207Challenges and Benefits 208

Creating and Nurturing a Testing Culture . . . . . . . . . . . . . . . . . . . . 209Tip 1: Your First Test is “Do or Die” 209Tip 2: Don’t Get Caught in the Tool/Consultant Hype 209Tip 3: “Open the Kimono”—Get Over Yourself 210Tip 4: Start with a Hypothesis 210Tip 5: Make Goals Evaluation Criteria and Up-Front Decisions 210Tip 6: Test For and Measure Multiple Outcomes 211Tip 7: Source Your Tests in Customer Pain 211Tip 8: Analyze Data and Communicate Learnings 212Tip 9: Two Must-Haves: Evangelism and Expertise 212

Chapter 8 Competitive Intelligence Analysis 213

CI Data Sources, Types, and Secrets . . . . . . . . . . . . . . . . . . . . . . . . . 214Toolbar Data 215Panel Data 216ISP (Network) Data 217Search Engine Data 217Benchmarks from Web Analytics Vendors 218Self-reported Data 219Hybrid Data 220

Website Traffic Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 221Comparing Long-Term Traffic Trends 222Analyzing Competitive Sites Overlap and Opportunities 223Analyzing Referrals and Destinations 224

Search and Keyword Analysis . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 225Top Keywords Performance Trend 226Geographic Interest and Opportunity Analysis 227Related and Fast-Rising Searches 230Share-of-Shelf Analysis 231Competitive Keyword Advantage Analysis 233Keyword Expansion Analysis 234

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Audience Identification and Segmentation Analysis . . . . . . . . . . . . . 235Demographic Segmentation Analysis 236Psychographic Segmentation Analysis 238Search Behavior and Audience Segmentation Analysis 239

Chapter 9 Emerging Analytics: Social, Mobile, and Video 241

Measuring the New Social Web: The Data Challenge . . . . . . . . . . . . 242The Content Democracy Evolution 243The Twitter Revolution 247

Analyzing Offline Customer Experiences (Applications) . . . . . . . . . . 248

Analyzing Mobile Customer Experiences . . . . . . . . . . . . . . . . . . . . . 250Mobile Data Collection: Options 250Mobile Reporting and Analysis 253

Measuring the Success of Blogs . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 257Raw Author Contribution 257Holistic Audience Growth 258Citations and Ripple Index 262Cost of Blogging 263Benefit (ROI) from Blogging 263

Quantifying the Impact of Twitter . . . . . . . . . . . . . . . . . . . . . . . . . . 266Growth in Number of Followers 266Message Amplification 267Click-Through Rates and Conversions 268Conversation Rate 270Emerging Twitter Metrics 271

Analyzing Performance of Videos . . . . . . . . . . . . . . . . . . . . . . . . . . . 273Data Collection for Videos 273Key Video Metrics and Analysis 274Advanced Video Analysis 278

Chapter 10 Optimal Solutions for Hidden Web Analytics Traps 283

Accuracy or Precision? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 284

A Six-Step Process for Dealing with Data Quality . . . . . . . . . . . . . . 286

Building the Action Dashboard . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 288Creating Awesome Dashboards 288The Consolidated Dashboard 290Five Rules for High-Impact Dashboards 291

Nonline Marketing Opportunity and Multichannel Measurement . . 294Shifting to the Nonline Marketing Model 294Multichannel Analytics 296

The Promise and Challenge of Behavior Targeting . . . . . . . . . . . . . . 298The Promise of Behavior Targeting 299Overcoming Fundamental Analytics Challenges 299Two Prerequisites for Behavior Targeting 301

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Online Data Mining and Predictive Analytics: Challenges . . . . . . . . 302Type of Data 303Number of Variables 304Multiple Primary Purposes 304Multiple Visit Behaviors 305Missing Primary Keys and Data Sets 305

Path to Nirvana: Steps Toward Intelligent Analytics Evolution . . . . . 306Step 1: Tag, Baby, Tag! 307Step 2: Configuring Web Analytics Tool Settings 308Step 3: Campaign/Acquisition Tracking 309Step 4: Revenue and Uber-intelligence 310Step 5: Rich-Media Tracking (Flash, Widgets, Video) 311

Chapter 11 Guiding Principles for Becoming an Analysis Ninja 313

Context Is Queen . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 314Comparing Key Metrics Performance for Different Time Periods 314Providing Context Through Segmenting 315Comparing Key Metrics and Segments Against Site Average 316Joining PALM (People Against Lonely Metrics) 318Leveraging Industry Benchmarks and Competitive Data 319Tapping into Tribal Knowledge 320

Comparing KPI Trends Over Time . . . . . . . . . . . . . . . . . . . . . . . . . . 321Presenting Tribal Knowledge 322Segmenting to the Rescue! 323

Beyond the Top 10: What’s Changed . . . . . . . . . . . . . . . . . . . . . . . . . 324

True Value: Measuring Latent Conversions and Visitor Behavior . . . 327Latent Visitor Behavior 327Latent Conversions 329

Four Inactionable KPI Measurement Techniques . . . . . . . . . . . . . . . 330Averages 330Percentages 332Ratios 334Compound or Calculated Metrics 336

Search: Achieving the Optimal Long-Tail Strategy . . . . . . . . . . . . . . 338Compute Your Head and Tail 339Understanding Your Brand and Category Terms 341The Optimal Search Marketing Strategy 342Executing the Optimal Long-Tail Strategy 344

Search: Measuring the Value of Upper Funnel Keywords . . . . . . . . . 346

Search: Advanced Pay-per-Click Analyses . . . . . . . . . . . . . . . . . . . . . 348Identifying Keyword Arbitrage Opportunities 349Focusing on “What’s Changed” 350Analyzing Visual Impression Share and Lost Revenue 351Embracing the ROI Distribution Report 353Zeroing In on the User Search Query and Match Types 354

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Chapter 12 Advanced Principles for Becoming an Analysis Ninja 357

Multitouch Campaign Attribution Analysis . . . . . . . . . . . . . . . . . . . 358What Is All This Multitouch? 358Do You Have an Attribution Problem? 359Attribution Models 361Core Challenge with Attribution Analysis in the Real World 364Promising Alternatives to Attribution Analysis 365Parting Thoughts About Multitouch 368

Multichannel Analytics: Measurement Tips for a Nonline World . . . 368Tracking Online Impact of Offline Campaigns 369Tracking the Offline Impact of Online Campaigns 376

Chapter 13 The Web Analytics Career 385Planning a Web Analytics Career: Options, Salary Prospects, and Growth . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 386Technical Individual Contributor 388Business Individual Contributor 388Technical Team Leader 390Business Team Leader 391

Cultivating Skills for a Successful Career in Web Analysis . . . . . . . . 393Do It: Use the Data 393Get Experience with Multiple Tools 393Play in the Real World 394Become a Data Capture Detective 396Rock Math: Learn Basic Statistics 396Ask Good Questions 397Work Closely with Business Teams 398Learn Effective Data Visualization and Presentation 398Stay Current: Attend Free Webinars 399Stay Current: Read Blogs 400

An Optimal Day in the Life of an Analysis Ninja . . . . . . . . . . . . . . . 401

Hiring the Best: Advice for Analytics Managers and Directors . . . . . 403Key Attributes of Great Analytics Professionals 404Experienced or Novice: Making the Right Choice 405The Single Greatest Test in an Interview: Critical Thinking 405

Chapter 14 HiPPOs, Ninjas, and the Masses: Creating a Data-Driven Culture 407

Transforming Company Culture: How to Excite

People About Analytics . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 408Do Something Surprising: Don’t Puke Data 409

Deliver Reports and Analyses That Drive Action . . . . . . . . . . . . . . . 412The Unböring Filter 413Connecting Insights with Actual Data 414

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Changing Metric Definitions to Change Cultures: Brand Evangelists Index . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 415The Case and the Analysis 415The Problem 416The Solution 417The Results 417The Outcome 418An Alternative Calculation: Weighted Mean 418The Punch Line 419

Slay the Data Quality Dragon: Shift from Questioning to Using Data . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 420Pick a Different Boss 420Distract HiPPOs with Actionable Insights 422Dirty Little Secret 1: Head Data Can Be Actionable in the First Week/Month 422Dirty Little Secret 2: Data Precision Improves Lower in the Funnel 423The Solution Is Not to Implement Another Tool! 423Recognize Diminishing Marginal Returns 424Small Site, Bigger Problems 424Fail Faster on the Web 425

Five Rules for Creating a Data-Driven Boss . . . . . . . . . . . . . . . . . . . 426Get Over Yourself 426Embrace Incompleteness 426Always Give 10 Percent Extra 427Become a Marketer 427Business in the Service of Data . Not! 428Adopt the Web Analytics 2 .0 Mind-Set 428

Need Budget? Strategies for Embarrassing Your Organization . . . . . 429Capture Voice of Customer 430Hijack a Friendly Website 431If All Else Fails…Call Me! 432

Strategies to Break Down Barriers to Web Measurement . . . . . . . . . 432First, a Surprising Insight 433Lack of Budget/Resources 433Lack of Strategy 434Siloed Organization 434Lack of Understanding 435Too Much Data 435Lack of Senior Management Buy-In 436IT Blockages 437Lack of Trust in Analytics 439Finding Staff 439Poor Technology 439

Who Owns Web Analytics? . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 440To Centralize or Not to Centralize 440Evolution of the Team 441

Appendix About the Companion CD 443

Index 447

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IntroductionI have a simple, if lofty, goal with this book: to change how the world makes

decisions when it comes to online. For far too long our online efforts have accurately been classified as faith-based initiatives.

And why not? that’s exactly how we made decisions for our offline efforts, and when we moved online, we duplicated those practices. But online, in the glorious beautiful world of the Web, we do not have to rely on faith.

We live in the most data-rich environment on the planet—an environment where numbers, data, math, and analysis should be the foundation of our decisions. We can use data to deter-mine how to market effectively, how to truly connect with our audiences, how to improve the customer experience on our sites, how to invest our meager resources, and how to improve our return on investment, be it getting donations, increasing revenue, or winning elections!

You have a God-given right to be data driven, and this book will show you how to exer-cise that right.

Web Analytics 2.0 is a framework that redefines what data means online. Web Analytics 2.0 is not simply about the clicks that you collect from your website using analytics tools like Google Analytics, omniture, or Xiti. Web Analytics 2.0 is about pouring your heart into understanding the impact and economic value of your website by doing rigorous outcomes analysis. It is about expressing your love for the principles of customer centricity by embracing voice-of-customer initia-tives and, my absolute favorite, learning to fail faster by leveraging the power of experimentation. It is also—and this is so cool—about breaking free from your data silos by using competitive intel-ligence data to truly understand the strengths and weaknesses of your competitors.

this book answers four existential questions: what, how much, why, and what else.

The Second Little Book That Could

Like my first book, 100 percent of my proceeds from this book will be donated to two charities.

The Smile Train does cleft lip and palate surgery in 63 of the world’s poorest countries. They help do more than give the smile back to a child. Their efforts eliminate a condition that can have deep physical and long-term emotional implications for a child.

Ekal Vidyalaya initiates, supports, and runs nonformal one-teacher schools in the most rural parts of India. By locating their schools in remote areas neglected by the government and development agencies, they help eradicate illiteracy and open new paths for children.

By buying this book, you will elevate your knowledge and expertise about web analytics, but you are also helping me support two causes that are near and dear to my heart. When it comes to helping those in need, every little bit counts. Thank you.

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The Awesome World of Data-Driven Decision Makingthe offline world is not going anywhere. But the Web is becoming central to every aspect of our existence. It does not matter if you are a small-business owner, a politician, a mom, a student, an activist, a worker bee, or just one of 7 billion Homo sapiens on this planet. It does not matter if you live in Athens, Antananarivo, Abu dhabi, or Albuquerque.

We have access to multiple data sources (quantitative, qualitative, and competitive). We have access to an abundance of free tools that we can use to ensure our web deci-sions, from the tactical to the strategic, are informed by data. those decisions may range from what content should go on which page, to how to purchase the right set of keywords for our search marketing campaigns, to how to find the audience with the perfect demo-graphic and psychographic profile for our business, to how to delight visitors when they get to our website.

I have compared web analytics to Angelina Jolie; that comparison should suggest how sexy it is, how powerful it is, and what a force for good I think it is. By the time you are halfway through this book I am positive you’ll agree with me.

What’s Inside the Book?this book builds on the foundation laid by my first book, Web Analytics: An Hour a Day. I am not going to beat around the bush; chapter 1 starts with a bang by introducing you to the Web Analytics 2.0 framework. that is followed immediately by a strong case for why the multiplicity mental model is mandatory for success with tools. We go from 0 to 60 in 13 pages!

Picking the right set of tools might be just as important as picking your friends: pick the wrong one, and it might take a long time to recover. With chapter 2, I walk you through a process of self-reflection that will empower you to choose the right set of web analytics tools for your company. You’ll also learn questions you can ask tool vendors (why not stress them a bit?), the approach for choosing your vendor, and finally how to optimally negotiate your contract (stress them again!).

chapters 3 and 4 cover the awesome world of traditional web analytics, clickstream analysis. In chapter 3, using eight specific metrics, you’ll learn the intricate nuances that go into modern metrics: what you should look for, what you should avoid, and how to ensure that your company has chosen the right set of metrics. You’ll also learn my favorite technique for diagnosing the root cause behind poor performance.

chapter 4 picks up the story and gently walks you through a primer on web analyt-ics that will empower you to move very quickly from data to action on your website. I’ll then explore foundational analytical strategies followed by six specific analyses for your daily life. In every section you’ll learn how to kick things up a notch or two above average expectations. this chapter closes with a reality check on five key web analytics challenges (you are not going to want to miss this!).

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chapter 5 will be your best friend because it covers the single biggest reason for the existence of your websites: outcomes. that is, conversions, revenue, customer satisfaction, visitor loyalty, and more. You’ll learn the value of focusing on micro conversions (a must do!). At the end of the chapter, I offer two specific sets of recommendations on how to measure outcomes on non-ecommerce and B2B websites.

In chapter 6, the Web Analytics 2.0 fun really starts because I cover the wonder-ful world of customer centricity: listening to customers and doing so at scale. You’ll learn to leverage lab usability, surveys, and other user-centric design methodologies. Finally, I give an outline of exciting techniques on the horizon—techniques that will dramatically change how you think of leveraging voice of customer.

chapter 7 covers experimentation and testing. If you have ever read my blog or heard me speak, you’ll know how absolutely liberating it is that the Web allows us to fail faster, frequently, and get smarter every single day. You’ll learn about A/B and multivari-ate testing, but I think you’ll remember this book the most for teaching you about the power of controlled experiments (finally you can answer the hardest questions you’ll ever face!).

chapter 8 will help you come to grips with competitive intelligence analysis. Like the rest of this book, this chapter is not about teaching you how to use one tool or the other. no sirree, Bob! You’ll learn how to dig under the covers and understand how data is captured and why with competitive intelligence more than anywhere else the principle of garbage in, garbage out applies. By the time you finish this chapter, you’ll know how to analyze the website traffic of your competitors, use search data to measure brand and identify new opportunities, zero in on the audiences relevant for your campaign or busi-ness, and benchmark yourself against your competitors.

chapter 9 will clarify how to measure the new and evolving fields of mobile analyt-ics; you’ll see why measuring blogs is not like measuring websites and how to measure the success of your efforts on social channels such as twitter. You’ll start by learning about the fundamental challenges that the social Web presents for measurement.

chapter 10 starts the process of truly converting you to an analysis ninja. I cover the hidden rules of the game, issues to be careful about, tasks to do more, and why some approaches work and others don’t. You’ll want to read the end of this chapter to learn why revolutions in web data fail miserably and evolution works magnificently. oh, and as you might expect, I offer a very specific recommended path to nirvana!

chapter 11 is about analytical techniques—the key weapons that you’ll need in your arsenal as you head off to conquer the data world. You’ll get to know context, com-parisons, “what’s changed,” latent conversions, the head and tail of search, and really, really advanced paid search analysis. oh my.

chapter 12 contains material that will be worth multiple times the price of this book. It tackles the hardest, baddest, meanest web data challenges on the planet today: multitouch campaign attribution analysis and multichannel analytics. there’s no dancing

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around here, just practical actionable solutions you can implement right now, today. Don’t do anything in web analytics until you have read this chapter.

Chapter 13 was one of the most fun chapters for me to write. Web Analytics 2.0 is about people (not surprising coming from the creator of the 10/90 rule for magnificent success). Regardless of your role in the data world, this chapter includes guidance on how to plan your career to ensure maximum success. I offer best practices for keeping your knowledge current, but I don’t stop there; I suggest ways to move to the bleeding edge. The chapter closes with advice for managers and directors about how to identify the right talent, nurture them, and set them up for success.

Chapter 14 collects all my experience and research in this nascent field and shares rec-ommendations for tackling the one task that will make or break your success: creating a data-driven culture. I recommend approaches on how to present data, how to excite people, how to use metric definitions to influence behavioral change in your organization, and how to create a truly data-driven boss (yea!) and finally strategies for getting budget and support for your analytical program and people.

Does that sound exciting? Oh, it’s so much fun!

Valuable Multimedia Content on the CD

The podcasts, videos, and resources on the CD extend the content in the book by making concepts easier to understand and offering additional guidance and instruction not in the book. For more information, see the book’s appendix—or better yet, fire up the disc and start exploring.

Request for Feedback

I love preaching about the value of customer data, and I love practicing that mantra as well. I want to hear your thoughts about this book. What was the one thing you found to be of most value in the book? What was the biggest surprise? What was the one big thing you implemented and won praise for? What is one thing I should have done differently? What was the biggest missing piece?

You can email me at feedback@webanalytics20.com.I’ll learn from every bit of feedback, and I promise to reply to each and every per-

son who writes to me. Please share your experience, critiques, and kudos.One more fun thing: for my first book I requested readers to send me a picture with

the book (of people, places, babies, buildings, and so on). That led to the wonderful col-lection of pictures you’ll see here: http://zqi.me/wapeople. It makes the world a bit closer and more real.

I would love to get a picture of you or your hometown or your pet with this book. Please email it to me at feedback@webanalytics20.com.

Thank you.

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The BeginningI am sure you can tell that I had a ton of fun writing this book. I really, really did. I am confident that you’ll have just as much fun reading it, learning from it, and changing the world one insightful analysis at a time.

Let’s go!

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Web Analytics 2.0

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