Adobe Analytics For Dummies

Adobe Analytics For Dummies

Adobe Analytics For Dummies

Adobe Analytics For Dummies


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Use Adobe Analytics as a marketer —not a programmer!

If you're a marketer in need of a non-technical, beginner's reference to using Adobe Analytics, this book is the perfect place to start. Adobe Analytics For Dummies arms you with a basic knowledge of the key features so that you can start using it quickly and effectively.

Even if you're a digital marketer who doesn't have their hands in data day in and day out, this easy-to-follow reference makes it simple to utilize Adobe Analytics. With the help of this book, you'll better understand how your marketing efforts are performing, converting, being engaged with, and being shared in the digital space.

  • Evaluate your marketing strategies and campaigns
  • Explore implementation fundamentals and report architecture
  • Apply Adobe Analytics to multiple sources
  • Succeed in the workplace and expand your marketing skillset

The marketing world is continually growing and evolving, and Adobe Analytics For Dummies will help you stay ahead of the curve.

Product Details

ISBN-13: 9781119446088
Publisher: Wiley
Publication date: 04/02/2019
Series: For Dummies Books
Pages: 400
Product dimensions: 7.40(w) x 9.10(h) x 0.90(d)

About the Author

Eric Matisoff is Adobe's global evangelist for their Analytics solution. He appears regularly at tech and industry events to speak about Adobe products and their potential. David Karlins has written 40 books on digital communications and design, including HTML 5 & CSS 3 For Dummies.

Table of Contents

Introduction 1

About This Book 1

Foolish Assumptions 2

Icons Used in This Book 2

Beyond the Book 3

Where to Go from Here 3

Part 1: Getting Started with Adobe Analytics 5

Chapter 1: Why Adobe Analytics? 7

Understanding Why You’re Using Adobe Analytics 8

Avoiding HiPPO! 8

Knowing when you need Adobe Analytics 10

Knowing the difference between reporting and analysis 10

Identifying Where Adobe Analytics Data Comes From 11

Capturing data from websites 12

Capturing data from mobile devices 14

Mining data from native apps 14

Data from IoT and beyond 15

Configuring and Analyzing Data 16

Preparing to slice and dice data 16

Optimizing your raw data 17

Being a data collection detective 17

Situating Adobe Analytics in the Universe of Data Analysis 19

Surveying how Adobe Analytics stacks up 19

Understanding how Google Analytics fits into the picture 22

Evaluating plusses and minuses 25

Noting other analytics options 26

Building a Positive Relationship with Your Data Team 26

Chapter 2: Basic Building Blocks of Reporting and Analysis 27

Standard Categories of Measurement 28

Defining Dimensions 29

Using the page dimension 30

Knowing when a page is not a page 30

Appreciating the foundational role of the page dimension 31

Splitting dimensions with breakdowns 32

Measuring with Metrics 33

Defining hits 33

Measuring page views 33

Counting visits 34

Identifying unique visitors 36

Understanding deduplication 37

Trending metrics 38

Calculating metrics 38

Measuring with Segments 39

Using Report Suites 41

Breaking it down in the real world 42

Using Adobe Experience Cloud Debugger to identify your report suite 43

Chapter 3: Conquering the Analysis Workspace Interface 45

Surveying the Analytics Environment 46

Zooming In on the Workspace 47

Creating Your First Project 48

Understanding the Calendar 51

Using Analysis Workspace Panels 53

Adding Dimensions, Metrics, Segments, and Time Components 56

Adding a dimension 58

Adding a metric 59

Adding a dimensional breakdown 59

Adding a segment 60

Adding a time 60

Navigating the Menu Structure 62

Part 2: Analyzing Data 65

Chapter 4: Building Analytic Reports with Freeform Tables 67

Working with Dimensions and Metrics 67

Wrapping your head around dimensions 68

Combining dimensions and metrics 68

Adding Dimensions to a Table 70

Adding the page dimension 70

Analyzing a second dimension using the visit number dimension 71

Mixing in the marketing channel dimension 72

Zooming in with Multiple Metrics 73

Replacing a metric 73

Adding a second metric 73

Throwing a third metric into the mix 74

Sorting and Filtering Data 75

Sorting freeform tables in ascending and descending order 75

Filtering freeform tables based on a word or phrase 76

Advanced filtering of freeform tables 77

Dropping into the Segment Drop Zone 78

Dropping one or more segments into the drop zone 78

Using metrics, dimensions, and time ranges in the drop zone 80

Exploiting the Value of Templates 81

Looking at the content consumption template 82

Examining the products template 83

Using custom templates 84

Creating custom templates 84

Chapter 5: Using Metrics to Analyze Data 87

Analyzing Time Spent 88

Counting total seconds spent 89

Measuring time spent per visit (seconds) 90

Identifying time spent per visitor (seconds) 91

Calculating average time on site 91

Assessing mobile app time spent 92

Using Metrics for Bounces, Bounce Rate, and Single Page Visits 93

Understanding Metrics Unique to Adobe 94

Counting instances 94

Measuring occurrences 94

Averaging page views per visit 96

Averaging page depth 96

Distinguishing page hits from page events 97

Identifying pages not found 98

Measuring visitors with Experience Cloud ID 98

Analyzing single access 99

Analyzing visits from search engines 99

Using the people metric 99

Exploiting Product and Cart Metrics 100

Identifying product views 100

Metrics for shopping carts 101

Using purchase metrics 103

Working with Custom Metrics in Adobe 104

Chapter 6: Using Dimensions to Analyze Data 107

Wielding Content Dimensions 108

Identifying server sources 108

Looking at the site section dimension 109

Examining hierarchy 110

Finding error pages 112

Analyzing links 112

Specifying Activity Map dimensions 117

Connecting Behavior to Advertising 121

Analyzing referrer dimensions 121

Tracking marketing channels 123

Tying back to search engines 126

Applying campaign tracking codes 130

Chapter 7: Using Device, Product, and Custom Dimensions to Analyze Data 133

Defining Key Technology Dimensions 134

Distinguishing browsers and operating systems 134

Differentiating mobile device dimensions 135

Locating users with geographic dimensions 137

Dissecting Product Dimensions 138

Zooming in on product 139

Adopting product category or not 140

Identifying customer loyalty 140

Sifting through Time Dimensions 141

Applying time-parting 141

Measuring time spent 142

Analyzing visit number 143

Identifying days before first purchase 145

Analyzing days since last purchase 146

Measuring return frequency 147

Identifying single-page visits 148

Working with Custom Dimensions 149

Defining expiration and allocation dimensions 149

Distinguishing between props and eVars 151

Applying date ranges 153

Chapter 8: Productivity Tips and Techniques 155

Exploiting Essential Keyboard and Mouse Shortcuts 155

Opening projects and saving work 156

Creating content 156

Undoing and redoing edits 157

Making quick selections for breakdowns 157

Using the clipboard to move data to other apps 158

Refreshing content 159

Deploying key keyboard shortcuts 159

Taking Advantage of One-Click Visualize 160

Generating unlocked visualizations 160

Locking visualizations 162

Saving time with visualization shortcuts 165

Invoking Time Comparisons 165

Adding a time period column 167

Comparing time periods 168

Applying Conditional Formatting 169

Understanding conditional formatting options 169

Part 3: Massaging Data for Complex Analysis 173

Chapter 9: Designing Precise Segments 175

Understanding and Defining Segments 176

Identifying segment containers 177

Distinguishing segment containers 178

Defining a Segment and Setting the Container 181

Governing your segments properly 183

Creating segments dynamically in a freeform table 185

Sharing segments between users and Adobe solutions 185

Using Virtual Report Suites Based on Segments 187

Identifying virtual report suites 187

Curating via virtual report suites 188

Redefining visits with context-aware sessions 189

Chapter 10: Creating Calculated Metrics to Accelerate Analyses 191

Understanding and Defining Calculated Metrics 191

Calculated metrics in the real world 192

Calculated metrics in the data world 193

Creating Basic Calculated Metrics in a Freeform Table 196

Calculating with two metrics 196

Applying functions to a single metric 198

Building Calculated Metrics from Scratch 198

Adding static numbers to a metric definition 202

Including parentheses when defining new metrics 203

Applying segments to create derived metrics 204

Getting the Most from Calculated Metrics 206

Applying basic and advanced functions 207

Governing all of your calculated metrics 210

Chapter 11: Classified! Using Classifications to Make Data More Accessible 213

Making Data Coherent and Accessible 214

Renaming unfriendly codes 214

Consolidating with classifications 215

Consolidating retroactively 216

Thinking outside product classifications 217

Applying classifications to breakdowns, metrics, and segments 218

Working with Classified Data 218

Identifying classified dimensions 219

Confirming: The best way to identify your classifications 220

Defining Classifications 221

Sending Data to a Classification 225

Importing classification data in bulk 225

Automating classifications with Rule Builder 228

Chapter 12: Applying Attribution Models for Sophisticated Analysis 235

Applying Attribution to Your Data 236

Differentiating Attribution Models 238

Applying last touch and first touch models 238

Considering linear and participation models 240

Exploring U-shaped, J-shaped, and inverse J models 241

Using custom and time decay models 242

Defining best fit, algorithmic, and data-driven attribution 243

Operating Attribution IQ in Workspace 244

Applying Attribution IQ in freeform tables 244

Creating calculated metrics with Attribution IQ 247

Comparing models using the attribution panel 250

Part 4: Visualizing Data to Reveal Golden Nuggets 255

Chapter 13: Creating Chart Visualizations for Data Storytelling 257

Getting the Most from Charts in Adobe Analytics 258

Getting visualization tips from templates 258

Dissecting a donut chart 258

Breaking down a bar chart 260

Looking at trends in a line chart 262

Sizing up data with stacked bar charts 264

Surveying multiple metrics with scatterplots 265

Creating Charts from Table Data 266

Generating a chart from a row of data 266

Generating a chart from multiple rows 267

Locking data displayed in a visualization 269

Building Histograms and Venn Diagrams 270

Organizing data with histograms 271

Deriving insights from Venn diagrams 273

Defining Chart Attributes in Detail 275

Visualization Beyond Data Charts 277

Chapter 14: Advanced Visualization 279

Visualizing Flow Paths 279

Defining flow paths 280

Creating a flow visualization 281

Interacting with flow visualizations 282

Analyzing Fallout Paths 286

Understanding fallout terms and concepts 287

Generating a fallout visualization 287

Building Cohort Tables 291

Understanding essential cohort table terminology 291

Generating a cohort visualization 293

Migrating from Google Analytics’ cohort table 296

Customizing and Sharing Curated Projects 298

Changing Color Palettes 300

Chapter 15: Leveraging Data Science to Identify Unknown Unknowns 303

Detecting Anomalies 304

Using Anomaly Detection for KPIs 304

Understanding how Anomaly Detection works 305

Understanding the logic and math behind Anomaly Detection 305

Identifying statistical methods and rules behind Anomaly Detection 306

Viewing anomalies in a date-based freeform table 307

Viewing anomalies without a date dimension via a trended line chart 309

Turning off Anomaly Detection 310

Discovering Contribution Analysis 311

Using Data Science to Compare Segments 314

Invoking Segment Comparison 315

Brainstorming Segment Comparison use cases 318

Chapter 16: Arming Yourself with Data from the Beyond 321

Drawing Analysis outside Workspace 322

Exporting projects to CSV or PDF 322

Sending projects from workspace to email 323

Creating alerts based on anomalies 325

Tapping into Adobe data directly in Excel 328

Visual Analysis Heat Maps with Activity Map 332

Integrating within Adobe Products 334

Dissecting Adobe Audience Manager audiences in Workspace 335

Integrating your tests and personalization 336

Capturing email metrics in Workspace 337

Integrating beyond Individual Products 337

Analyzing ad data in Adobe 338

Accessing the scale of Experience Cloud 339

Connecting data into Adobe Analytics today 340

Incorporating any dataset in the future 341

Part 5: The Part of Tens 343

Chapter 17: Top Ten Custom Segments 345

Identifying Purchasers 346

Defining a Non-Purchasers Segment 349

Isolating Single-Page Visitors 351

Identifying Single-Visit, Multi-Page Visitors 353

Bucketing SEO to Internal Search 354

Segmenting Pre-Purchase Activity 355

Going Strictly Organic 356

Finding Strictly Paid Activity 356

Filtering Out Potential Bots 357

Identifying Checkout Fallout 358

Chapter 18: Top Ten Analytics Resources 359

Checking Out Adobe’s Analytics Implementation Guide 360

Understanding Why You Need a Measurement Plan 362

Using Data Governance 362

Setting Up a Web Analytics Solution Design 363

Listening In on the Digital Analytics Power Hour 364

Getting Insights from Analytics Agencies 365

Attending Conferences, Conferences, Conferences 366

Joining the Adobe Experience League 367

Learning the Latest from the Adobe Analytics YouTube channel 368

Hacking the Bracket with Adobe Analytics 369

Index 371

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