Facebook and Google make a big chunk of money through the ads, not just any ads, targeted Ads, which they can do accurately after analyzing our online behavior, which includes our likes, comments, posts, pictures, our browsing history, the time we spend on a particular type of content etc. They have complex algorithms which can accurately classify a person and then serve them content and Ads which appeal to them.
But however smart the algorithms get, they are unable to record the affect which a particular content might have on a person. Does the person feel happy? Sad? Angry?… the reliance of current algorithms is on the time spent on content, frequency of interactions with similar content, interest in the content by family, friends etc. There is a need for a more accurate metric on customer feedback.
Steps in #iPhoneX and #FaceID: which solves the missing piece of real-time, accurate customer feedback which is displayed through the emotions exhibited in the face… this must be invaluable data for the advertisers who can launch pilots which receive feedback with very high accuracy, can segment and categorize based on real life, undisputed data right from the customer.
Comparing a person’s face (without them knowing) at different times and against different set of content has a potential to give an incredibly accurate feeling-o-meter
We can put a tape on our iPhone X’s camera, sensors, dot projector to guard against it, but if you spent a cool grand on a new iPhone, why would you? Apple may not be the first one to introduce this technology, but since they will make it mainstream, this will change the advertising game in a major way.
Published originally on LinkedIn on September 21, 2017