Luth  Research  Whitepaper  Tracking  Digital  Ads:  Facing  Up  to  the  Challenges          6/10/2014          Prepared  By:  Becky  Wu,  Ph.D.  Sr.  Executive  Vice  President  Research  Luth  Research,  Inc.                        

Digital  advertising  measurement  technologies  have  evolved  significantly  in  recent  years.  As  the  industry  responsible  for  quantifying  the  value  of  advertising,  we  have  advanced  from  earlier  paradigms,  including  last-­‐click  attribution.  However,  the  practice  is  not  getting  easier  as  the  current  ecosystems  in  which  ad  measurement  research  take  place  are  laden  with  fragmented  technological  capabilities,  non-­‐standardized  metrics,  and  varying  privacy  concerns.      To  begin  solving  these  problems,  the  first  step  is  to  become  crystal  clear  and  cognizant  about  the  leading  challenges  for  the  methods  available  today.    Three  areas  warrant  a  more  widely  participated  discussion.      The  foremost  area  is  accuracy  of  tracking  individuals  associated  with  ad  exposure  and  their  ensuing  activities.  While  it  sounds  easy,  many  popular  tracking  methods  are  unable  to  identify  the  individuals  accurately.  Cookie  tracking  is  subject  to  cookie  deletion  and  duplication.  Digital  fingerprinting,  a  newly  emerging  technique,  takes  device  types,  operating  systems,  IP  addresses,  and  other  device  configuration  attributes  into  consideration  while  turning  these  inputs  into  a  statistical  estimation  to  determine  the  same  or  different  persons.  These  estimations  are  often  subject  to  false  matching  due  to  switching  between  mobile  network  and  Wi-­‐Fi  IP  address  assignment,  which  is  a  common  event  with  Apple  device  configuration.                The  second  area  relates  to  the  essential  goal  of  advertising  tracking  –  to  gauge  advertising’s  full  impact.  While  we  have  moved  beyond  the  last-­‐click  mindset,  we  haven’t  been  able  to  have  enough  visibility  into  post-­‐click/post-­‐impression  behaviors  to  do  this  job  right.  The  most  prevalent  tracking  mechanism,  cookie  tracking,  has  been  used  to  determine  ad  exposure/impression,  and  post  ad  conversion  if  the  conversion  happens  within  a  relatively  short  period  of  time  following  the  exposure.  This  approach  does  not  offer  the  ability  to  observe  and  capture  the  lion’s  share  of  the  individual’s  digital  activities  that  can  be  relevant  to  ad  impact.  An  individual’s  visits  to  websites  of  interest,  searches,  video  views,  and  purchases  related  to  the  brand  and  its  competitors  are  left  out  from  this  process.      Adding  to  the  mix  of  challenges  is  mobile  tracking,  which  is  increasingly  critical  to  marketers.  The  mobile  environment’s  biggest  drawback  is  its  absence  of  standardization  in  abilities  to  track  because  it  lacks  the  more  established  tracking  mechanisms  found  in  the  PC  digital  world.  Cookie  tracking  is  not  feasible  with  

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mobile  apps.  iOS  has  shifted  from  Universally  Unique  Identifier  (UUID)  to  Advertising  ID,  which  is  created  uniquely  for  each  individual  user.  It  can  be  reset  by  the  user  and  Apple  policy  prohibits  its  integration  with  other  data  sources  to  mitigate  privacy  concerns.  The  Advertising  ID  is  often  employed  to  tie  app  downloads  to  individual  users.  On  Android,  advertisers  can  use  Android  Referrer  to  accomplish  a  similar  goal.  However,  neither  feature  can  adequately  address  the  need  to  track  in-­‐app  advertising,  where  ads  are  dynamically  distributed  across  vast  and  diverse  mobile  apps.      Heeding  the  above  complex  issues,  Luth  Research’s  ZQ  Intelligence™  digital  behavior  tracking  technology  presents  an  opportunity  for  fresh  thinking  in  advertising  measurement.  At  its  very  core,  ZQ’s  ad  tracking  technology  consists  of  two  components:  1)  the  ability  to  identify  ad  tags  that  are  generated  for  ad  creatives  when  they  are  being  served,  and  2)  the  ability  to  collect  the  user’s  digital  data  across  browsers,  operating  systems,  and  devices.  Because  each  ad  creative  must  have  a  unique  ad  tag  in  ad  serving,  detecting  the  ad  tag  is  the  surest  way  to  accurately  pinpoint  if  and  where  the  ad  is  being  shown  to  the  user  across  publishers  and  ad  networks.  This  detection  mechanism  is  not  effective  without  ZQ’s  holistic  digital  behavior  data  collection.  After  a  user  has  downloaded  the  tracking  technology,  ZQ  captures  granular  http/https  requests  and  responses  from  both  PC  and  mobile  devices.  Specifically  for  mobile,  ZQ  enables  unified  data  collection  across  iOS  and  Android,  and  across  mobile  web  and  mobile  app.  The  ad  tag  identification  is  performed  for  the  target  ads  within  this  digital  data  with  tremendous  depth  and  breadth.  More  importantly,  ZQ  makes  it  possible  to  directly  correlate  the  individual’s  ad  tag  exposure(s)  with  his/her  other  digital  activities  collected  24/7  and  over  time  with  user  permission.  Hence,  post-­‐click/post-­‐impression  attribution  is  no  longer  an  unattainable  ideal  for  ad  measurement.      Luth  Research’s  ZQ  Intelligence  offers  a  powerful  alternative  in  tracking  advertising  impact.  Its  advantages  lie  in  being  platform  agnostic,  breaking  down  ecosystem  fragmentation,  precise  ad  detection,  deep  in-­‐app  ad  visibility,  and  providing  a  single-­‐source  view  of  the  entire  consumer  digital  journey.  Unprecedented  challenges  call  for  critical  thinking  and  willingness  for  marketers  to  step  outside  of  the  traditional  toolkits.  With  its  distinct  benefits,  ZQ  helps  marketers  unleash  the  true  potential  of  digital  marketing  with  clarity  and  accountability.