Using AI to understand customer feelings, we create focused strategies to raise sales and lower churn
Ad Testing or Advertising Research mainly focuses on calculating the effectiveness of an ad. Traditionally, it has been done through detailed customer feedback and responses. An ad is played for the customers and post-competition, people are asked to critique it. Passive Expression Analysis allows the marketer to bypass this.
What the traditional method does is that it allows the customers with time to reflect and form rational responses (triggering System 2 Thinking), thereby squelching the raw, instinctive, emotional response (System 2 Thinking).
As Harvard Business School Emeritus professor, Gerald Zaltman claims “95 percent of all cognition occurs in the subconscious mind”. He also explains how, “many consumers report handling competing brands and comparing prices at the point of purchase. However, observations of these same consumers often reveal that they don’t even look at alternatives to the chosen brand."
Therefore, monitoring carefully thought out, rational responses is clearly not the best way to test an advert.
Passive Expression Analysis, with the use of Face recognition allows marketers to arrest and analyse raw, unfiltered and instinctual responses of the customers to an ad. It provides detailed insights into a customer’s response to an ad video by focusing on the most significant element for creation of Brand Love and Brand Loyalty- Emotion. Therefore, analysis methods (like Passive Face recognition) that go beyond self-reported feedback are far more accurate in predicting the impact of an ad on its target audience. Unlike standard feedback and survey methods, they are also non-intrusive and non-disruptive.Organisations often spend an exorbitant amount of money on ads. With Passive Expression Analysis, it is possible to be certain of how much impact the ad will create and what its enjoyment quotient is.
The Facial Recognition Software arrests the changes in a viewer’s expressions as he watches an ad video.
The expressions are then broken down into various attributes (facial features that can be detected such as age, gender, head pose, facial hair and smile) and analysed.
In Ad Testing, the attributes that are primarily focused on are Head Pose, Smile and most importantly, Emotion.
Emotion, however, is measured across 8 categories. These are-
The software scrutinises the viewer’s face for these elements every minute fraction of a second, leading to a fairly accurate analysis of the impact of the ad. This empowers the decision makers to take an informed decision, backed by extensive data.
It is undoubtable that analysing consumer’s facial expression, with the help of Face Recognition software is the strongest predictor of ad impact and thereby, sales. The world of advertising research is evolving rapidly. Markets and marketing practices must evolve alongside it, in order to survive and flourish.
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