Google Data Studio Toronto, Ontario May 31, 2017
Introductions Share with us: Your name, organization, and role How do you currently display and share data? e.g. Excel? PowerPoint? Dashboards in Google Analytics? Tableau? Other tools? One thing you must learn to make this course worthwhile 2
Who am I? Marc Soares Senior Consultant Digital analytics consulting at ClickInsight Measurement strategy, design, & implementation Reporting, visualization, & analysis Instructor for Google Analytics, Google Tag Manager, & Data Studio training courses 3
What We ll Cover Introduction Features & Benefits Overview Integrating with Google Analytics Fundamentals of Data Sources Connectors Fields, Dimensions, & Metrics Calculated Fields Fundamentals of Reports Charts & Components Pages Properties Principles of Data Visualization Why we visualize data How to visualize data effectively Choosing the right chart type Connecting to Data Connecting to Google Analytics Connecting to other sources Building Reports Using charts and filters Customizing style and formatting Sharing & Collaboration 4
Introduction Overview of Features and Interface 5
Google Data Studio Launched in May 2016 (U.S. Only) Available in Canada since Sept 2016 Free and unlimited since March 2017 Currently in Beta 6
Key Features & Benefits Connect to all your data sources in one place Clean and transform your data Build reports using the drag-and-drop visual editor Create interactive reports and dashboards Tell a story using a combination of words, numbers, and visuals Easily share reports and dashboards 7
7 Reasons to Use Data Studio with Google Analytics 1. Create as many reports as you need for free! 2. Customize the appearance of reports and dashboards 3. Combine data from different views and sources 4. Create calculated dimensions and metrics 5. Break the 12-widget limit 6. Share reports easily 7. Avoid GA Reporting API restrictions 8
Home Page Interface 9
Practice: Create a Report from a Template 1. Start a new report using the Acme Marketing template 2. Select [Sample] Google Analytics Data as the new data source 10
Report Editor Interface 11
Connecting to Data Creating and Editing Data Sources 12
Data Sources Reports in Data Studio can use one or more data sources Each data source connects to an underlying data set, for example: Google Analytics AdWords Search Console Google Sheets BigQuery CSV (Comma Separated Values) file 13
Practice: Connect to Google Analytics 1. Create a new data source 2. Select the Google Analytics connector 3. Authorize Data Studio to connect to your GA account 4. Select your GA account, property, and view 5. Click Connect 14
Data Source Editor Interface 15
Editing a Data Source You can perform the following changes to a data source: Rename the data source Rename fields Duplicate fields Create calculated fields Delete the data source Edits to a data source do not change the underlying data set 16
Metrics & Dimensions City, Campaign, and Device Category are Dimensions Sessions, Pages/Session, Avg. Session Duration are Metrics 17
Metrics & Dimensions Dimensions (attributes) City Device Category Page Title Campaign Name Browser Event Category etc. Metrics (measures) Users Sessions Pageviews Avg. Session Duration Ecommerce Conversion Rate Bounce Rate etc. 18
Calculated Fields In the Data Source editor, you can create calculated dimensions or metrics: Click the + button to create a new calculated field Enter a name for the new field Enter a formula For simple arithmetic, use standard operators: + - / * Refer to Function List for available functions and syntax 19
Practice: Create Calculated Fields 1. Create 4 calculated fields in your GA data source: a) Create a dimension that combines the Hostname and Page URI: CONCAT(Hostname, Page) b) Create a dimension that forces Medium to lowercase: LOWER(Medium) c) Create a metric for Avg. Sessions per User Sessions / Users d) Create a metric for the ratio of Pageviews to Unique Pageviews Pageviews / Unique Pageviews 20
Creating Reports Overview of Charts and Components 21
Components Reports are made up of components: Pages Charts Filter Controls Text and Images Groups 22
Charts The following charts are currently available in Data Studio: Bar chart Time series Table Geo map Scorecard Scatterplot Bullet chart Area chart Pie chart 23
Practice: Create a basic dashboard 1. Using your Google Analytics data source, create a report with the following charts: a) Time series of Sessions and Users by month b) Scorecard of Avg. Sessions per User c) Geo map of Avg. Session Duration by province d) Bar chart of Bounce Rate by Medium e) Table of most viewed pages with Unique Pageviews, Avg. Time on Page, and Pageviews / Unique Pageviews 24
Filtering Your Data 25
Filters Filters can be applied to the following components: Report Page Group Chart You can also add Filter Controls to allow report viewers to dynamically filter reports, pages, or charts Google Analytics data can be filtered by an Advanced Segment (segment must already exist in GA) 26
Practice: Filtering a Page 1. Duplicate your basic dashboard page Page > Duplicate Page 2. Add a page-level filter for mobile/tablet devices only Page > Current Page Settings > Page Filter 27
Practice: Filtering a Chart 1. On a new page, create a bar chart showing Sessions by Default Channel Grouping 2. Duplicate the chart 3. Filter the first chart for Desktop devices only 4. Filter the second chart for Mobile or Tablet devices only 28
Practice: Filtering by Date 1. Change the default date range for the report File > Report Settings > Default Date Range Set to Last Month 2. Add a Date Range filter control 3. Make the Date Range control report-level 29
Practice: Adding a Filter Control 1. Add a Filter Control for Default Channel Grouping 2. Sort Channels by Sessions descending 3. Select Expandable style from Style properties tab 30
Regular Expressions (RegEx) A regular expression is a sequence of characters that can be used to match a pattern of text Special characters and wildcards enable efficient matching For example: ^(www\.)?clickinsight\.ca$ Matches www.clickinsight.ca or clickinsight.ca United (States Kingdom) Matches United States or United Kingdom 31
Styling Your Report Overview of style and formatting options 32
Report Layout and Theme Use the Layout and Theme panel to apply style and formatting to the entire report Adjust view mode and canvas size Change colour scheme and default chart formatting 33
Text and Images You can draw text boxes, images, rectangles, or circles Ideas: Use text boxes to add titles, comments, and analysis to your reports Insert images and shapes to add corporate branding Use background shapes to visually group charts or create sections Make a component report-level to create a persistent header or footer 34
Practice: Styling your dashboard 1. Add a visual style to your GA dashboard: a) Adjust chart colours using the report-level theme settings b) Insert a text box and add a title for your dashboard c) Insert a logo image 35
Sharing Your Report 36
Sharing a Report Sharing a Data Studio report works similarly to Google Drive Share via a link Share with specific people You can grant View or Edit permissions Viewers don t need to sign-in and don t need access to the underlying data set You must share both the report and associated data source(s) 37
CASE Statements Advanced Examples of Conditional Calculations 38
CASE Statements Data Studio does not have an IF construct. You must use CASE to create conditional formulas. The CASE syntax: CASE WHEN condition THEN result ELSE result END You can have multiple WHEN THEN clauses The WHEN condition must return a Boolean (true or false) 39
Practice: Creating Custom Geographies 1. Create a calculated field using a CASE statement that produces a custom geographic grouping of provinces: a) British Columbia, Alberta, Saskatchewan, or Manitoba West b) Ontario or Quebec Central c) Nova Scotia, New Brunswick, Prince Edward Island, or Newfoundland and Labrador East Hint: Use the IN operator to match against a list of values e.g. WHEN Region IN ( Ontario, Quebec ) THEN Central 40
RegEx Functions Using Regular Expressions in Calculated Fields 41
RegEx Functions You can use RegEx functions in calculated fields: REGEXP_EXTRACT Extract a portion of a dimension value e.g. REGEXP_EXTRACT(Page, category=([^&]+) ) REGEXP_MATCH Match a dimension value against a regex pattern, returning true or false e.g. REGEXP_MATCH(Medium,"^(cpc ppc paidsearch)$") REGEXP_REPLACE Search and replace a text pattern within a dimension value e.g. REGEXP_REPLACE(Hostname, www.abc.xyz, abc.xyz ) 42
Data Viz 101 Principles of Data Visualization 43
What is Data Visualization? Data visualization is the use of visual representations to explore, make sense of, and communicate data. ~ Stephen Few 44
Why do we visualize data? Visualization enables us to: 1. See the big picture 2. Easily and rapidly compare values 3. See patterns among values 4. Compare patterns 45
1. See the big picture 46
2. Easily and rapidly compare values 47
3. See patterns among values 48
4. Compare patterns 49
Bad reasons for visualizing data Because some people are visual learners Because some people have difficulty understanding numbers Because visuals are eye-catching and grab people s attention 50
Edward Tufte s Principles 1. Above all else, show the data 2. Maximize the data-ink ratio 3. Erase non-data-ink 4. Erase redundant data-ink 5. Revise and edit 51
The Data-Ink Ratio Data Ink Ratio = Data ink Total ink used in graphic Data-ink is the non-erasable core of a graphic 52
Device Category Low vs. High Data-Ink Ratio Low Data-Ink Ratio High Data-Ink Ratio Sessions 0 10,000 20,000 30,000 40,000 Sessions Smartphone Smartphone 32,354 Desktop Desktop 22,718 Tablet Tablet 2,733 53
Sessions Sessions Low vs. High Data-Ink Ratio Low Data-Ink Ratio High Data-Ink Ratio Referral Direct Organic 45k Direct 45,000 40,000 Organic 35,000 30,000 30k 25,000 20,000 15,000 15k 10,000 5,000 Referral 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 0 Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec 54
Perfection is achieved not when there is nothing more to add, but when there is nothing left to take away. ~ Antoine de Saint-Exupery 55
Hierarchy of Visual Perception 1. Position along a common scale 2. Position on identical but non-aligned scales 3. Length 4. Angle & Slope 5. Area 6. Volume, density, and color saturation 7. Colour hue 56
Do you like pie? How different are the black slices between A and B? Is the green slice bigger in B or C? Is either bigger than A? 57
This is why pie charts suck. 58
The only worse design than a pie chart is several of them. ~ Edward Tufte 59
Exercise: Olympics Data Using a Google Sheet 60
Exercise: Summer Olympics Data 1. Connect to the Summer Olympics data set a) Open the Rio 2016 Summer Olympics Medal Results data set in Google Sheets (Link on Course Resources page) b) Make a copy of the sheet in your own Google Drive c) Create a new data source in Data Studio d) Select the Google Sheets connector e) Select the Rio 2016 Google Sheet f) Click Connect 61
Exercise: Summer Olympics Data 2. Create 4 calculated fields Total Medals Gold Medals Silver Medals Bronze Medals Hint: CASE WHEN Medal="Gold" THEN 1 ELSE 0 END 62
Exercise: Summer Olympics Data 3. Build a report that tells a story about the 2016 Olympics Use charts, tables, and filters to highlight parts of the data Insert titles, text, and images to support your story Keep it simple. Minimize non-data ink. 4. Share your finished report with msoares@clickinsight.ca 63
Exercise: Twitter Data Using a CSV File Upload 64
Exercise: Trump s Tweets 1. Connect to the Trump Tweets data set a) Download the trumptweets.csv data set from the Course Resources page b) Create a new data source using the File Upload connector c) Upload the trumptweets.csv file 2. Create a new report 3. Use Data Studio to tell a story about the data set 4. Share your finished report with msoares@clickinsight.ca 65
Contact Marc Soares Senior Digital Analytics Consultant ClickInsight Toronto, Ontario marc.soares@clickinsight.ca @marc_soares ClickInsight.ca 66
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