O slideshow foi denunciado.
Utilizamos seu perfil e dados de atividades no LinkedIn para personalizar e exibir anúncios mais relevantes. Altere suas preferências de anúncios quando desejar.

Universal Analytics and Google Tag Manager - Superweek 2014

22.898 visualizações

Publicada em

Universal Analytics and Google Tag Manager - Superweek 2014

  • Seja o primeiro a comentar

Universal Analytics and Google Tag Manager - Superweek 2014

  1. 1. About @analyticsninja Loves working with fun businesses
  2. 2. 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
  3. 3. THANK YOU
  4. 4. Caleb Whitmore Sam Briesemeister
  5. 5. 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
  6. 6. Still Missing… • Demographics • Remarketing • Most 3rd party plugins are stuck in _gaq land • Content Experiments – Not a huge loss
  7. 7. Use Case: Teams in US West Coast, Europe, Australia, Israel
  8. 8. Surprise Client with Reason to Personalize
  9. 9. Surprise Client with Reason to Personalize
  10. 10. http://www.simoahava.com/webdevelopment/universal-analyticsweather-custom-dimension/
  11. 11. 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.
  12. 12. Rules
  13. 13. Rules
  14. 14. Rules
  15. 15. Sample Universal Analytics Tags
  16. 16. Sample Universal Analytics Macros
  17. 17. Sample Universal Analytics Macros
  18. 18. Inside the Universal Analytics Tag
  19. 19. Tagging using helper file vs. multiple tags / rules
  20. 20. Quickly extend implementation
  21. 21. Data Layer
  22. 22. 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
  23. 23. # Of Weekly Visits dev.analyticsninja.co/periodic_visit.js
  24. 24. # Of Weekly Visits dev.analyticsninja.co/periodic_visit.js
  25. 25. Date of First Visit Tableau viz via @calebwhitmore
  26. 26. Accessing Restricted Content
  27. 27. Create Segments to compare Conversion Rates of users who took specific action
  28. 28. Smart Data Layer => Smart Decisions
  29. 29. Smart Data Layer => Smart Decisions
  30. 30. Smart Data Layer => Smart Decisions
  31. 31. Course Technology > Course Name
  32. 32. Smart Data Layer => Smart Decisions
  33. 33. 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)
  34. 34. All custom dimensions require admin setup
  35. 35. 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 .
  36. 36. Smart Data Layer => Smart Decisions Product Category
  37. 37. Smart Data Layer => Smart Decisions Product Category
  38. 38. Smart Data Layer => Smart Decisions Product Category
  39. 39. Smart Data Layer => Smart Decisions Product Name
  40. 40. Smart Data Layer => Smart Decisions Product Name  Product Promotion
  41. 41. Smart Data Layer => Smart Decisions “Real” Page Value
  42. 42. Divide Unique Purchases by Unique Purchases
  43. 43. Explore Profit Metrics in GA
  44. 44. Smart Data Layer => Smart Decisions “Real” Page Value = Profit per Unique PV
  45. 45. 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.
  46. 46. Universal Analytics for CRM Integrations and B2B Lead Gen
  47. 47. Universal Analytics for CRM Integrations and B2B Lead Gen
  48. 48. 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.
  49. 49. 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.
  50. 50. 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.

×