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Facial recognition and analysis in relation to big data and IoT

Understanding the relationship between emotive states and buying habits is a holy grail for marketers.

Facial recognition and analysis

In relation to big data and IoT

A study of dogs showed they are of studying their master’s face, determining emotional states, and making decisions based on these determinations. Studies like this are adding to the pool of Big Data covering facial recognition. Understanding the relationship between emotive states and buying habits is a holy grail for marketers. The extraction of Big Data from IoT devices will drive marketing to new techniques. Could content marketing become extinct?

Think of an emotion; any emotion. Now think of what kind of facial expression you make when you express the emotion. The two are congruent. In the next few years, small recognition devices, more than just video cameras, will record your face for expression, heat, and moisture. This info will supplement a cache of Big Data. This data can be mined for its emotional context in relation to products on the shelves.

Pretend you’re a construction worker who’s had a difficult day. You’re stopping in to grab some groceries and beer after work. In front of the beer isle, you’re indecisive about which brand to purchase. One on hand, you don’t want to spend too much and should buy a domestic. On the other, you had a crappy day and want the beer that you really enjoy.

If you were recorded making your decision to grab the more expensive beer, the data would show your mood and your emotive state when entering the store and how it changed in relation to a purchase decision. This is a gold mine of information. Small bits of measurable data lie in this scenario. What’s the relation between the construction worker’s grumpy mood and the decision to buy the more expensive brand of beer? If Moore’s Law is considered in relation to facial expression, the next few years of R&D may give us the perfect ratio of marketing content to optimized sales funnel. Facial expression coupled with voice recognition and other measurable variables will make a huge strides in conversion optimization. This is because marketing will be able to touch people on an emotional level. Your funnel is now steeper and more deftly refined to capture more of your niche. These individuals now make up your customer market assets. Connected customers are the ones who post positive reviews and share on social media. They do this because of feeling connected to an “in-group”.

Facial expression recognition was pioneered by Dr. Paul Ekman in the 1970s. He created a catalog of over 5,000 muscle movements that create a map expressions and their emotive values. He know works as an advisor for Emotient Inc., a young company working on expanding Ekman’s work into effective algorithms for determining feelings. Outside of R&D, there has been a boom in the analysis side of the equation. Firms like Emotiva have turned analysis of facial recognition into smart data. They offer a multitude of different measurement analysis. Their offerings can put a help boost a company’s brand to the forefront of their market. 

Emotiva is changing the face of analysis with these cool modalities:

  • Screen new ideas Test new product concepts and ideas
  • Diagnosis and optimization for advertising Create or improve advertising campaigns
  • Media measurements and comparisons Measurement and optimization of video clips for the best audience engagement
  • Virtual shopping and packaging testing Packaging design and shopping UI with the most conversion.
  • Client evaluation and surveys Measured responses with “absolute certainty”
  • Website usability evaluations Analysis and improvement of website UI

 

Photo by Joshua Rawson-Harris on Unsplash

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