Transcript 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
• 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
THANK YOU
Caleb Whitmore
Sam Briesemeister
Benefits Of Universal Analytics
• Custom Dimensions and Custom Metrics
– Much better reporting that is more 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…
• Demographics
• Remarketing
• Most 3rd party plugins are stuck in _gaq land
• Content Experiments
– Not a huge loss
Use Case: Teams in
US West Coast, Europe, Australia, Israel
Surprise Client with Reason to Personalize
Surprise Client with Reason to Personalize
http://www.simoahava.com/webdevelopment/universal-analyticsweather-custom-dimension/
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.
Rules
Rules
Rules
Sample Universal Analytics Tags
Sample Universal Analytics Macros
Sample Universal Analytics Macros
Inside the Universal Analytics Tag
Tagging using
helper file vs. multiple tags / rules
Quickly extend implementation
Data Layer
Sample Data Layer for Publishers
Content Level
• Article publish date
• Article publish hour
• Author
• Topics / Tags
• Article Category
– Sub Category
• Free or Restricted Content
User Level
• User Logged In State
• Newsletter Subscriber
• Registration Date
• First Visit Date
• # of Weekly Visits
# Of Weekly Visits
dev.analyticsninja.co/periodic_visit.js
# Of Weekly Visits
dev.analyticsninja.co/periodic_visit.js
Date of First Visit
Tableau viz via @calebwhitmore
Accessing Restricted Content
Create Segments to compare
Conversion Rates of users who took specific action
Smart Data Layer => Smart Decisions
Smart Data Layer => Smart Decisions
Smart Data Layer => Smart Decisions
Course Technology > Course Name
Smart Data Layer => Smart Decisions
Sample Data Layer for Ecommerce
Product Level
• Page Type
• Product Category
• Product Sub Category (etc)
• Product Brand
• Product Name
• Product SKU
• Product Price
• Product Gender (if relevant)
• Product Promo / Discount
User Level
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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)
All custom dimensions require admin setup
Smart Data Layer => Smart Decisions
Page Category
Page value, assuming properly
configured ecommerce and goal values,
is an excellent index to use when looking
to analyze page level dimensions .
Smart Data Layer => Smart Decisions
Product Category
Smart Data Layer => Smart Decisions
Product Category
Smart Data Layer => Smart Decisions
Product Category
Smart Data Layer => Smart Decisions
Product Name
Smart Data Layer => Smart Decisions
Product Name  Product Promotion
Smart Data Layer => Smart Decisions
“Real” Page Value
Divide Unique Purchases
by Unique Purchases
Explore Profit Metrics in GA
Smart Data Layer => Smart Decisions
“Real” Page Value = Profit per Unique PV
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 for
CRM Integrations and B2B Lead Gen
Universal Analytics for
CRM Integrations and B2B Lead Gen
Summary
• 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.
Summary
• 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.
Summary
• 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.