From Big data to feel data to capture consumers' emotions and use them like any other marketing data in order to improve brand marketing strategies.

In recent years, the keys to understanding consumer behavior in many brands have tended to evolve towards a more emotional approach. From now on, they are based not on logical factors of visibility, utility or price optimization, but rather on the emotions generated by the brand and its product.

The definition

The notion of emotional data includes all data relating to a consumer or group of consumers. It can be collected and processed in such a way as to reflect the emotions that individual or group felt.

Emotional data are collected as part of advertising effectiveness studies. However, it can also be collected on a less ad hoc basis to measure emotions about a brand or event. They can also be collected as part of customer support (telephone, mail, etc.).

Feel-data or in other words emotional data are able to measure, in a quantified way, the emotional intensity of consumers. 

How it works ?

DatakaLab has developed a sensory sensor solution. It makes it possible to measure in real time and every second certain physiological and emotional reactions of individuals. They are equipped with a bracelet to a content experience, an advertisement, a product, a service or a consumer journey.
Important clues are collected: electrodermal conductance reflecting emotional intensity, eye movement, pupil dilation. Some 30,000 data per second can be mixed. Thanks to its neuroscientific tools and its proprietary algorithm, Datakalab calibrates and aggregates the data obtained, giving rise to feel data. Alexandre Letexier, Feel data Chief Analyst, explains: “The advent of Feel data is a revolution for Big data. Now, thanks to emotional data, we can better understand behaviors, anticipate trends and predict new, more efficient and effective models.”

Role and importance of feel data

It is scientifically proven that emotion plays a major role in all human behavior, from perception to memorization. Indeed, emotions are responsible for 95% of our decisions. For this reason, the principal objectif is to analyze consumers’ emotions when faced with an advertisement, product or service.

In addition to, this method will determine through neuromarketing tools which colours, contextual elements need to be improved to maximize an advertisement. A dashboard makes it possible to visualize in real time the emotions customers felt. The aim is to reverse marketing so that consumers can drive future brand services and products with their emotions. In the face of an advertising message, these emotional data will make it possible to better calibrate it and adapt it to the client’s emotional profile. Emotion then becomes a measurable factor. 

If today, the memorization of an advertising message is directly correlated with the reputation of an advertiser, feel data challenges this general truth. Indeed, it tends to impose itself as a new performance lever for little-known or medium-known brands that are unable to compete with the major players in the ecosystem: reaching the hearts of their audience to enter into a long-term loyalty relationship, by forcing a place in their brain thanks to the emotion that allows a significant memorization rate.