Content analysis

Through image analysis, Datakalab measures the level of attention and reaction of online panelists who agree to be recorded in a statistical way when they are exposed to content. This methodology is developed in partnership with market research institutes and can be complemented by declarative questions.

Metrics:

  • Attention: position of the head and the position of eyes facing the content.
     

  • Emergence: sum of all emotions (positive + negative).

  • Adhesion: sum of all positive emotions.

  • Magic / Pain points: factors influencing the results (character, color, sound...).

Example - content analysis and optimization, second-by-second impact analysis:

Content_edited.jpg

They trust us

Analyzes the reactions of panelists who are exposed to a display content to optimize it.

Image de Jud Mackrill
Image de Christina @ wocintechchat.com

Analyzes the reactions of panelists navigating on tf1.fr to determine the level of attention of their audience, to measure advertising pressure and to optimize the user experience.

Analyzes the reactions of online panelists in front of a trailer or in a movie theater to optimize the content.

Image de Krists Luhaers