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INTEGRATED CAMPAIGN REPORTING + MULTI-TOUCH ATTRIBUTION Brandon Ralls Director, Digital Intelligence Lab

Engage 2013 - Integrated Campaign Reporting + MTA

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Page 1: Engage 2013 - Integrated Campaign Reporting + MTA

INTEGRATED CAMPAIGN REPORTING + MULTI-TOUCH ATTRIBUTION Brandon Ralls Director, Digital Intelligence Lab

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Introduction

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•  Agency  Perspec,ve  

•  Analy,cs  Consul,ng  

•  Digital  Marke,ng  

•  Data  Visualiza,on  

Background

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1)  Performance  across  digital  channels  

2)  Mul,-­‐touch  aBribu,on  (MTA)  

3)  Integrated  repor,ng  

4)  Implemen,ng  campaign  tracking  

5)  Client  stories  

Topics for Discussion

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How do I begin to understand

campaign performance across

multiple digital channels?

Topic 1: Performance across digital channels

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Digital Landscape

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•  Landing page

•  Hero image

•  Specific CTAs

•  Videos

•  Whitepapers

•  Promotions

•  Lead gen forms

•  Downloads

•  Special offers

Ways to Engage

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Complex Agency Network

Media •  Planning •  Buying •  Trafficking

Creative •  Messaging •  Asset creation

Development •  Site development •  Tagging & tracking

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Complex Agency Network

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Complex Agency Network

Challenges •  Silos of data

•  Disjointed story

•  Different cadences

•  Different formats

•  Difficult to rationalize

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User Behavior

Our Objective Link specific media placements to actions on our site and determine what attributes influence behavior

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Digital Ecosystem

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Topic 2: Multi-Touch Attribution (MTA)

What is cross-channel, or

multi-touch attribution?

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MTA Overview

First  Click   Last  Click   Equal   Weighted  

•  Basic      approach  

•  First  interac,on  receives  100%  

•  Not  accurate  representa,on  

100%   0%   0%   0%   0%   100%   33%   33%   33%   15%   35%   50%  

Low    Sophis,ca,on  

•  Most  common  approach  

•  Last  interac,on  receives  100%  

•  Not  accurate  representa,on  

•  Moderate  sophis,ca,on  

•  Each  interac,on  receives  equal  

•  Good  direc,onal  perspec,ve  

•  Most  sophis,cated  

•  Each  interac,on  propor,onately  weighted  

•  Most  accurate  representa,on  

High  Sophis,ca,on  

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Example Scenario

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Example Scenario: First Click

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Example Scenario: Last Click

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Example Scenario: Equal Weight

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Role of Channel

First  Touch   Last  Touch  Secondary  Touches  

Touch  type  helps  us  understand  role  each  channel  plays:  

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Topic 3: Integrated Reporting

How can integrated reporting with

MTA enhance my understanding of

my digital marketing campaigns?

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Decisions

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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?  

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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  

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Sample Questions

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Topic 4: Implementing Campaign Tracking

How do I implement campaign

tracking to enable integrated

reporting and MTA?

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The World as a Pivot Table

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How Do We Do This?

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Establish a Process

If  you  aren’t  proacLvely  capturing  data,  it  won’t  magically  become  available  once  your  campaign  goes  live.  

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Establish a Process

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Campaign Attributes

•  Campaign  Type:  Seasonal  Promo,on  

•  Campaign  Name:  Back  to  School  2012  

•  Campaign  Goal:  Target  college  students  

•  Launch:  July  2012  

•  End:  September  2012  

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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  

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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  

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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  

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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)  

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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?  

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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  

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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  

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1-to-1 Relationship

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Topic 5: Client Stories

How has Webtrends helped

others solve these problems?

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Red Bull Case Study

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Business Challenge

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Solution Overview

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Data Visualization + MTA

Web-based data visualization •  Streamline reporting

•  Enhance time to insight

•  Provide comprehensive view

•  Actionable through visualization

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Business Value

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Microsoft Case Study

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Background

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Business Challenge

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Webtrends Solution Webtrends provided Microsoft with end-to-end support through campaign planning, vendor management, and ongoing analysis and recommendation

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Business Value •  Unified measurement approach

•  Consistency in tagging and tracking

•  Adoption of standardized processes

•  Automated reporting

•  Quick time to analysis

•  Actionable insight and recommendations

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Final Thoughts

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Items to Remember

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Questions?

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Thank you Brandon  Ralls  

Director,  Digital  Intelligence  Lab