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Universal Analytics - PowerPoint PPT Presentation

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Universal Analytics. &. Google Tag Manager. About @ analyticsninja. Loves working with fun businesses. Goals of this presentation. Discuss the benefits of Universal Analytics and Google Tag Manager

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Universal Analytics


Google Tag Manager

about @ analyticsninja
About @analyticsninja

Loves working with fun businesses

goals of this presentation
Goals of this presentation
  • Discuss the benefits of Universal Analytics and Google Tag Manager
  • Provide a general overview and training for how to use GTM, especially for UA implementations
  • Tactical implementation examples and how to use the resulting data
Caleb Whitmore

Sam Briesemeister

benefits of universal analytics
Benefits Of Universal Analytics
  • Custom Dimensions and Custom Metrics
    • Much better reportingthat ismore accessible across organizations, 20 vs 5 CVs for GA Standard.
  • Measurement Protocol
    • Offline conversions FTW!
  • GA’s First Attempt at Visitor Stitching
    • From what I can ascertain, still lots of room for improvement. Also, still not out of closed beta.
  • Many Settings Configured on the Backend
    • Less likely to cause problems due to coding fails
still missing
Still Missing…
  • Demographics
  • Remarketing
  • Most 3rd party plugins are stuck in _gaq land
  • Content Experiments
    • Not a huge loss
http www simoahava com web development universal analytics weather custom dimension
basic intro to gtm
Basic Intro to GTM
  • Tags pixels or javascript
  • Rules cause tags to fire
    • URLs / hostnames / referrers
    • Values or Conditions present in Macro
  • Macros values
  • Events  trigger rules to execute if conditions are not already present to fire tag when GTM loads.
sample data layer for publishers
Sample Data Layer for Publishers

Content Level

User Level

User Logged In State

Newsletter Subscriber

Registration Date

First Visit Date

# of Weekly Visits

  • Article publish date
  • Article publish hour
  • Author
  • Topics / Tags
  • Article Category
    • Sub Category
  • Free or Restricted Content
sample data layer for ecommerce
Sample Data Layer for Ecommerce

Product Level

User Level

Registered User

First Visit Date

First Purchase Date

Count of Purchase

Days Since Previous Purchase

User registration date

User Gender

Business Name (B2B)

Business Vertical (B2B)

  • Page Type
  • Product Category
  • Product Sub Category (etc)
  • Product Brand
  • Product Name
  • Product SKU
  • Product Price
  • Product Gender (if relevant)
  • Product Promo / Discount
smart data layer smart decisions page category
Smart Data Layer => Smart DecisionsPage Category

Page value, assuming properly configured ecommerce and goal values, is an excellent index to use when looking to analyze page level dimensions .

google tag manager transaction tags
Google Tag Manager Transaction Tags
  • GTM does not support custom dimensions for item hits (yet). You should still push all of the additional meta data into a transaction_products array.
  • Use a custom html ecommerce tag if you want to be able to look at secondary dimensions within the commerce reports.
  • Alternatively, just use event tracking and custom dimensions to rebuild the commerce data model.
  • Universal Analytics offers powerful new features (Custom Dimensions, Measurement Protocol, etc). You should deploy it if you haven’t do so yet.
  • Google Tag Manager is a free and powerful TMS. Requires someone who knows what they’re doing, but will make implementations more flexible, extendible, and manageable.
  • Strategic consideration of a business’s objectives and underlying business questions is the foundation upon which a Smart Data Layer is built, which will lead to Smart Decisions.
  • GTM allows one to navigate the balance between doing things that “right way” (i.e. proper on-page markup, fully defined CMS driven Data Layer) versus bootstrap approaches to get data quickly when IT may take months or more to complete tasks
  • Page value, assuming properly configured ecommerce and goal values, is an excellent index to use when looking to analyze page level dimensions such as product attributes or service offerings.
  • Dividing unique purchases of products by unique pageviews of those product pages yields a “look to book” ratio that should have a direct impact on decisions regarding product placement and ad spend. (Propensity to buy).
  • Use Server-Side hits to capture PROFIT metrics in GA. Profit is far more important than conversion rate or per visit value.