How AI & ML are changing consumer research — Dr. Duane Varan // MediaScience

Show Notes

• 01:54
  MediaSciences place in marketing

  MediaScience measures user emotion directly, instead of depending on people to tell you, which can be inaccurate. Their tools give you a detailed look at your customers on an individual level.
• 03:47
  How technological advancements changed consumer research

  Over the years weve used data to track our users' behaviors. With technological advancements like biometrics, we now have a greater chance to really get to know them better.
• 06:52
  How to evaluate performance with neuroscience

  To check an ads performance, metrics like peoples heart rate and facial expressions are used. MediaScience creates a simulated home environment to test reactions to the ads.
• 10:49
  Lab Data VS Field Data: Quality assurance

  A home environment is simulated to make the experience more real. While machines like EEGs are obvious, there are other more subtle measures that go unnoticed by the user.
• 12:56
  Popular metrics used to measure user response

  Some metrics used to measure user reactions include facial muscle movements like lip and eye movements. You can also track response speed to measure awareness.
• 14:29
  Who uses MediaScience and why

  The major TV networks make up the bulk of MediaSciences clients. Any major innovation in the marketing world generally gets tested by MediaScience first.
• 16:07
  The break ad experience

  An interstitial helps with user experience by providing a better break experience. While your customer experience improves, the drawback depends on your priority.
• 17:37
  Testing new ad formats

  The approach for this would be a comparison testing to gauge user emotion. So youd test the performance of the new ad format against a regular ad format used before.
• 19:46
  Evaluating brand associations

  Over time, people form brand associations. MediaScience tests this by evaluating user reactions to your brands at different times and settings.
• 21:33
  MediaScience versus comparative data analysis

  You wont get the most accurate data just by comparing the usual analytics data from 2 ads. MediaScience shows not only end results but how you got there.
• 23:19
  Evaluating the why through testing

  Testing an ad in aggregate, you miss the smaller elements that produce your result. Using machine learning and AI, theres no need to make assumptions about how your user feels.