IT'S EASY AS 1-2-3

THE MONET HUMANIZED DATA™️ PLATFORM WORK FLOW PROCESS

  • 1. FRAME THE STUDY
  • 2. PROGRAM THE STUDY
  • 3. INITIATE STUDY

You define your study objective, content type and quantity of assets to be tested AND intended audience.

If you don’t know who the best audiences is for the content, we can implement our Audience Optimizer. Here we flip the process by recruiting a general pop sample and advise where we saw the greatest response pockets.

Monet customizes the questionnaire, formats study components and recruits sample.

Once sample is recruited, screened and filtered, we implement the study in three primary steps.

  • We passively capture subconscious emotions through proprietary, patented methodology and observe natural eye movement to see what people are looking at.
  • We collect conscious emotional reactions and verbatim comments to add dimensionality to our observations.
  • We survey attitudes and opinions.

4. ANALYZE FINDINGS

Using the patented, proprietary Monet AI data science platform, data analysis applies three primary scientific methods

Contextualization of Emotions ™️ (COE)

COE was developed by Dr. Anurag Bist as a means for leveraging the value of FACS to predict human reaction by understanding the nature of engagement and propensity to take action associated with specific displayed emotions.

Facial Action Coding (FACS)

FACS is is an anatomically based system for describing all visually discernible facial movement. It breaks down facial expressions into individual components of muscle movement proven to represent specific unspoken human emotional reactions. The system was originally developed and validated by Swedish anatomist Carl-Herman Hjortsjö and popularized and first published by Dr. Paul Ekman in 1978.

Circumplex Model of Affective Response

The Circumplex model plots the affective states of reaction from the neuropsychological systems of emotional engagement and arousal

Created with Lunacy

Monet codes unspoken facial emotions correlating subconscious emotions with conscious emotional reactions. Attitudes and opinions from the survey portion are then analyzed. Lastly, we harmonize all above data sets to decode the gap between what people say and what they really feel.

5. REPORT FINDINGS

Monet rapidly reports findings so decision makers can see the whole picture and make real time editing decisions. 
Specific measures reported include:

  1. The lift or drag effect of critical strategic and/or creative components.
  2. Emotion peaks and valleys on a scene by scene or framexframe basis.
  3. Using proprietary algorithms, all metrics captured and collected are harmonized into the following 3 MAIN MEASURES and reported along with a MONET SCORE of overall content effectiveness.
  • ATTENTION
  • EMOTIONAL ENGAGEMENT
  • ACTION

All scores are then compared to category norms for contextual evaluation and a final report is issued.

SDK & APIs

Mobile and SDK Solutions

Monet offers web and mobile SDKs for plugging Monet Analytics into existing applications. This lightweight client widget can be installed into your website, or via an Android or iOS SDK integration.