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Adobe Analytics For Dummies [Minkštas viršelis]

3.40/5 (10 ratings by Goodreads)
  • Formatas: Paperback / softback, 400 pages, aukštis x plotis x storis: 234x188x25 mm, weight: 522 g
  • Išleidimo metai: 10-May-2019
  • Leidėjas: For Dummies
  • ISBN-10: 1119446082
  • ISBN-13: 9781119446088
Kitos knygos pagal šią temą:
  • Formatas: Paperback / softback, 400 pages, aukštis x plotis x storis: 234x188x25 mm, weight: 522 g
  • Išleidimo metai: 10-May-2019
  • Leidėjas: For Dummies
  • ISBN-10: 1119446082
  • ISBN-13: 9781119446088
Kitos knygos pagal šią temą:
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.

Introduction 1(4)
About This Book
1(1)
Foolish Assumptions
2(1)
Icons Used in This Book
2(1)
Beyond the Book
3(1)
Where to Go from Here
3(2)
PART 1 GETTING STARTED WITH ADOBE ANALYTICS
5(60)
Chapter 1 Why Adobe Analytics?
7(20)
Understanding Why You're Using Adobe Analytics
8(3)
Avoiding HiPPO!
8(2)
Knowing when you need Adobe Analytics
10(1)
Knowing the difference between reporting and analysis
10(1)
Identifying Where Adobe Analytics Data Comes From
11(5)
Capturing data from websites
12(2)
Capturing data from mobile devices
14(1)
Mining data from native apps
14(1)
Data from IoT and beyond
15(1)
Configuring and Analyzing Data
16(3)
Preparing to slice and dice data
16(1)
Optimizing your raw data
17(1)
Being a data collection detective
17(2)
Situating Adobe Analytics in the Universe of Data Analysis
19(7)
Surveying how Adobe Analytics stacks up
19(3)
Understanding how Google Analytics fits into the picture
22(3)
Evaluating plusses and minuses
25(1)
Noting other analytics options
26(1)
Building a Positive Relationship with Your Data Team
26(1)
Chapter 2 Basic Building Blocks of Reporting and Analysis
27(18)
Standard Categories of Measurement
28(1)
Defining Dimensions
29(4)
Using the page dimension
30(1)
Knowing when a page is not a page
30(1)
Appreciating the foundational role of the page dimension
31(1)
Splitting dimensions with breakdowns
32(1)
Measuring with Metrics
33(6)
Defining hits
33(1)
Measuring page views
33(1)
Counting visits
34(2)
Identifying unique visitors
36(1)
Understanding deduplication
37(1)
Trending metrics
38(1)
Calculating metrics
38(1)
Measuring with Segments
39(2)
Using Report Suites
41(4)
Breaking it down in the real world
42(1)
Using Adobe Experience Cloud Debugger to identify your report suite
43(2)
Chapter 3 Conquering the Analysis Workspace Interface
45(20)
Surveying the Analytics Environment
46(1)
Zooming In on the Workspace
47(1)
Creating Your First Project
48(3)
Understanding the Calendar
51(2)
Using Analysis Workspace Panels
53(3)
Adding Dimensions, Metrics, Segments, and Time Components
56(6)
Adding a dimension
58(1)
Adding a metric
59(1)
Adding a dimensional breakdown
59(1)
Adding a segment
60(1)
Adding a time
60(2)
Navigating the Menu Structure
62(3)
PART 2 ANALYZING DATA
65(108)
Chapter 4 Building Analytic Reports with Freeform Tables
67(20)
Working with Dimensions and Metrics
67(3)
Wrapping your head around dimensions
68(1)
Combining dimensions and metrics
68(2)
Adding Dimensions to a Table
70(3)
Adding the page dimension
70(1)
Analyzing a second dimension using the visit number dimension
71(1)
Mixing in the marketing channel dimension
72(1)
Zooming in with Multiple Metrics
73(2)
Replacing a metric
73(1)
Adding a second metric
73(1)
Throwing a third metric into the mix
74(1)
Sorting and Filtering Data
75(3)
Sorting freeform tables in ascending and descending order
75(1)
Filtering freeform tables based on a word or phrase
76(1)
Advanced filtering of freeform tables
77(1)
Dropping into the Segment Drop Zone
78(3)
Dropping one or more segments into the drop zone
78(2)
Using metrics, dimensions, and time ranges in the drop zone
80(1)
Exploiting the Value of Templates
81(6)
Looking at the content consumption template
82(1)
Examining the products template
83(1)
Using custom templates
84(1)
Creating custom templates
84(3)
Chapter 5 Using Metrics to Analyze Data
87(20)
Analyzing Time Spent
88(5)
Counting total seconds spent
89(1)
Measuring time spent per visit (seconds)
90(1)
Identifying time spent per visitor (seconds)
91(1)
Calculating average time on site
91(1)
Assessing mobile app time spent
92(1)
Using Metrics for Bounces, Bounce Rate, and Single Page Visits
93(1)
Understanding Metrics Unique to Adobe
94(6)
Counting instances
94(1)
Measuring occurrences
94(2)
Averaging page views per visit
96(1)
Averaging page depth
96(1)
Distinguishing page hits from page events
97(1)
Identifying pages not found
98(1)
Measuring visitors with Experience Cloud ID
98(1)
Analyzing single access
99(1)
Analyzing visits from search engines
99(1)
Using the people metric
99(1)
Exploiting Product and Cart Metrics
100(4)
Identifying product views
100(1)
Metrics for shopping carts
101(2)
Using purchase metrics
103(1)
Working with Custom Metrics in Adobe
104(3)
Chapter 6 Using Dimensions to Analyze Data
107(26)
Wielding Content Dimensions
108(13)
Identifying server sources
108(1)
Looking at the site section dimension
109(1)
Examining hierarchy
110(2)
Finding error pages
112(1)
Analyzing links
112(5)
Specifying Activity Map dimensions
117(4)
Connecting Behavior to Advertising
121(12)
Analyzing referrer dimensions
121(2)
Tracking marketing channels
123(3)
Tying back to search engines
126(4)
Applying campaign tracking codes
130(3)
Chapter 7 Using Device, Product, and Custom Dimensions to Analyze Data
133(22)
Defining Key Technology Dimensions
134(4)
Distinguishing browsers and operating systems
134(1)
Differentiating mobile device dimensions
135(2)
Locating users with geographic dimensions
137(1)
Dissecting Product Dimensions
138(3)
Zooming in on product
139(1)
Adopting product category ... or not
140(1)
Identifying customer loyalty
140(1)
Sifting through Time Dimensions
141(8)
Applying time-parting
141(1)
Measuring time spent
142(1)
Analyzing visit number
143(2)
Identifying days before first purchase
145(1)
Analyzing days since last purchase
146(1)
Measuring return frequency
147(1)
Identifying single-page visits
148(1)
Working with Custom Dimensions
149(6)
Defining expiration and allocation dimensions
149(2)
Distinguishing between props and eVars
151(2)
Applying date ranges
153(2)
Chapter 8 Productivity Tips and Techniques
155(18)
Exploiting Essential Keyboard and Mouse Shortcuts
155(5)
Opening projects and saving work
156(1)
Creating content
156(1)
Undoing and redoing edits
157(1)
Making quick selections for breakdowns
157(1)
Using the clipboard to move data to other apps
158(1)
Refreshing content
159(1)
Deploying key keyboard shortcuts
159(1)
Taking Advantage of One-Click Visualize
160(5)
Generating unlocked visualizations
160(2)
Locking visualizations
162(3)
Saving time with visualization shortcuts
165(1)
Invoking Time Comparisons
165(4)
Adding a time period column
167(1)
Comparing time periods
168(1)
Applying Conditional Formatting
169(4)
Understanding conditional formatting options
169(4)
PART 3 MASSAGING DATA FOR COMPLEX ANALYSIS
173(82)
Chapter 9 Designing Precise Segments
175(16)
Understanding and Defining Segments
176(5)
Identifying segment containers
177(1)
Distinguishing segment containers
178(3)
Defining a Segment and Setting the Container
181(6)
Governing your segments properly
183(2)
Creating segments dynamically in a freeform table
185(1)
Sharing segments between users and Adobe solutions
185(2)
Using Virtual Report Suites Based on Segments
187(4)
Identifying virtual report suites
187(1)
Curating via virtual report suites
188(1)
Redefining visits with context-aware sessions
189(2)
Chapter 10 Creating Calculated Metrics to Accelerate Analyses
191(22)
Understanding and Defining Calculated Metrics
191(5)
Calculated metrics in the real world
192(1)
Calculated metrics in the data world
193(3)
Creating Basic Calculated Metrics in a Freeform Table
196(2)
Calculating with two metrics
196(2)
Applying functions to a single metric
198(1)
Building Calculated Metrics from Scratch
198(8)
Adding static numbers to a metric definition
202(1)
Including parentheses when defining new metrics
203(1)
Applying segments to create derived metrics
204(2)
Getting the Most from Calculated Metrics
206(7)
Applying basic and advanced functions
207(3)
Governing all of your calculated metrics
210(3)
Chapter 11 Classified! Using Classifications to Make Data More Accessible
213(22)
Making Data Coherent and Accessible
214(4)
Renaming unfriendly codes
214(1)
Consolidating with classifications
215(1)
Consolidating retroactively
216(1)
Thinking outside product classifications
217(1)
Applying classifications to breakdowns, metrics, and segments
218(1)
Working with Classified Data
218(3)
Identifying classified dimensions
219(1)
Confirming: The best way to identify your classifications
220(1)
Defining Classifications
221(4)
Sending Data to a Classification
225(10)
Importing classification data in bulk
225(3)
Automating classifications with Rule Builder
228(7)
Chapter 12 Applying Attribution Models for Sophisticated Analysis
235(20)
Applying Attribution to Your Data
236(2)
Differentiating Attribution Models
238(6)
Applying last touch and first touch models
238(2)
Considering linear and participation models
240(1)
Exploring U-shaped, J-shaped, and inverse J models
241(1)
Using custom and time decay models
242(1)
Defining best fit, algorithmic, and data-driven attribution
243(1)
Operating Attribution IQ in Workspace
244(11)
Applying Attribution IQ in freeform tables
244(3)
Creating calculated metrics with Attribution IQ
247(3)
Comparing models using the attribution panel
250(5)
PART 4 VISUALIZING DATA TO REVEAL GOLDEN NUGGETS
255(88)
Chapter 13 Creating Chart Visualizations for Data Storytelling
257(22)
Getting the Most from Charts in Adobe Analytics
258(8)
Getting visualization tips from templates
258(1)
Dissecting a donut chart
258(2)
Breaking down a bar chart
260(2)
Looking at trends in a line chart
262(2)
Sizing up data with stacked bar charts
264(1)
Surveying multiple metrics with scatterplots
265(1)
Creating Charts from Table Data
266(4)
Generating a chart from a row of data
266(1)
Generating a chart from multiple rows
267(2)
Locking data displayed in a visualization
269(1)
Building Histograms and Venn Diagrams
270(5)
Organizing data with histograms
271(2)
Deriving insights from Venn diagrams
273(2)
Defining Chart Attributes in Detail
275(2)
Visualization Beyond Data Charts
277(2)
Chapter 14 Advanced Visualization
279(24)
Visualizing Flow Paths
279(7)
Defining flow paths
280(1)
Creating a flow visualization
281(1)
Interacting with flow visualizations
282(4)
Analyzing Fallout Paths
286(5)
Understanding fallout terms and concepts
287(1)
Generating a fallout visualization
287(4)
Building Cohort Tables
291(7)
Understanding essential cohort table terminology
291(2)
Generating a cohort visualization
293(3)
Migrating from Google Analytics' cohort table
296(2)
Customizing and Sharing Curated Projects
298(2)
Changing Color Palettes
300(3)
Chapter 15 Leveraging Data Science to Identify Unknown Unknowns
303(18)
Detecting Anomalies
304(7)
Using Anomaly Detection for KPIs
304(1)
Understanding how Anomaly Detection works
305(1)
Understanding the logic and math behind Anomaly Detection
305(1)
Identifying statistical methods and rules behind Anomaly Detection
306(1)
Viewing anomalies in a date-based freeform table
307(2)
Viewing anomalies without a date dimension via a trended line chart
309(1)
Turning off Anomaly Detection
310(1)
Discovering Contribution Analysis
311(3)
Using Data Science to Compare Segments
314(7)
Invoking Segment Comparison
315(3)
Brainstorming Segment Comparison use cases
318(3)
Chapter 16 Arming Yourself with Data from the Beyond
321(22)
Drawing Analysis outside Workspace
322(10)
Exporting projects to CSV or PDF
322(1)
Sending projects from workspace to email
323(2)
Creating alerts based on anomalies
325(3)
Tapping into Adobe data directly in Excel
328(4)
Visual Analysis Heat Maps with Activity Map
332(2)
Integrating within Adobe Products
334(3)
Dissecting Adobe Audience Manager audiences in Workspace
335(1)
Integrating your tests and personalization
336(1)
Capturing email metrics in Workspace
337(1)
Integrating beyond Individual Products
337(6)
Analyzing ad data in Adobe
338(1)
Accessing the scale of Experience Cloud
339(1)
Connecting data into Adobe Analytics today
340(1)
Incorporating any dataset in the future
341(2)
PART 5 THE PART OF TENS
343(28)
Chapter 17 Top Ten Custom Segments
345(14)
Identifying Purchasers
346(3)
Defining a Non-Purchasers Segment
349(2)
Isolating Single-Page Visitors
351(2)
Identifying Single-Visit, Multi-Page Visitors
353(1)
Bucketing SEO to Internal Search
354(1)
Segmenting Pre-Purchase Activity
355(1)
Going Strictly Organic
356(1)
Finding Strictly Paid Activity
356(1)
Filtering Out Potential Bots
357(1)
Identifying Checkout Fallout
358(1)
Chapter 18 Top Ten Analytics Resources
359(12)
Checking Out Adobe's Analytics Implementation Guide
360(2)
Understanding Why You Need a Measurement Plan
362(1)
Using Data Governance
362(1)
Setting Up a Web Analytics Solution Design
363(1)
Listening In on the Digital Analytics Power Hour
364(1)
Getting Insights from Analytics Agencies
365(1)
Attending Conferences, Conferences, Conferences
366(1)
Joining the Adobe Experience League
367(1)
Learning the Latest from the Adobe Analytics YouTube channel
368(1)
Hacking the Bracket with Adobe Analytics
369(2)
Index 371
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.