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
