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       At the core of our data collection is connectivity – not just  We  currently  support  our  clients  in  the  area  of
       from  one  device  to  one  platform  but  multi-device-multi-  Descriptive  analytics  -  data  processing,  mining  and
       platform  connectivity.  With  mobile  thrown  into  the  mix,  visualization.  The  goal  is  to  develop  the  online
       brands  can  use  device  proximity  or  location-specific  interactive  data  visualization  platform  further  and
       activations  to  integrate  both  in-vehicle  screens  and  provide  customers  with  the  tools  so  that  they  can
       mobile devices and engage consumers in transit, when  manipulate and extract useful business knowledge and
       they are more likely to be active on a screen.      insights aligned to their business goals.
       Such  a  sophisticated  use  of  data  is  driving  the  senior  The next phase of predictive analytics is where we use
       management decision-making process.                 machine learning to build  models to  predict outcomes
                                                           to a level of certainty. For example, based on a set of
       Gartner predicted that 30 per cent of enterprise access   multi-variates when a customer engages on a particular
       to  big  data  would  be  through  intermediary  data  broker   advertisement,  such  as  a  new  bar  at  about  9  pm
       services,  to  support  business  decisions.    To  support   Saturday night, travelling in a specific direction from a
       client’s data needs, IDOOH’s partner ecosystem of fleet   certain  location,  the  data  predicts  that  they  are  going
       owners,  ride-sharing  companies,  content  providers  and   out to town for a night out.
       brands  benefit  from  the  all-encompassing  data
       collection,  where  all  data  points  are  captured  Building on predictive analytics capability, we prescribe
       consistently.  They  are  subsequently  used  for  data  a  campaign’s  roll-out  through  a  push-pull  model  –  in
       modelling to extract valuable information in the future for  that, we can drive, push or sequence the most relevant
       a variety of users across different industries.     content  to  the  customer,  based  on  real-time
                                                           information.  For  instance,  based  on  the  above
       Driving the future - From data to analytics         example, we could promote a new nightclub event with
                                                           a  discount  coupon  in  exchange  for  contact  details  to
       Beyond  data  collection,  IDOOH  is  positioned  to  help
       brands  with  information  for  predictive  purposes.  One   support lead generation and track sales conversions.
       such means is the utilization of metadata to find analysis  Through all three types of data analytics, we can help
       -worthy  big  data  needed  in  order  to  introduce  new   drive  the  business  agenda  by  arming  marketers  with
       products and services that might also be of interest. For  insightful  data  and  feedback  in  real-time.  Conversely,
       instance, this could be to decipher passenger viewership   consumers  also  benefit  from  more  relevant  and
       content  and  engagement  to  derive  insights  into   engaging  content  delivered  to  them.  Consumer  habits
       consumer preferences and behaviors.                 and  behaviors  are  constantly  changing  in  an  ever-
                                                           evolving  digital  economy.  The  only  way  to  detect  that
       There  are  also  plans  to  further  develop  IDOOH’s  big   shift is to trust the data. ◊
       data  architecture  with  descriptive,  predictive  and
       prescriptive analytics.                                   By Mark Capogreco and Malcolm Wong, IDOOH

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