“Think·in Consumer Neuroscience”, is a neuromarketing company based in Chile. We perform neuromarketing research studies to understand the conscious and subconscious responses of the individuals towards any marketing stimuli, using technologies from the fields of neuroscience and biometrics measurements. We perform studies both in our lab and on point of sale.
With an Emotiv electroencephalogram (EEG) we can get the measurements of engagement/boredom, frustration, motivation and excitement. With the help Tobbi Eye tracker we can track visual attention, fixation points, pupil dilation, and create heat maps that show witch areas attracted the individuals the most. Last but not least with Emotient Facial Recognition Software we can analyze emotions such as fear, surprise, anger, disgust, contempt, sadness and joy. To work with these three technologies simultaneously we use iMotions Software.
Neuromarketing is a great innovation in marketing, however we are certain we can take it one step further. That´s why we need a machine learning expert and data scientist to develop: A model that would be able predict & identify customer behavior and emotional response to marketing stimuli’s using applications from the fields of neuromarketing and artificial intelligence.
In the identification process we want to ad more outputs and correlations coming from our existing technologies combined with traditional marketing methods, such as surveys or social networks analysis, to have a better answer when asking the questions like:
- How can we identify emotional response more accurately and have actionable insights from this process?
- Can extract more emotions using EEG, Eye tracker, Emotient, text emotion recognition and surveys?
- How do people feel when they see your commercial?
- What emotion is most related with your brand?
- What emotion is most related with buying decisions?
The prediction process is the most innovative one, currently there are some companies that already use predictive marketing analytics to predict when are online consumers most likely going to buy. However we want to create a model witch can predict offline behavior as well. Each of us generates digital exhaust and electronic bread crumbs on a daily basis. From the websites we browse to the brands we follow on Facebook, data is available to gain insight on habits, target behavior trends, emotional responses to future stimuli, among others. Some simple questions we expect to answer are:
- Where is my target audience going on winter holidays?
- Where should we advertise in 6 months from now?
- When is my audience most likely going online/offline shopping?
- If we release this commercial on the 4th of July how would my audience most likely feel?
- What segment is most likely to change brand loyalty?
- Name the behavioral trends of my target audience during the 7 seven days of the week, in the moths of December, January and February.
Finally the prediction & identification model should be able to recognize spoken natural language, to make the interaction with the software more natural and efficient. Our clients need to feel they are talking with their own personal marketing intelligence agent. We are looking for a lot of positive initiative and creative developers; doing some research we believe machine learning algorithms, predictive analytics and artificial neural networks will be needed in order to achieve our goal. However we are open to new ideas for the best approach to tackle this challenge. For example the idea of developing this model using WATSON´s API’s instead of creating a software from scratch.
If interested please send an estimated time of development and estimated cost.
If you need more information or examples of what we are looking for please feel free to contact us.