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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

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 Benefits Of Universal Analytics

Demographics Remarketing Most 3 rd party plugins are stuck in _gaq land Content Experiments – Not a huge loss Still Missing…

Use Case: Teams in US West Coast, Europe, Australia, Israel

Surprise Client with Reason to Personalize

development/universal-analytics- weather-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

Sample Universal Analytics Tags

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

Date of First Visit Tableau viz

Accessing Restricted Content

Create Segments to compare Conversion Rates of users who took specific action

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 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 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

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.