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Adobe Analytics For Dummies David Karlins

Adobe Analytics For Dummies By David Karlins

Adobe Analytics For Dummies by David Karlins

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Adobe Analytics For Dummies Summary

Adobe Analytics For Dummies by David Karlins

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.

About David Karlins

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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Adobe Analytics For Dummies by David Karlins
Used - Very Good
John Wiley & Sons Inc
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
This is a used book - there is no escaping the fact it has been read by someone else and it will show signs of wear and previous use. Overall we expect it to be in very good condition, but if you are not entirely satisfied please get in touch with us

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