Engage 2013 - Integrated Campaign Reporting + MTA
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  • 1. INTEGRATED CAMPAIGN REPORTING+ MULTI-TOUCH ATTRIBUTIONBrandon RallsDirector, Digital Intelligence Lab
  • 2. Introduction
  • 3. Background •  Agency  Perspec,ve   •  Analy,cs  Consul,ng   •  Digital  Marke,ng   •  Data  Visualiza,on  
  • 4. Topics for Discussion1)  Performance  across  digital  channels  2)  Mul,-­‐touch  aBribu,on  (MTA)  3)  Integrated  repor,ng  4)  Implemen,ng  campaign  tracking  5)  Client  stories  
  • 5. Topic 1: Performance across digital channelsHow do I begin to understandcampaign performance across multiple digital channels?
  • 6. Digital Landscape
  • 7. Ways to Engage •  Landing page •  Hero image •  Specific CTAs •  Videos •  Whitepapers •  Promotions •  Lead gen forms •  Downloads •  Special offers
  • 8. Complex Agency Network Media •  Planning •  Buying •  Trafficking Creative •  Messaging •  Asset creation Development •  Site development •  Tagging & tracking
  • 9. Complex Agency Network
  • 10. Complex Agency Network Challenges •  Silos of data •  Disjointed story •  Different cadences •  Different formats •  Difficult to rationalize
  • 11. User BehaviorOur ObjectiveLink specific media placements to actions on our site anddetermine what attributes influence behavior
  • 12. Digital Ecosystem
  • 13. Topic 2: Multi-Touch Attribution (MTA)What is cross-channel, ormulti-touch attribution?
  • 14. MTA Overview First  Click   Last  Click   Equal   Weighted   100%   0%   0%   0%   0%   100%   33%   33%   33%   15%   35%   50%  •  Basic      approach   •  Most  common   •  Moderate   •  Most  sophis,cated   approach   sophis,ca,on  •  First  interac,on   •  Each  interac,on   receives  100%   •  Last  interac,on   •  Each  interac,on   propor,onately   receives  100%   receives  equal   weighted  •  Not  accurate   representa,on   •  Not  accurate   •  Good  direc,onal   •  Most  accurate   representa,on   perspec,ve   representa,on  Low     High  Sophis,ca,on   Sophis,ca,on  
  • 15. Example Scenario
  • 16. Example Scenario: First Click
  • 17. Example Scenario: Last Click
  • 18. Example Scenario: Equal Weight
  • 19. Role of ChannelTouch  type  helps  us  understand  role  each  channel  plays:   First  Touch   Secondary  Touches   Last  Touch  
  • 20. Topic 3: Integrated ReportingHow can integrated reporting withMTA enhance my understanding ofmy digital marketing campaigns?
  • 21. Decisions
  • 22. Key Areas to Focus•  AUDIENCE:  Who  you  are  sending?  •  CHANNELS:  Where  you  are  sending  them  from?  •  CREATIVE:  What  are  they  seeing  that  is  driving  their  response?  •  CONTENT:  What  do  they  do  when  they  land  on  your  site?  •  ACTIONS:  What  content  drives  con,nued  ac,on?  
  • 23. Sample Integrated Report •  Channel  performance   •  Top  first  touch  channels   •  Top  last  touch  channels   •  Average  touches   •  Average  latency   •  Touch  distribu,on   •  Paths  to  convert   •  Role  of  channels  
  • 24. Sample Questions
  • 25. Topic 4: Implementing Campaign TrackingHow do I implement campaigntracking to enable integrated reporting and MTA?
  • 26. The World as a Pivot Table
  • 27. How Do We Do This?
  • 28. Establish a ProcessIf  you  aren’t  proacLvely  capturing  data,  it  won’t  magically  become  available  once  your  campaign  goes  live.  
  • 29. Establish a Process
  • 30. Campaign Attributes•  Campaign  Type:  Seasonal  Promo,on  •  Campaign  Name:  Back  to  School  2012  •  Campaign  Goal:  Target  college  students  •  Launch:  July  2012  •  End:  September  2012  
  • 31. Audience Attributes•  Gender:  Male  •  Age:  18-­‐24  years  old  •  Geo:  In  the  United  States  •  SituaLon:  Going  off  to  college  •  ObjecLve:  Looking  for  a  new  laptop  •  Focus:  Focused  on  portability  vs.  processing  power  •  Desire:  Want  something  cool  and  cu`ng  edge  •  Digital  Space:  Highly  engaged  in  social  media  •  PlaVorm:  Highly  engaged  on  mobile  
  • 32. Media Attributes•  PlaVorm:  device  where  user  is  exposed  to  media    •  Channel:  types  of  media  you  buy  •  Publisher:  sites  where  users  are  exposed  to  media  •  TacLc:  method  for  delivering  media  •  Placement:  name  of  the  ad  that  is  displayed  •  CreaLve  type:  method  for  delivering  message  •  CreaLve  size:  size  of  the  actual  placement  displayed  •  CreaLve  name:  version  of  the  ad  displayed  
  • 33. Site & Content Attributes•  LocaLon:  where  on  the  site  the  ac,on  takes  place  •  Category:  the  general  category  of  the  ac,on  •  Name:  the  actual  name  of  the  ac,on  •  Type:  the  type  of  ac,on  performed  
  • 34. Webtrends Tags•  Base  JS  tag:  standard  tag  for  Webtrends  Analy,cs  that  generates  a  log  entry  •  WT.mc_id:  Webtrends  campaign  ID  (used  to  capture  media  placement  IDs)  •  WT.tsrc:  Webtrends  traffic  source  parameter  (used  to  capture  organic  sources)  •  WT.z_loc:  Custom  tag  (used  to  track  where  on  the  site  an  ac,on  occurs)  •  WT.z_cat:  Custom  tag  (used  to  specify  the  category  of  ac,ons)  •  WT.z_name:  Custom  tag  (used  to  specify  the  name  of  an  ac,on)  •  WT.z_type:  Custom  tag  (used  to  specify  the  type  of  ac,on)  
  • 35. Media Metrics•  Spend:  how  much  am  I  paying  to  get  my  message  out  there?  •  Impressions:  how  many  eyeballs  are  exposed  to  my  message?  •  Responses:  how  many  people  are  compelled  by  my  message?  •  Response  Rate:  how  efficient  is  my  media  at  ge`ng  people  to  respond?  •  Cost  per  Response:  how  much  does  it  cost  me  to  get  a  visit  to  my  site?  
  • 36. Web Metrics•  Visitors:  unique  number  of  people  who  came  to  your  site  •  Visits:  number  of  sessions  on  your  site  •  Bounce  Rate:  %  of  people  who  landed  on  your  site  but  did  not  engage  further  •  Visits  per  Visitor:  number  of  ,mes  people  return  to  your  site  •  Return  Visit  Rate:  %  of  total  traffic  who  come  back  to  your  site  •  Visit  DuraLon:  length  of  an  average  session  on  your  site  •  Views:  number  of  pages  rendered  on  your  site  •  Views  per  Visit:  average  number  of  pages  rendered  in  a  session  •  Conversion  AcLons:  number  of  engagement  ac,ons  performed  •  Conversion  Rate:  rate  at  which  engagement  ac,ons  are  performed  •  Cost  per  Conversion:  cost  of  driving  a  user  to  engage  •  AOV  (if  ecommerce):  average  size  of  an  order  placed  on  your  site  
  • 37. Linking Systems Together •  Aligning  media  IDs  to  WT.mc_id  enables  integra,on   •  Several  dependencies  to  ensure  process  works  as  expected   o  Ability  for  agency  to  pass  media  ID  value  used  by  ad  trafficking  tool  as  value  in   Webtrends  parameter   o  Standardiza,on  of  naming  conven,ons  in  the  lookup   o  The  ability  for  agency  to  provide  campaign  lookup  file  
  • 38. 1-to-1 Relationship
  • 39. Topic 5: Client Stories How has Webtrends helpedothers solve these problems?
  • 40. Red Bull Case Study
  • 41. Business Challenge
  • 42. Solution Overview
  • 43. Data Visualization + MTA Web-based data visualization •  Streamline reporting •  Enhance time to insight •  Provide comprehensive view •  Actionable through visualization
  • 44. Business Value
  • 45. Microsoft Case Study
  • 46. Background
  • 47. Business Challenge
  • 48. Webtrends SolutionWebtrends provided Microsoft with end-to-end support through campaign planning,vendor management, and ongoing analysis and recommendation
  • 49. Business Value •  Unified measurement approach •  Consistency in tagging and tracking •  Adoption of standardized processes •  Automated reporting •  Quick time to analysis •  Actionable insight and recommendations
  • 50. Final Thoughts
  • 51. Items to Remember
  • 52. Questions?
  • 53. Thank you Brandon  Ralls  Director,  Digital  Intelligence  Lab