Feeder is a Machine Learning AI created to predict the success of video contents analyzing audiences’ reactions and emotions in real time through facial coding technology. In terms of how the product and the technology work, basically the facial recognition tracks people’s micro-expressions while they watch the content creating a frame-by-frame analysis of their reactions in real time. Each one of the micro-expressions we humans do are unconscious and directly related to our emotions (happiness, fear, sadness, disgust, etc). Thanks to their unique algorithm, Feeder is able to translate these emotions into actual qualitative KPIs, such as attention, validation, impact or engagement, among other parameters under a frame by frame basis, giving customers an accurate tool for understanding their audiences while measuring the success rate of their videos in the most easy way you can imagine.
Interview with Pablo Filomeno, CEO & Co-Founder of Feeder.
Easy Engineering: What are the main areas of activity of the company?
Pablo Filomeno: We are mainly focused on helping marketing agencies, marketing professionals and content creators to help them analyzing their campaigns’ audiences even though we are also crating products for the movie industry and we are working in a couple pilots in the health industry.
E.E: What’s the news about new products/services?
P.F: We will be launching different versions of our product by the end of the year, targeting not only marketing agencies but also giving service to other verticals and other type of companies. Our vision is putting our technology to the service of every content creator that has the need or the will of getting to understand the audience they’re addressing in a more qualitative and better way. Also, we intend to use our technology to help our customers not only under a content creation perspective but in as many ways as possible so we are also putting our tech in service of some health companies.
E.E: What are the ranges of products/services?
P.F: Right now we are offering different approaches for using our technology. On one way we are assisting market research and marketing agencies on their focus groups installing cameras and adding a new layer of emotional information to the session using our algorithm, we are also working as a consultancy with some of our customers, but mostly we have customers paying our regular monthly subscription. The tool was born as a Saas (Software as a service) tool with different prices according to the needs of every user.
E.E: What is the state of the market where you are currently active?
P.F: There are actually many good companies out there doing an amazing job performing emotional analysis through facial recognition technology, especially in the United States and in the UK. But Feeder is the only solution in the market that is able to provide of an accurate emotional analysis based on micro-expressions under a frame by frame basis through a unique algorithm that is able to translate this information into actionable qualitative kpi’s, without any hardware required.
E.E: What can you tell us about market trends?
P.F: The emotional analytics sector is experiencing significant growth, driven by increasing demand across various industries and technological advancements.
The constant integration of technologies such as AI, biometrics, and facial recognition is a significant driver of market growth. These technologies enable more accurate and efficient emotion recognition, enhancing applications like customer experience management, sales and marketing. Especially the retail sector will be facing many ethical challenges in terms of GDPR when adopting these technologies.
E.E: What are the most innovative products/services marketed?
P.F: Both our algorithm and our predictive AI are two of the most innovative products in the market in terms of content and audience analytics. Our model is constantly learning and we expect to launch our next version by the end of the year.
E.E: What estimations do you have for 2024?
P.F: We are focused on the development of our next model for addressing new markets, delivering new data, and creating in-depth analytics in real time to improve the way people creates content.